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Digital Pathology 2017

About Conference

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engineering jobs |

 

The 2nd international Conference on Digital Pathology, which is going to be held during November 15-16, 2017 at San Antonio, USA, organized by ConferenceSeries Ltd Conferences will bring together world class pathologist, researchers, professors and scientists to discuss strategies and advancements in Digital Pathology. ConferenceSeries Ltd Organizes 300+ conferences, 500+workshops and 200+symposiums on Clinical, Medicine, Pharma and Science & Technology every year across USA, Europe, Asia, Middle East, Australia and UK with support from 1000 more scientific societies and Publishes 500 open access journals which contains over 30000 eminent personalities, reputed scientists as editorial board members.

Digital pathology is make use of computer technology to switch analog microscopic images into digital images.  For this gathering we will be using the term Whole Slide Imaging, abbreviated “WSI”, also known as digital imaging, virtual slides, or virtual microscopy. The complete slide imaging systems consist of hardware - a microscope, camera, scanner, computer and monitor and the associated image software.  The technical system performs image acquisition, processing, archiving and repossession. 

 

Sessions & Tracks

2nd International Conference on Digital Pathology November 15-16, 2017 San Antonio, USA, Digital pathology | image analysis | intellectual property | legal | patent | telepathology | whole-slide imaging |Digital pathology network | whole slide image | virtual microscopy | DICOM | data federation | integration | false positive detection | computer-aided prognosis | mitosis cell karyorrhexis digitized histological images | histopathological examination | patient pediatric tumor | sympathetic nervous system | International Neuroblastoma Classification | inter-reader variation | intra-reader computer-assisted analysis approach | likelihood functions | probability map generation | component-wise 2-step thresholding | slides | lesions | brightness adjustment procedure | statistical classification method | local-window-based verification strategy | normal retinal Gleason score | Tumor staging | Pattern Recognition | Automated | Reproducibility of Results | Retina | Vessels | Sensitivity and Specificity | user interface archiving | managing | tissue staining methods | spectral overlap | intensity | signatures | computer assisted diagnosis | stain density estimation techniques | separation | spread signal decorrelation | color imaging sensor | unblinded blind deconvolution matrices estimation | Beer-Lambert intensity decay law | Maxwellian chromaticity based regularization factor | PAS stained cervical biopsy samples | VG HE 6-fold cross validation technique | uptake measurement | immunohistochemical compound state-of-the-art nucleus-cell segmentation approaches | differential interference contrast | fluorescence | electron principal components kernel matrix | PCA-based feature scoring PCA | NLDR algorithm | dataset | breast cancer | prostate t-test | Fisher Gini index | accuracy | TMA processing | specimen characteristics | low-contrast unstained sample effect | spongiosis diagnosis reliability | cerebral edema poultry brain | class | clinical tool | laboratory analytic capability | short turn-around time | consistency | adjacent section | scan registration | automated registration lines-based features | high-level morphological extraction | texture tiled grid | H&E histopathology patch-level single group-level ground-truth label | graph-based MIL mi-Graph | spatially-correlated instances | Bayesian logistic regression | color | cancer grading | quantification | query graphs | key regions | graph embedding | textural management | storage | care | computer-based algorithms | sequence acquisition | focus measure computation | volume creation | rendering | complex continuous wavelet transform phase angles | retina circinates | drusens | microaneurysms | t-statistics | entropy | Battacharrayia statistic | receiver operating characteristic | component ROC | support vector machines | SVM | polynomial basis function kernels | radial leave-one-out envelope step | high blot hemorrhage | low subretinal | exudate | subretinal power law regression estimates | fractal properties | Fourier domain | fat globules | hepatic anatomical structures | central veins | portal tracts | grey value distribution | magnification | shading | standardization | medical ICI | factor discriminate neural decision history | content information | routine surgical Nottingham histologic score resolution deep learning high-resolution pixel sliding window operation | classifier | patch representation | imaging | χ2 histogram distance | universal quality quantifying structural distortion | human-perceived standardization quality | robust systems | object-based representations | pixels | noise | components | spatial object definition | multityped objects | shape size local subregions | dominant blob scale | colon pertinent second opinions | traceable brain cervix lung imagery | hematoxylin-eosin protocols | diagnostic biomarkers | nuclei segmentation | lab workload reduction | optical microscope | WSI scanners | cost-effective digitization | automatic hematoxylin | eosin-stained grades | AdaBoost-based labeling | superpixel partitioning | whole-mount tissue | prostatectomy patients | ER+ FOV parallelization | distributed graphics processors | correlation updating nuclear centroid | deconvolution | watershed MRI | protein expression | nonlinear dimensionality LCIB | image-based risk IbRiS | lymphocytic infiltration | Her2+ histopathology | triple-negative dynamic contrast enhanced DCE grade | digitzed needle biopsy | mass spectrometry | disease recurrence | personalized medicine | high-dimensional vector | Varma-Zisserman texton-based scheme | auto-fluorescence compensation | preprocessing | latent semantics | block Gabor structure | nucleus-based pathological probabilistic semantic models | desktop PC | pathologist annotated ground truth | popular supervised boosting trees | k-means clustering bioinformatics applications | prognostic predictions | time 6 s | histology computerized program | grading pyramid | multiple levels | first-order filter AdaBoost ensemble tree classifiers | resolutions | Gamma Markov prior model | pairwise cancerous gland | distance-hull patches | NMF-based computation module | normalization | spectra | matrix inverse depths | reasoning | achromatic circular von Mises mixture hue color-based soft-clustering solution | mixing | expectation maximization delaunay triangulation graph | minimum spanning machine | reduction multidimensional analyses | kidney transplant framework | changes | interstitial inflammation | tubular cast | micrograph | renal microscopic illuminant normalization information preservation | content |CRP images platform | Computational Medicine Laboratory | FORTH-ICS | secure cloud upgradable file support | multiformat scanner vendors | collaboration capabilities | scheduling tools | microscope viewer | Biological cells | Pathology | Genetic algorithms | Sociology | Statistics | Cancer | Tumors | Whole-Slide Imaging | Adaptive Sampling | Convolutional Neural Network | Digital pathology | Genetic Algorithm | Niobium | Neoplasms | Image color analysis | Image texture analysis | Sympathetic nervous system | USA Councils | Tumors | Microscopy | tumours | biomedical optical imaging | cellular biophysics | image classification | image segmentation | medical image processing | neurophysiology | paediatrics | probability | Multiplexing | Image analysis | Biomedical imaging | Image color analysis | radiology | diseases | medical image processing | digital pathology imaging | medical imaging | disease dignosis | diagnostic biomarkers | image based technology | digital workflow | Medical Image Analysis | Tissue Diagnostics | Retina | Diabetes | Costs | Medical diagnostic imaging | Ear | Art | learning (artificial intelligence) | eye | object detection | image colour analysis | image classification | medical professionals | lesion detection | color retinal images | diabetic-related eye diseases | blindness | regular screening | state-of-the-art image processing techniques | automatic detection | abnormalities | retinal images | abnormal signs | exudates | Glands | Prostate cancer | Skin cancer | Biological tissues | Merging | image segmentation | information fusion mechanism | color based segmentation | texture based segmentation | molecular pathology images | hierarchical self-organizing maps | tissues | k-means clustering | Molecular pathology | Hematoxylin and Eosin staining (H&E) | Hierarchical selforganizing maps (HSOM) | Color and texture segmentation | Feature extraction | Region merging | Tissue microarray (TMA) | Robustness | Magnetic resonance imaging | Brain | Image motion analysis | Aging | Medical diagnostic imaging | biomedical MRI | image texture | texture descriptor | local binary patterns | aging population | risk factors | neurodegenerative diseases | automated brain image analysis | tissue contrast | Algorithms | Artifacts | Databases Factual | Humans | Image Processing Computer-Assisted | Models Statistical | Phantoms Imaging | Reproducibility of Results | Signal Processing Computer-Assisted | false positive detection | computer-aided prognosis | mitosis cell detection | karyorrhexis cell detection | digitized histological images | histopathological examination | patient prognosis | pediatric tumor | Colon | Data mining | Statistical analysis | Biomedical imaging | matrix algebra | colour graphics | discriminant analysis | colon cancer images | colour texture analysis | cooccurrence matrices | cytological images | discriminating ability | tissue samples | polyps | binning | Blood vessels | Databases | morphological technique | red lesions | automated detection | digital colour fundus photographs | diabetic retinopathy | vision loss | rule-based classifier | Automatic Data Processing | Automation | Colorimetry | Computer Graphics | Diagnostic Imaging | Fundus Oculi | Image Processing | Computer-Assisted | Microscopy | Principal component analysis | Sun | Image sampling | image sampling | principal component analysis | tissue staining | color-based approach | automated segmentation | tumor tissue classification | microscopic images | color normalization | automatic sampling | PCA | fully-automated method | oral cancer images | Color | Mouth Neoplasms | Lungs | Respiratory system | Eigenvalues and eigenfunctions | Computed tomography | computerised tomography | Hessian matrices | lung | accuracy | automatic segmentation | lung lobe | CT image | fissure | lobewise analysis | pulmonary parenchyma | lobe segmentation | water shed transformation | pulmonary fissures | watershed segmentation | cost image | Hessian matrix | segmentation | lung lobes | pulmonary fissures | Tongue | Inspection | Image edge detection | Shape | Diseases | interpolation | edge detection | biological organs | graphical user interfaces | image colour analysis | oriental medicine | digital tongue inspection system | human body physiological information | color interpolation | edge detection algorithm | tongue area separation | tongue color detection algorithm | Training | set theory | threshold level-set | digital pathology images | image cancer nuclei segmentation | clinical decision support systems | brain tumor diagnosis | omics | color information | HSV | hue saturation value | level-set segmentation | VLS | sparsity representation | tissue intensity distributions | clinical decision support | sparsity technique | Deconvolution | Compounds | Electronic countermeasures | Estimation | Optical microscopy | decorrelation | estimation theory | image sensors | matrix algebra | brightfield microscopy | generalized framework | digital pathology applications | microscopic examination | stained tissue sections | biopsies | pathology disease organ diagnosis | system pathology | intra-observer variation | Color deconvolution | digital stain separation | histopathology compound staining | stain density estimation | spectral overlap in staining | Maxwellian chromaticity | Morphology | Computer aided diagnosis | reviews | electron microscopy | fluorescence | nucleus-cell detection | robust nucleus-cell detection | comprehensive review | microscopy image analysis | tissue structure | cell morphology | computer-aided diagnosis system | Cell | detection | histopathology | microscopy images | nucleus | Proteins | Biomarkers | Immune system | Pathology | quantification | Biomarker | histology | image normalization | immunohistochemistry | Algorithm design and analysis | Software | Protocols | Pattern recognition | glomeruli detection | whole slide imaging | machine learning | Standards | optical microscopy | fluorescence | gold standard bright field H&E | DRAQ5 | dual-stain fluorescent analogue | fixed frozen tissue | Eosin Y | human tissue | fluorescent microscope | pseudocoloring | morphological features | pathologist | fluorescence microscopy | cancer | Kernel | Matrix decomposition | Laplace equations | feature selection | Feature Selection Challenge | Feature Importance in Nonlinear Embeddings | quantitative histomorphometry | disease modeling | digital pathology image | image feature | high dimensional feature space | nonlinear dimensionality reduction | dimensionality reduction | Registers | Immune system | biochemistry | image registration | information retrieval systems | high-throughput analysis | tissue microarray technology | standardized screening | protein expression | immunohistochemistry | tissue-based biomarker analysis | image sharing | image archiving | Bit rate | Image coding | Encoding | Computational modeling | Video coding | Adaptation models | image reconstruction | random codes | rate distortion theory | rate control | lossless region of interest | lossless reconstruction | random access | rate distortion curve slope | R-λ model | target bit rate | RoI mask | HEVC intracoding | medical images | HEVC | lossless RoI coding | Classification algorithms | Multispectral imaging | biological specimen preparation | medical diagnostic computing | hospital | spongiosis identification | unstained histopathological specimen | histopathological specimen preparation | histopathological specimen staining | cell structure contrast | tissue structure contrast | spectral imaging | Correlation | Image resolution | image matching | intermarker whole slide registration | state-of-the-art registration methods | multiresolution approach | gradient magnitude images | tissue boundary regions | clinical diagnosis | primary stained image | tumor region | multi-resolution search | registration | line fitting | robust estimation | Vectors | prostate carcinoma classification | tissue representation | Gleason grades | high-grade cancer | noncancer tiles | tissue classes | feature vector representation | image tiles | classifier models | tissue segmentation algorithms | Support vector machines | Kernel | regression analysis | Bayes methods | texture features | multiple instance learning | Barrett's cancer diagnosis | hematoxylin & eosin stained histopathological biopsy images | tissue cores | rectangular patches | feature vector | cell-level features | histopathological tissue imaging | Cancer diagnosis | multiple instance learning | Educational institutions | digital photography | ideal WB scenario | fast auto white balance scheme | white balance correction | low-level statistics based technique | illuminant estimation | linear transformation method | image correction | WB performance | real life conditions | computer vision | Color constancy | auto white balance | digital pathology | Pattern recognition | Approximation methods | Biological system modeling | patient diagnosis | colon tissue images | hybrid classification model | structural pattern recognition technique | statistical pattern recognition technique | cell distribution | biological structures | correct localization | structure characterization | structural pattern recognition | Automated cancer diagnosis | graph embedding | histopathological image analysis | inexact graph matching | Aneurysm | Optical imaging | Tomography | Coherence | Fiber optics | stereo image processing | biological techniques | optical tomography | specimen preparation | three dimensional OCT image | 3D optical coherence tomography | cross-sectional view | biological tissue | tissue sample preparation | intracranial aneurysms | breast cancer | Bioinformatics | Virtual environments | information technology | interobserver variability | data-intensive frontier | tissue | anatomic pathologists | information technology | image-based diagnostic applications | research applications | healthcare practices | virtual microscopy | biomedical informatics | image analysis | Histograms | Brightness | Helium | Information processing | image enhancement | post-acquisition adjustments | image visibility | image brightness | image contrast | brightness preserving contrast enhancement technique | Image enhancement | Biomedical image processing | Lenses | Lighting | Image sequences | solid modelling | data acquisition | data visualisation | rendering (computer graphics) | real time image generation | slide digitization | 3D visualization technique | pathological application | field image sequence | high resolution extended depth | volume visualization technique | ray casting | digital pathology work flow | Rendering | Biomedical microscopy | Biomedical image processing | wavelet transforms | image texture | automated pathology detection | leave-one-out cross-validation method | microaneurysms | drusen | SVM | CWT decomposition | image columns | image rows | one-dimensional signals | Entropy | Discrete wavelet transforms | Support vector machines | frequency-domain analysis | radial basis function networks | sensitivity analysis | statistical features selection | intrinsic mode functions | pathologies detection | retina digital image analysis | empirical mode decomposition | frequency domain | statistical feature extraction | high frequency components | Fractals | Hemorrhaging | Digital images | vision defects | probability | classical 2D-EMD | retina digital images | student-adjusted empirical mode decomposition | power law statistics | modified two-dimensional empirical mode decomposition method | biomedical images | Student's probability density function | classification | EMD | Student distribution | retina digital image | blot hemorrhage | Fourier power spectrum | fractal | SVM | Breast cancer | Mammography | Biopsy | Needles | automated real-time breast cancer diagnosis tool | digital imaging | human breast cancer | staining techniques | histopathological slides | color polarization | Bi-color monochrome image and Inverse color | FNAC | MRI | Core biopsy | Surgical biopsy | Histopathological Slide | 24-bit color bitmap image | Grey scale image | Digital images | Pediatrics | Density measurement | Blood | Laboratories | Error analysis | Proposals | Absorption | Sensitivity | Cameras | specimen preparation | microscopes | stain separation | stain normalization | blind method | stain image | visual comparability | automatic analysis | cellular structures | visible contrast | imaging device | glass slide | sample preparation | microscope | thin tissue samples | digital bright field histopathology | Beer-Lambert law | transmission light microscopy | Fats | Dictionaries | Liver | Anatomical structure | Algorithm design and analysis | physiological models | compressed sensing | image filtering | size distributions | spatial analysis | hepatic steatosis detection | histopathology images | sparse linear models | nonalcoholic fatty liver disease | obesity | metabolic syndrome | image-based analysis | biopsy images | morphological filtering | dictionary-based algorithm | Hepatic steatosis | liver fat detection | biopsy image analysis | shape classification | Calibration | Standardization | software tools | medical computing | color standardization | immunohistochemically stained tissue section images | color calibration microscope slide | digitalization tools | microscope color calibration slide | microscopic image analysis | color correction | whole slide image | Lesions | Prognostics and health management | History | time series | patient diagnosis | tissue-based diagnosis | diagnosis assistants | time series analysis | disease classification | object features measurement | syntactic structure analysis | stereology | structure coordinates | object coordinates | texture coordinates | ROI | image content information | diagnosis algorithms | Training | Decoding | image representation | learning (artificial intelligence) | average area under Precision-Recall curve | stacked sparse autoencoder | nuclei detection | automated nuclear detection | computer assisted pathology related image analysis algorithms | automated grading | deep learning | Automated nuclei detection | breast cancer histopathology | feature representation learning | Distortion | Distortion measurement | Indexes | biomedical equipment | modeling human-perceived quality | digitized histopathology color standardization | digitized slides | computer-aided diagnosis systems | color standardization algorithms | computer-aided diagnosis (CAD) | Color standardization quality | histopathology image analysis | Hospitals | Education | telemedicine | biomedical ultrasonics | medical diagnostic computing | surgery | anatomic pathology | medical diagnosis virtual slides | medical diagnosis instant sharing | telepathology practices | King Fahd hospital | information and communication technology | teleradiology | tele-ultrasound | tele-surgery | ICTs | Saudi Arabia | Technologies of Pathology | Telepathology | Virtual Pathology | University of Dammam | Measurement | image denoising | cancerous histopathological images | two-tier tissue decomposition | histopathological image representation | histopathological image classiiication | effective image representations | tissue decomposition model | blob | histopathological image representation | Digital systems | Classification | lung | nuclei classification | digital histopathology | review | medical protocols | gold standard | architecture distribution | computerized method | human intervention | nuclei separation | microscopic analysis | nuclei segmentation | mammography | high-throughput histopathology slide digitization | breast cancer patient prognosis | computer-aided diagnosis | image processing applications | image processing techniques | tissue preparation | quality improvement | object segmentation | object detection | Labeling | patient care | postprostatectomy patient care | prostate histopathology | learning tissue component histograms | cancer classification | radical prostatectomy | organ-confined prostate cancer | prostatectomy specimen | adjuvant treatment | quantitative pathology superpixels | Automated prostate cancer detection | cancer grading | digital pathology image analysis | Erbium | Image edge detection | proteins | BCa histopathology | multifield-of-view framework | Bloom-Richardson grading | intraobserver variability | estrogen receptor-positive | image features | tumor morphology | tumor texture | hematoxylin | eosin | nuclear texture | Breast cancer (BCa) | modified Bloom–Richardson (mBR) grade | multi-field-of-view (multi-FOV) | nuclear architecture | Graphics processing unit | Parallel processing | Instruction sets | Interpolation | coprocessors | GPU | two point correlation function | TPCF calculation acceleration | pathology image segmentation | tissue region segmentation | high resolution microscopy | digitized pathology sections | tissue image textural appearance | slide scanning devices | Graphical Processing Unit | Two Point Correlation Function | Lead | Board of Directors | sensitivity analysis | gynaecology | receiver operating characteristic curve | boosted classifier | integrating multiple fields | multiscale frameworks | hierarchical classifiers | quantitative feature extraction | computerized breast cancer grading | whole-slide histopathology imaging | cancer nuclei | Breast cancer grading | AdaBoost | multi-FOV | multi-scale | Pixel | cascaded multiclass pairwise classifier | CascaMPa | normal confounder class | cancerous confounder class | cancer confounder class | prostate histology | Gleason grading | Supervised Classification | Gleason Grading | Transforms | Pixel | Biopsy | gleason grade classification | diagnosing prostate cancer | computer aided diagnosis | pathologist | gland inner area | feature extraction | Physics computing | Breast biopsy | Coronary arteriosclerosis | CAD | mass spectroscopy | proteomics | sensor fusion | multimodal image analysis | CAP | computerized image analysis | multimodal data fusion | disease outcome | patient survival | laboratory for computational imaging and bioinformatics | multi-modal | computer-aided prognosis (CAP) | personalized medicine | data fusion | Cancer detection | Metastasis | Markov random fields | Tree graphs | Support vector machine classification | Visualization | computer aided analysis | Markov processes | mesh generation | 3D embedding space | computerized image-based detection | lymphocytic infiltration grading | HER2+ breast cancer histopathology | lymphocytic infiltration | nodal metastasis | distant recurrence | Markov random field algorithms | lymphocytes | texture | Breast cancer (BC) | lymphocytic infiltration (LI) | prognosis | segmentation | Coronary arteriosclerosis | Machine learning algorithms | Application software | Computer applications | Machine learning | computer-assisted diagnosis | digitized tissue histopathology | imaging modalities | immunofluorescence | cytopathology | microscopy analysis | computer-assisted interpretation | Image retrieval | Content based retrieval | Information retrieval | Image databases | Spatial databases | Indexing | medical information systems | content-based retrieval | query execution | content based sub-image retrieval system | high-resolution digital pathology images | salient interest points | medical database | scale-invariant feature extraction | robust searching mechanism | image indexing | sCBIR | scale-invariant features | IHC | Tuning | optimal set search | SVM classifier | numerical features | digital pathology slides | image-based evaluation | prevention screening programs | histopathological image classification | Training data | features extraction | deep convolutional activation features | brain tumor histopathology | MICCAI 2014 Brain Tumor Digital Pathology Challenge | image dimensions | CNN activations | ImageNet | feature learning | Biology | image representation | biological stain-sparse regularized stain separation | structure-preserved color normalization | histological images | automated image processing | structure-preserved color representation | non-negative matrix factorization | Histopathology image | stain separation | Semantics | diagnostic radiography | digital pathology image database | pathology image retrieval method | pathological features | content-based image retrieval | breast cancer aided diagnosis | pathology image content | probabilistic latent semantic analysis | Real-time systems | Rendering (computer graphics) | Tiles | Hardware | Manuals | whole slide (WS) | Digital slide (DS) | mosaicing | virtual microscopy (VM) | Clustering algorithms | Spatial resolution | lab-on-a-chip | frequency 2.8 GHz | high-throughput biomarker segmentation | ovarian cancer tissue microarrays | hierarchical normalized cuts | vascular staining | frequency weighted mean shift | hierarchical pyramid | color resolutions | Biomarker discovery | hierarchical normalized cuts (HNCuts) | high-throughput | mean shift | multivariate histology | normalized cuts | Bayesian methods | Classification tree analysis | belief networks | computerised instrumentation | decision trees | Gabor filters | boosted Bayesian multiresolution classifier | prostate cancer detection | digitized needle biopsies | prostate cancer diagnosis | computer-aided algorithms | digitized glass slides | Computer-aided detection (CAD) | prostate cancer (CaP) | quantification | Data structures | data compression | serial electron micrographs | interactive histology | large-scale biomedical image stacks | microscopy techniques | digital imaging technology | display-aware processing | GPU-accelerated texture compression | nanoscale-resolution | texture compression | Gigapixel viewer | GPU | Transportation | Biomedical computing | graph theory | liver | cell mechanics | graph-based method | characteristic phenotypes | graph partition | hepatoblastoma nuclei | location proteomics | genetic screens | Phenotype detection | Optimal transportation distance | Graph partition | Transform coding | Image storage | Hard disks | gamma distribution | receiver operating characteristic curves | JPEG2000 compression | computer-aided detection system | digitized histopathology | hard disk space | image compression | carcinoma | region-growing algorithm | Haar transforms | image retrieval | CIE L-channel histogram | color feature extraction technique | content-based medical image retrieval system | digital oral pathology image database | Haar wavelet coefficient | image query | Single channel color histogram | Haar wavelet co-efficient | oral pathology images | Mixture models | Chemicals | Colored noise | uncertainty handling | pattern clustering | saturation-weighted computation | circular mixture modeling | color distribution | blind stain separation | pathology images | stain decomposition | naturally nonnegative matrix factorization problem | circular color analysis module | von Mises distribution | Circular mixture model | color analysis | pathology image | stain decomposition | Visualization | appearance-based necrosis detection | histopathological whole slide images | discriminative thresholding | disease diagnosis | disease prognosis | living tissue | tumor necrosis | gastric cancer | malignancy level | Gold | expectation-maximisation algorithm | genetics | Oncotype DX recurrence score | estrogen receptor-positive breast cancer | gene-expression based assay | tissue specimen | disease detection | Cancer grade | Oncotype DX | Computers | patient care | kidney | Bowman capsule | automatic glomerulus extraction | whole slide images | diagnostic assessments | prognostic assessments | renal transplants | renal biopsy interpretation | gene array | metabolomics | clinical interpretation | Informatics | Breast | Latent Dirichlet Allocation | Content Based Image Retrieval | Whole Slide Image | Local Statistical Feature of Nuclei | Gray-scale | local color texture patterns | color texture representation | circular-processing | hue-LBP | histo-pathology image analysis | hue component | cylindrical color space | color texture descriptor | LBP paradigm | LBP variants | hue channel | angular variable | Texture description | circular processing | Imaging | achromatic colors | complete color normalization approach | color cues | saturation-weighted statistics | color variation | image samples | inconsistent biopsy staining | nonstandard imaging condition | spectral estimation | illuminant normalization | Collaboration | Surgery | Processor scheduling | virtual machines | cloud computing | virtual instrumentation | digital slides | collaborative reviewing platform | central reviewing platform | digital microscopy images | virtual slide telepathology | surgical pathology cases | quality assurance program | Central Review for Pathology

 

Track1:  Strategy and Technology

To formulate medical decisions, healthcare experts require that all essential information is both are accurate and easily accessible. Collaborative Digital Anatomic Pathology discus about the use of information technology that supports the formation and distribution or exchange of information, including metadata and images, throughout the complex workflow monitored in an Anatomic Pathology department from specimen reception to report transmission and exploitation. Collaborative Digital Anatomic Pathology is supported by standardization efforts towards interoperability and knowledge representation for shareable and computable clinical information. Digital Pathology expands the limits of microscopy, enabling students, educators, researchers, and clinicians to contribute tissue samples. Images transmitted or shared over the Internet or through specific analysis software open the path to a modern and exciting microscopy toolDigital Pathology excludes some of the issues associated with sharing slides such as the degeneration of samples and inability to share samples of live cells.  Benefits include: Diagnostics – a hospital can transmit images anywhere in the world, probably decreasing the time it takes to accordingly diagnose and treat a pathogen. Education – colleges and universities can approach an enormous database of samples, via on-line or through a web database, saving fund on histological slides; students and professors will also have the capability to study images of live and dead cells Finances – savings can be establish from decreasing or eliminating purchases of glass slides, cover-slips, adhesives and dyes as well as the cost to conserve and send pathology exhibit to colleagues or institutions

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Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Digital Pathology association, Indiana; American Society for Investigative Pathology, USA; American association of pathologists assistants , USA; American Speech Language Hearing Association, USA; Association of Directors of Anatomic and Surgical Pathology, USA; Association of Indian Pathologists in North America, USA; Association for Molecular Pathology, USA

Track 2: Pathology Informatics

Pathology Informatics concentrates on the management and analysis of clinical and research pathology data using modern computing, communications and digital imaging methods. The Division of Pathology Informatics has grown to a nationally acknowledged informatics organization at the University of Pittsburgh Medical Center (UPMC) prepares pathologists grows to be leaders in the development and application of informatics in educational, industry and/or community practice settings. Sharing digital pathology images for firm wide use into a picture archiving and communication system (PACS) is not yet extensively adopted. We share our solution and 3-year experience of broadcasting such images to an Enterprise Image Server (EIS). A computerized picture archiving and communications system (PACS) has been successfully used in the stream of radiology for storage, rapid retrieval, and widespread access to digital imagesDigital images can be captured using multiple modalities and many PACS users at different sites can have at the same time, remote access to images. Both computerized images and reports can be transmitted digitally via PACS. Whole slide imaging (WSI), also indicated to as "virtual" or wide-field microscopy, associate with digitization of glass slides, which resembles light microscopy (i.e. "digital slides"). WSI produces high-resolution digital images and associates with relatively high speed digitization of glass slides of different samples (e.g. tissue sections, smears), scanning them at various magnifications and focal planes (xy and z axes). Compared to immovable (still) and live (usually robotic) digital imagesWSI is commonly more beneficial for educational purposes.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Conferences

Pathology Informatics Summit 2016, Pittsburgh, PA, May 23-26,2016; 13th European congress on Digital Pathology, Berlin, May 25-28,2016; Molecular med TRI-CON 2016, Mascone North Convention centre, San Francisco, CA, March 6-11,2016; Digital Pathology Congress, London, UK, December 3-4,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Clinical Pathology Meeting, October 28-30, 2015, Long Beach, California, United States; Diagnostic Pathology, Greensboro, Georgia, United States; Pathology Informatics 2016, May 23-26, 2016, Pittsburgh, USA; Dermatopathology: Highlighting Oral Pathology, Soft Tissue Tumors and Lymphoma, October 19-22, 2015. International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

The United States and Canadian Academy of Pathology, USA; The American Society for Clinical Pathology (ASCP), USA; European Society of Pathology, Belgium; Paediatric Pathology Society, UK; Australian Medical Association, Australia; College of American Pathologists, USA

Track 3: Telepathology

Telepathology can be described as the electronic transmission of digital images of pathology for education, examination, diagnosis, or conference. Since its first proof-of-concept demonstration in 1968, this technology has resulted in close to 600 magazines and has been used with ever-growing rate throughout the world. From a medical point of view, telepathology has developed from point-to-point transmission of live or near-live video images, to the capture of digital images of preferred  microscopic fields for storage and future transmission, to robotic control of the microscope with quick point-to-point transmission, to improvement of software that simplifies Web-based consultations and interactions, to the generation of virtual slides that characterize the entire slide for stress-free Web site access or for storage. The basic machineries of a telepathology system are a microscope with an attached digital camera connected to a computer. Basic systems deliver an image that can be stored and sent via e-mail or the Internet to a professional for consultation. The cost and difficulty of a basic simple system increases with the accumulation of a robotic microscope and point-to-point transmission but permits the observer to control slide movement, concentration, and use objective selection. Virtual-slide technology, the most expensive of the possibilities for telepathology, forms a particular single image of a glass slide. These tools combine an objective (310 to340) with computerized stage and digital camera with the computer power to promptly obtain a sequence of images that are automatically stitched together in software and compressed to form a single image file of the slide. All of these systems are presently used for all phases of telepathology, but each differs in its applicability in providing pathology financial assistance for countries in the developing world or in regions with limited resources.

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Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Royal College of Pathologists of Australasia, Australia; International Board for Medical Research and Studies, Switzerland; European Society of Cardiology, France; German Medical Association, Germany; Irish Medical Organisation, Ireland; British Medical Association, UK

Track 4: Digital Image Analysis

digital image composed of pixels performs an analog image transformed to numerical form using ones and zeros (binary) so that it can be stored and used in a computer system. The digital imaging process consists of four key steps: image acquisition (capture), storage and management (saving), manipulation and annotation (editing), and viewing, display or transmission (sharing) of images. Before digital images become extensively used for periodic clinical work, standards are needed and the entire imaging process approved. For example, when six practicing pathologists were asked to all photographs the same section on a glass slide with similar microscopes that had the same associated digital cameras, they all produce dissimilar images.  Moreover, global manipulation (e.g. contrast enhancement) of Papanicolaou test digital images has been shown to significantly change their interpretation. We also need to pay more consideration to the digital pathology diagnosing station (cockpit) to that they integrate computers with appropriate performance and graphics cards, screens with exceptional image resolution and color quality, as well as connectivity to the Internet, laboratory information system (LIS) and electronic medical record (EMR). The use of computer monitors for digital pathology should, possibly, employ a Macbeth color manager (array of color squares) or correspondent to guarantee precise color balance once a digital image has been developed, computer applications can be leveraged to evaluate the information they hold. More than a few algorithms have been developed (e.g. pattern recognition algorithms) that potential to increase accuracy, reliability, specificity, and productivity. For example, computer assisted image analysis (CAIA) has been used to score (quantify) certain immunohistochemical stains (e.g. ER, PR and HER-2/neu breast biomarkers). In this manner, CAIA gives all pathologists the similar yardstick for scoring immunohistochemistry results in Breast cancer cases. This quantitative method to tissue analysis using WSI has been stated to as "slide-based histocytometry". Multispectral image analysis is additional emerging device that exploits both spatial and spectral image statistics to classify images. This computerized technology has already been shown to be important in certain clinical settings (e.g. cytopathology) to help distinguish and classify morphologically similar lesions.

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Related Conferences

Pathology Informatics Summit 2016, Pittsburgh, PA, May 23-26,2016; 13th European congress on Digital Pathology, Berlin, May 25-28,2016; Molecular med TRI-CON 2016, Mascone North Convention centre, San Francisco, CA, March 6-11,2016; Digital Pathology Congress, London, UK, December 3-4,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Clinical Pathology Meeting, October 28-30, 2015, Long Beach, California, United States; Diagnostic Pathology, Greensboro, Georgia, United States; Pathology Informatics 2016, May 23-26, 2016, Pittsburgh, USA; Dermatopathology: Highlighting Oral Pathology, Soft Tissue Tumors and Lymphoma, October 19-22, 2015. International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Royal College of Pathologists, UK; Royal Society of Medicine, UK; Canadian Medical Association, Canada; American College of Cardiology, USA; American College of Gastroenterology, USA; Brazilian Medical Association, Brazil; American College of Radiology, USA

Track 5: Digital Pathology Applications and Research Case Studies

Prior to slide digitization, skilled pathologists examined clinical trial data to determine evidence of disease and diagnose disease by reviewing glass specimen slides utilizing microscopes. To acquire interpretations, more than a few sets of slides were arranged from each patient’s tissue block, each slide comprising a different level of tissue, and shipped to reviewers. As a result of the alteration in tissue levels, variability in inter-reader interpretations of specimens was improved. Digital pathology decreases such variability by providing reviewers with matching digital images of patients’ tissue.  The field of digital pathology has exploded and is now regarded as one of the most promising avenues of diagnostic medicine in order to attain even better, faster and inexpensive diagnosis, prognosis and prediction of cancer and other significant diseases. Digital pathology and the implementation of image analysis have grown rapidly in the last few years. This is mostly due to the implementation of whole slide scanning, improvements in software and computer processing capacity and the increasing position of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application regions for digital pathology and image analysis, with a particular emphasis on research and biomarker discovery. Digital pathology and image analysis have significant roles across the drug/companion diagnostic improvement pipeline including biobankingmolecular pathology, tissue microarray analysismolecular profiling of tissue and these significant developments are reviewed. Underpinning all of these significant developments is the necessity for high quality tissue samples and the effect of pre-analytical variables on tissue research is discussed. This requirement is merged with practical advice on setting up and running a digital pathology laboratory. 

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Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

American College of Surgeons, USA; American Medical Association, USA; Association of Clinical Pathologists, UK; Wisconsin Society of Pathologists, USA; American Society for Gastrointestinal Endoscopy, USA; American Society for Clinical Pathology, USA; ; British Medical Association, UK

Track 6: Digital pathology versus Traditional Microscopy

Digital pathology can be considered as an adjunct to traditional microscopy. In traditional microscopy, we require a microscope to view the glass slide. We can only view one slide, one field of view, and one exaggeration at a time. If we want to do any sort of analysis with a microscope, we have to remember the information from each field of view. For example, if we want to associate two slides, we have to look at one slide, store the information in our brain bank, look at the slide, and try to remember the one we looked at prior to make a comparison. In digital pathology, we have the benefit of doing things different way. We can view some digital slides on a computer monitor. We can combine them side-by-side if we want to calculate the entire cells or calculate protein expression; these can be done easily by computer software that can be seen on an image file and it is called a digital slide. In case of traditional microscopy, if we want to transfer the data with someone in a distant place, the slide has to be mailed. But with digital pathology, we can transmit the data with anyone in the world directly. It is also comparatively very easy to integrate a digital pathology system into a laboratory data system. Digital pathology can support the monitoring and consolidation of different sources of information required for pathological purposes to do work more proficiently and innovatively.

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Related Conferences

Pathology Informatics Summit 2016, Pittsburgh, PA, May 23-26,2016; 13th European congress on Digital Pathology, Berlin, May 25-28,2016; Molecular med TRI-CON 2016, Mascone North Convention centre, San Francisco, CA, March 6-11,2016; Digital Pathology Congress, London, UK, December 3-4,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Clinical Pathology Meeting, October 28-30, 2015, Long Beach, California, United States; Diagnostic Pathology, Greensboro, Georgia, United States; Pathology Informatics 2016, May 23-26, 2016, Pittsburgh, USA; Dermatopathology: Highlighting Oral Pathology, Soft Tissue Tumors and Lymphoma, October 19-22, 2015. International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

American Society of Clinical Oncology, USA; American Society of Cytopathology, USA; American Gastroenterological Association, USA; American Association for Cancer Research, USA; College of American Pathologists, USA; Catholic Medical Association, USA; Digital Pathology association,Indiana

Track 7: Digital Pathology Environment

Digital pathology is extensively more than whole slide imaging (WSI); it has data security and creates an environment for handling data that consists of multi-gigabyte images that are merged. It also comprises integration of the digital pathology data management system with autostainers, converslippers, and the laboratory management system. It comprises the following elements. Conventional glass slides are converted to digital slides using a scanning device. Digital slide scanners are considered as successors of early telepathology systems that facilitated the transfer of static and dynamic images via computer networks for remote consultation and second opinion. Digital slides are accessible for viewing through computer system and viewing software either locally or remotely via the Internet. Digital slides viewers can show an overview image, along with high-power view, enabling better orientation. Showing two or more slides side-by-side is a characteristics of many slide viewers, which can be useful for analyse the same tissue contaminate with different stainings. Digital slides are sustained in an information management system that permits archival and intelligent retrieval. Educational and examination slides end up in the constant storage where they are kept without an invalidating time frame. Object-based storage offers overall redundancy of stored objects without the necessity to take incremental backups. Digital slides are maintained in a data management system that allows for archival and intelligent retrieval. Image examination tools are used to derive objective quantification procedures from digital slides. Pattern recognition and visual search tools are used to categorize specimen imagery and discover medically significant regions of digital slidesDigital pathology workflow is integrated into the institution's overall operational background. Digital pathology also permits internet information transmitting for education, diagnostics, publication and research.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

California Medical Association, USA; Infectious Diseases Society of America, USA; International Academy of Medical Acupuncture, USA; Digital Pathology association, Indiana;  Federation of Clinical Immunology Societies, USA; Denver Medical Society, USA; Congenital Heart Surgeons' Society, USA

Track 8: Digital Pathology Workflow

Currently, the standard Digital pathology workflow begins with the procedure performed on the patient, most commonly a biopsy or a resection. The material is then sent to a pathology division associated by an order (ideally in a digital way), along with appropriate clinical information. This information regularly comes out of the local electronic health records, simultaneously with localization and clinical information of the material. When the material is received in the pathology department, it is registered in the local laboratory information system before undergoing the necessary procedure in order to be managed to glass slides. Then, the glass slides are observed under a light microscope in order to create the pathology report. Switching the current workflow to a fully digital one would require glass slides to be scanned prior to sending them to pathologists, which can add cumulatively to the overall diagnosis time. This can be concentrated by using speed scanners and integrating the scanning with the cover slipping and staining method. Thus, digital pathology workflow is incorporated into the institution overall operational environment.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Conferences

Pathology Informatics Summit 2016, Pittsburgh, PA, May 23-26,2016; 13th European congress on Digital Pathology, Berlin, May 25-28,2016; Molecular med TRI-CON 2016, Mascone North Convention centre, San Francisco, CA, March 6-11,2016; Digital Pathology Congress, London, UK, December 3-4,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Clinical Pathology Meeting, October 28-30, 2015, Long Beach, California, United States; Diagnostic Pathology, Greensboro, Georgia, United States; Pathology Informatics 2016, May 23-26, 2016, Pittsburgh, USA; Dermatopathology: Highlighting Oral Pathology, Soft Tissue Tumors and Lymphoma, October 19-22, 2015. International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Boston Society for Medical Improvement, USA; American Board of Family Medicine, USA; American Board of Internal Medicine, USA; American Board of Medical Genetics, USA; American Heart Association, USA; American Society for Clinical Pathology, USA; American College of Cardiology, USA

Track 9: Digital Pathology Utility in The Future

Many articles are being published regarding its use in routine pathologic diagnosis. Validation of a WSI system for primary diagnosis in surgical pathology has been studied. Even the concordance between digital pathology and light microscopy in general surgical pathology has been studied in a pilot study of 100 cases, and it was found that digital pathology is a safe and viable method of making a primary histological diagnosisDigital pathology is being increasingly tried in the interpretation of immunohistochemistry (IHC) markers. Interpretation of human epidermal growth factor receptor 2 (HER2/neu) immunohistochemical expressions with unaided as well as computer-aided digital microscopy as well has been documented. Digital pathology has penetrated classrooms, especially pathology teachings. It can effectively replace the traditional methods of learning pathology by providing mobility and convenience to medical students.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Association of Directors of Anatomic and Surgical Pathology, USA; Association for Molecular Pathology, USA; American Board of Internal Medicine, USA; Congenital Heart Surgeons' Society, USA; Denver Medical Society, USA

Track 10: Current Status and Future Perspectives

During the last decade pathology has promoted from the quick progress of image digitizing technology. The development in this technology had led to the formation of slide scanners which are incapable to produce whole slide images (WSI) which can be discovered by image viewers in a way comparable to the conventional microscope. The file size of the WSI varies from a few megabytes to several gigabytes, leading to contests in the area of image storage and management when they will be used regularly in daily clinical practiceDigital slides are used in pathology for education, diagnostic purpose (clinicopathological meetings, consultations, revisions, slide panels and, increasingly, for direct clinical diagnostics) and archiving. As an alternative to conservative slides, WSI are usually well accepted, especially in education, where they are obtainable to a large number of students with the full possibilities of annotations without the problem of difference between serial sections. Image processing techniques can also be functional to WSI, providing pathologists with tools assisting in the diagnosis-making procedure.

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Related Conferences

Pathology Informatics Summit 2016, Pittsburgh, PA, May 23-26,2016; 13th European congress on Digital Pathology, Berlin, May 25-28,2016; Molecular med TRI-CON 2016, Mascone North Convention centre, San Francisco, CA, March 6-11,2016; Digital Pathology Congress, London, UK, December 3-4,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Clinical Pathology Meeting, October 28-30, 2015, Long Beach, California, United States; Diagnostic Pathology, Greensboro, Georgia, United States; Pathology Informatics 2016, May 23-26, 2016, Pittsburgh, USA; Dermatopathology: Highlighting Oral Pathology, Soft Tissue Tumors and Lymphoma, October 19-22, 2015. International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

Association of Directors of Anatomic and Surgical Pathology, USA; Association of Indian Pathologists in North America, USA; Paediatric Pathology Society, UK; The United States and Canadian Academy of Pathology, USA

Track 11: Dermatopathology and Diagnostics

Dermatopathology is a subspecialty of both pathology and dermatology in which acceptable clinical info is needed to a valid tissue diagnosisDermatopathology is a subspecialty of anatomic pathology that emphases on the skin and the respite of the integumentary system as an organ. It is unique, in that there are two pathways a physician can take to obtain the specialization. All universal pathologists and general dermatologists train in the pathology of the skin, so the word dermatopathologist signifies either of these who has reached a certainly level recognition and experience. Dermatologists are able to identify most skin diseases based on their arrivals, anatomic distributions, and behaviour. Sometimes, however, those criteria do not lead to a conclusive diagnosis, and a skin biopsy is taken to be observed under the microscope using usual histological tests. In certain cases, additional specialized testing wants to be executed on biopsies, comprising immunofluorescenceimmunohistochemistryelectronmicroscopyflow cytometry, and molecular-pathologic analysis

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Conferences

Digital Pathology Congress, London, UK, December 3-4,2015; 12th European congress on Digital Pathology, Paris, France, June 18-21,2014; Digital Pathology Congress,  United States, February 11-16,2017; Pathology Visions conference 2015,The Westin Boston Waterfront Boston, MA, October 11-13,2015; Digital Path Europe 2016,Hilton Tower, Bridge, London, May 18-19,2016; Global Pathologists Annual Meeting September 29-October 01, 2016, London, UK; 3rd Global Experts Meeting on Medical Case Reports May 09-10, 2016, New Orleans, Louisiana, USA; 6th European Pathology Congress, June 16-17, 2016, Alicante, Spain; 4th International Conference and Exhibition on Pathology, July 13-15, 2015 New Orleans, USA; International Conference on Speech-Language Pathology, November 14-15, 2016 Atlanta, USA;

Related Associations and Societies:

British Medical Association, UK; International Board for Medical Research and Studies, Switzerland; European Society of Cardiology, France; German Medical Association, Germany; Irish Medical Organisation, Ireland; Royal College of Pathologists of Australasia, Australia

Track 12: Anatomic pathology

Anatomical pathology is the significant claim to fame of pathology those arrangements with the investigation of the morphologic parts of infection. Anatomical Pathology worries with the finding of tissue and organ based large scale or tiny testing. The most recent exploration experiences from the accompanying themes such as Radio recurrence recognizable proof and example following propelled biosafety hones, Multi-model anatomical pathology and Anatomical pathology of sexually transmitted maladies.

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Relevant Conferences:

Pathology Conference,  May 09-11, 2016 Chicago, USA; Clinical Pathology Congress, Sept 26-28, 2016 Toronto, Canada; Applied Ergonomics Conference, 21–24 March 2016 Orlando, United States; Medical Case Reports Conference, June 30-July 02, 2016 Valencia, Spain; Cytology & Histology Annual Meeting, August 11-12, 2016 Birmingham, UK; Molecular Pathology Congress, July 25-27, 2016 Melbourne, Australia; Brain Injury Meetings 24–27 January, Santa Fe, USA; Conference on Advances in Cell Biology, March 18-20, 2016 Los Angeles, USA; Cervical Cancer Conference, September 22-23, 2016 Vienna, Austria; Cancer Annual Symposium, April 30, 2016 Florida, USA.

Related Associations and Societies:

American Society for Clinical Pathology, USA; American Heart Association, USA;  Boston Society for Medical Improvement, USA; American Board of Internal Medicine, USA; American Board of Medical Genetics, USA; American College of Cardiology, USA; American Board of Family Medicine, USA

Track 13: Forensic pathology

Forensic pathology is a sub-claim to fame of pathology that spotlights on examining so as to decide the reason for death a cadaver. The post-mortem examination is performed by a restorative analyst, more often than not amid the examination of criminal law cases and common law cases in a few purviews. This incorporates measurable post-mortem contextual analyses, determination of after death interim, MRNA examination of death examinations, criminological veterinary pathology (utilization of veterinary pharmaceutical to the legal sciences), and suggestions in legal pathology and posthumous interim investigation

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Relevant Conferences:

Euro Medical Case Reports Conference, June 30-July 02, 2016 Valencia, Spain; Cytology & Histology Annual Meeting, August 11-12, 2016 Birmingham, UK; Molecular Pathology Congress, July 25-27, 2016 Melbourne, Australia; Pathology Conference,  May 09-11, 2016 Chicago, USA; Clinical Pathology Congress, Sept 26-28, 2016 Toronto, Canada; Applied Ergonomics Conference, 21–24 March 2016 Orlando, United States; Brain Injury Meetings 24–27 January, Santa Fe, USA; Conference on Advances in Cell BiologyMarch 18-20, 2016 Los Angeles, USA; Cervical Cancer Conference, September 22-23, 2016 Vienna, Austria; Cancer Annual Symposium, April 30, 2016 Florida, USA.

Related Associations and Societies:

Association for Molecular Pathology, USA; Congenital Heart Surgeons' Society, USA; Denver Medical Society, USA; Association of Directors of Anatomic and Surgical Pathology, USA;  American Board of Internal Medicine, USA

Track 14: Renal Pathology

Renal Pathology is a subtopic of anatomical pathology that with the conclusion and portrayal of kidney related maladies. The renal pathology research discoveries are connected with light microscopy, electron microscopy and immunofluorescence to acquire the precise analysis. Renal Pathology or kidney pathology covers the themes poisonous tubular corruption, renal carcinomas, Diabetic glomerulosclerosis and other kidney related infections analysed under magnifying lens or sub-atomic testing. Renal pathology in nephrology, poisons, tumors and Pathology of lupus glomerulonephritis are likewise vital examination points for renal pathology. Therapeutic renal sicknesses might influence the glomerulus, the tubules and interstitium, the vessels, or a mix of these compartments.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Pathologists Meeting, October 10-12, 2016 Manchester, UK, Clinical Pathology Congress Meeting, September 26-28, 2016 Toronto, Canada, Surgical Pathology Summit Breast and Gynaecologic Tract, Oct 17-20, 2016, Hawaii, USA, Surgical Pathology & Cytopathology conferences, July 11-14, 2016, Hawaii, USA

Related Associations and Societies:

The United States and Canadian Academy of Pathology, USA; Paediatric Pathology Society, UK; Association of Indian Pathologists in North America, USA; Association of Directors of Anatomic and Surgical Pathology, USA

Track 15: Veterinary Pathology

Veterinary Pathology is the study and analysis of creature illness by utilizing creature tissue and liquids. Veterinary Pathology is arranged into two fundamental teaches; those are veterinary anatomical pathology and veterinary clinical pathology. Veterinary Pathology manages the accompanying sicknesses like Veterinary parasite maladies and Veterinary parasitology though Veterinary clinical pathology manages the determination of illness in light of the research facility examination. The American school of veterinary pathologists and European school veterinary pathologists are the primary associations taking a shot at pathology research and allows for the exploration. Veterinary pathology gives a basic connection between the fundamental and clinical sciences.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Relevant Conferences:

Medical Case Reports Conference, June 30-July 02, 2016 Valencia, Spain; Histology Annual Meeting, August 11-12, 2016 Birmingham, UK; Molecular Pathology Congress, July 25-27, 2016 Melbourne, Australia; Pathology Conference,  May 09-11, 2016 Chicago, USA; Clinical Pathology Congress, Sept 26-28, 2016 Toronto, Canada; Applied Ergonomics Conference, 21–24 March 2016 Orlando, United States; Brain Injury Meetings 24–27 January, Santa Fe, USA; Conference on Advances in Cell Biology, March 18-20, 2016 Los Angeles, USA; Cervical Cancer Conference, September 22-23, 2016 Vienna, Austria; Cancer Annual Symposium, April 30, 2016 Florida, USA

Related Associations and Societies:

American Medical Association, USA; Wisconsin Society of Pathologists, USA; American College of Surgeons, USA; Association of Clinical Pathologists, UK; American Society for Gastrointestinal Endoscopy, USA; American Society for Clinical Pathology, USA; ; British Medical Association, UK

Track 16: Hematopathology

Hematopathology is a subspecialty of pathology. Hematopathology worry with the investigation of hematopoietic cells maladies and hematological issue. An extensive variety of finding test are done in Acute and endless leukemia, Myelodysplastic disorders, Myeloproliferative issue, Anemias, Benign bone marrow and lymph hub issue, B-cell lymphomas and T-cell lymphomas and Cutaneous lymphomas

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Practical Hematopathology Conferences, June 27-30,2016, Georgia, USADigestive Tract Pathology Symposiums, July 2-9,2016, Rome, Surgical Pathology Meetings on  Breast and Gynaecologic Tract, Oct 17-20, 2016, Hawaii, USA European Pathology Congress, June 16-17, 2016 Alicante, Spain., Clinical Pathology Congress Meeting, September 26-28, 2016 Toronto, Canada

Related Associations and Societies:

Canadian Medical Association, Canada; American College of Gastroenterology, USA; Brazilian Medical Association, Brazil; American College of Radiology, USA; Royal College of Pathologists, UK; Royal Society of Medicine, UK;  American College of Cardiology, USA

Track 17: Histopathology

Alludes to the tiny examination of different types of human tissue. In particular, in clinical medication, histopathology alludes to the examination of a biopsy or surgical example by a pathologist, after the example has been prepared and histological segments have been put onto glass slides. This stands out from the techniques for cytopathology which uses free cells or tissue sections. Histopathological examination of tissues begins withsurgery, biopsy, or dissection. The tissue is expelled from the body of a life form and after that set in a fixative which settles the tissues to forestall rot. The most widely recognized fixative is formalin, albeit solidified segment settling is likewise normal. To see the tissue under a magnifying instrument, the segments are recolored with one or more shades. The point of recoloring is to uncover cell segments; counterstains are utilized to give contrast. Histochemistry alludes to the study of utilizing concoction responses between research facility chemicals and parts inside of tissue. The histological slides are then translated indicatively and the subsequent pathology report portrays the histological discoveries and the conclusion of the pathologist. On account of disease, this speaks to the tissue finding required for most treatment conventions.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Related Associations and Societies:

California Medical Association, USA;  Federation of Clinical Immunology Societies, USA; Association of Directors of Anatomic and Surgical Pathology, USA ; American Board of Internal Medicine, USA; American Board of Medical Genetics, USA; Irish Medical Organisation, Ireland

Track 18: Gastrointestinal pathology

Gastrointestinal pathology is the subspecialty of surgical pathology which deals with the determination and depiction of neoplastic and non-neoplastic diseases of the digestive tract and additional organs, for instance, the pancreas and liver. Different liver limit tests are available to test the right limit of the liver. These tests for the region of chemicals in blood that are ordinarily most plenteous in liver tissue, metabolites or things. serum proteins, serum egg whites, serum globulin, alanine transaminase, aspartate transaminase, prothrombin time, partial thromboplastin time. The enthusiasm for gastroenterology care and symptomatic systems continue extending, driven by a growing rate of gastrointestinal infection and the prerequisite for colorectal development screening in the developing patients.

Related Pathology Conferences | Laboratory Conferences | ConferenceSeries Ltd

Surgical Pathology Conferences, May,18-20,2016, Madrid, Spain, Surgical Pathology & Cytopathology conferences, July 11-14, 2016, Hawaii, USA, Meeting on Medical Case Reports, May 09-10, 2016 New Orleans, Louisiana, USA, Conference on Cytopathology & Histopathology Conference series August 10-12, 2016 Las Vegas, Nevada, USA

Related Associations and Societies:

Catholic Medical Association, USA; American Society of Cytopathology, USA; American Association for Cancer Research, USA; College of American Pathologists, USA; American Gastroenterological Association, USA; American Society of Clinical Oncology, USA; ; Digital Pathology association, Indiana

 

 

Market Analysis

Importance & Scope:

Digital pathology has been increasingly used for education, clinical practice, and research.Digital imaging in the pathology laboratory has improved significantly with advances in computers, digital camera technology, and whole-slide imaging (WSI) scanners. Digital imaging allows pathologists to become untethered from conventional light microscopes, which has resulted in increased use of telepathology applications. Development of image analysis algorithms has allowed pathologists to reproducibly provide more accurate quantification of histological and immunohistochemical biomarkers and offers the potential to capitalize on computer-aided diagnosis (CAD).

Digital Pathology 2017 conference will cover the new research Techniques and concentrates on Exhibition of new Products introduced by the Pathology Laboratories. Digital Pathology brings advanced and Clinical research into mechanisms of Disease.

Conference Highlights:

  • Strategy and Technology
  • Pathology Informatics
  • Telepathology
  • Digital Image Analysis
  • Digital Pathology Applications and Research Case Studies
  • Digital pathology versus Traditional Microscopy
  • Digital Pathology Environment
  • Digital Pathology Workflow
  • Digital Pathology Utility in The Future
  • Current Status and Future Perspectives
  • Dermatopathology and Diagnostics
  • Anatomic pathology
  • Forensic pathology
  • Renal Pathology
  • Veterinary Pathology
  • Hematopathology
  • Histopathology
  • Gastrointestinal

Digital pathology Market analysis:

Industry Insights

Increasing global prevalence of chronic diseases, rising demand for faster and accurate pathology test results, automation of pathology systems and supportive government initiatives are some high impact rendering factors expected to fuel the growth of the digital pathology market over the forecast period. Digital pathology refers to the digitization of conventional pathology lab and tests in order to increase workflow efficiency via faster and accurate analyses. Additionally, growing demand for novel treatment options, laboratory expenses reduction and better patient care are further likely to drive the growth of the digital pathology market. The global digital pathology market was valued at USD 248.4 million in 2013 and is expected to grow at a CAGR of over 12.0% over the forecast period.

Digital pathology solutions provide high resolution sample scanning, virtual storage of digital slides, and analysis & interpretation of histological images on computer screen or smart phones. It helps pathologist consult other experts across the globe without physical transportation of slides thereby, speeding up the analysis process. Increasing cancer mortality is pushing the need for faster diagnosis mechanisms. According to the W.H.O, cancer diagnosis is expected to increase by 70% in the next two decades with an estimated 1.41 million misdiagnoses of cancer globally. Manufactures are striving to provide accurate and effective diagnosis solutions pertaining to cancer diagnosis. For example, in March 2015, GE Healthcare via its JV Omnyx, LLC, entered in to strategic collaboration with Clarient Diagnostic Services, Inc. in an attempt to accentuate research related to personalized cancer therapeutics.

The next section of report highlights the digital pathology market by region. It provides the market outlook for 2015-2022 and sets the forecast within the context of the global digital pathology market. The study discusses key regional trends, drivers and restraints contributing to growth of digital pathology market, worldwide. Key regions assessed in this report include North America, Latin America, Western Europe, Eastern Europe, Asia Pacific Excluding Japan (APEJ), Japan and the Middle East & Africa.

Global digital pathology market, by region, 2012 – 2022 (USD Million)

Regional Insights

North America witnessed the highest market penetrations pertaining to digital pathology technologies. Increasing prevalence of cancer boosting the demand for fast and accurate diagnostics, the need to effectively manage EMR (Electronic Medical Records) and the presence of favorable reimbursement policies are some key factors attributing to the current market scenario. Trends witnessed in the European digital pathology market are found to be in congruence with North America. Asia Pacific and Latin America are expected to spearhead market growth over the forecast period. Presence of large untapped opportunities in the emerging markets of India, Brazil and China, increasing use of digital pathology in cancer diagnosis and constantly improving healthcare infrastructure in these countries are some factors expected to drive regional market growth.

Technology Insights

WSI (Whole Slide Imaging) or virtual microscopy was found to be the most commonly used technology. The segment’s market dominance is attributed to associated advantages such as scanning of slides at Z axis, multiple magnifications and developing enhanced resolution digital images in a comparatively shorter time span. Additionally, increasing usage of WSI for academic research is also expected to drive market growth in near future. Dynamic telepathology or robotic interactive telepathology is gaining popularity owing to its capability of functioning as bidirectional. It is also helpful in the study of frozen tissue sections. Additionally, features such as real time imaging and controlled movement associated with dynamic telepathology are expected to drive segment growth during the forecast period.

 

Application Insights

Digital pathology system found the largest application in disease diagnosis in 2014. Software solutions enable sharing of virtual slides and help experts reach a consensus diagnoses in a relatively shorter time frame. Image analysis via computer based algorithms provides accurate diagnosis and is instrumental in deciding treatment pattern for chronic diseases such as cancer. Increasing prevalence of chronic diseases triggering the demand for advanced diagnostics is expected to provide further growth opportunities to this digital pathology market. The digital pathology based academics market is expected to grow at the fastest rate over the forecast period. The incorporation of digital pathology in research studies such as tumor morphological study and biomarker profiling are some factors accounting for its rapid growth.

Competitive Insights

Prominent players of this market include 3DHistech Inc., GE Healthcare, Leica Biosystems, Philips Healthcare, Ventana Medical Systems, Inc., Definiens, Olympus Corporation, Objective Pathology Services, Omynx LLC, LigoLAb LLC, Hamamatsu Photonics Inc., and MicroSkan Technologies. These players, in an attempt to increase market penetration adhere to sustainability strategies such as the introduction of technologically advanced products, entering into strategic collaborations and striving towards capitalizing on the untapped opportunities available in the emerging Asia Pacific and Latin American markets. For example, In March 2015, Royal Philips (Healthcare) of the Netherlands entered in to a joint development agreement with New York (U.S.) based Mount Sinai Health System in order to develop digital image repository of patient tissue sample and data analytics.

Why to attend?

Digital Pathology 2017 could be an exceptional event that brings along a novel and innovative International mixture of giant and medium pathology analysis, leading universities and Digital pathology analysis establishments creating the conference an ideal platform to share expertise, faster collaborations across trade and world, and assess rising technologies across the world. World-renowned speakers, the most recent techniques, tactics, and the newest updates in Pathology fields are hallmarks of this conference.

 

 

 

 

Past Conference Report

Digital Pathology 2016

We gratefully thank all our wonderful speakers, conference attendees, students for making Digital Pathology 2016 Conference the best ever!

The World Digital Pathology and Pathologists Congress hosted by the Conference Series LLC was held during December 05-06, 2016 at Melia Avenida America, Madrid, Spain based on the theme Transforming Pathology with Complete Digital Solutions. Benevolent response was received from the Editorial Board Members of Conference Series LLC Journals along with scientists, researchers, students and leaders from various fields of Pathology, who made this event a grand success. Conference Series will acknowledge with gratitude the support by all the Editorial Board Members of Journal of Clinical & Experimental Pathology and Journal of Medical & Surgical Pathology for their valuable suggestions for up growth of the Organization

The conference was initiated with the Honorable presence of the Keynote forum. The list includes:

  • Dongfeng Tan, University of Texas MD Anderson Cancer Center, USA
  • Marcio Alvarez-Silva, Universidade Federal de Santa Catarina, Brazil
  • Christian Munzenmayer, Fraunhofer Institute for Integrated Circuits IIS, Germany
  • Tomoo Itoh, Kobe University Hospital, Japan
  • Ichiro Mori, International University of Health and Welfare, Japan
  • Michael Grunkin, Visiopharm A/S, Denmark
  • K H Ramesh, Director, Montefiore Medical Center, USA

The meeting reflected various sessions, in which discussions were held on the following major scientific tracks:

  • Pathology informatics
  • Strategy and Technology
  • Telepathology
  • Digital Pathology Utility in The Future
  • Digital Pathology Applications and Research Case Studies
  • Digital Image Analysis
  • Molecular Genetic Pathology
  • Hematopathology
  • Veterinary Pathology
  • Clinical Pathology
  • Anatomic Pathology

Conference Series LLC offers its heartfelt appreciation to the Organizing Committee Members, adepts of field, various outside experts, company representatives and other eminent personalities who supported the conference by facilitating the discussion forums. Conference Series LLC also took privilege to felicitate the Organizing Committee Members, Editorial Board Members and Media Partners who supported this event.

With the grand success of Digital Pathology 2016, Conference Series LLC is proud to announce the 2nd International Conference on Digital Pathology to be held during November 02-03, 2017 at San Antonio, USA. Digital Pathology 2017 has been prepared with the aim and the specific intent of promoting the development of new perspectives and ideas for exploiting the high level of knowledge achieved by the scientific community in pathology disciplines.

For More details visit: http://digitalpathology.conferenceseries.com/


Past Reports  Proceedings  Gallery  

Supported By

Journal of Clinical & Experimental Pathology Journal of Cytology & Histology: Open Access Molecular Histology & Medical Physiology Journal of Medical & Surgical Pathology

All accepted abstracts will be published in respective Conferenceseries International Journals.

Abstracts will be provided with Digital Object Identifier by


Keytopics

  • Acquisitions, Processing, Archiving And Retrieval Of WSI
  • Annotation Tools In Digital Pathology
  • Automated Pathology Image Analysis
  • Basal Cell Carcinoma
  • Biobanking
  • Biomarker Analysis /research / Quantification
  • Challenges In Image Analysis
  • Clinical Trials
  • Current Status And Future Perspectives
  • Dermatomyositis Pathogenesis
  • Dermatopathology And Diagnostics
  • Diagnosis Through Digitalization
  • Diagnostics
  • Digital Image Analysis
  • Digital Pathology Applications And Research Case Studies
  • Digital Pathology Environment
  • Digital Pathology Scanner
  • Digital Pathology Slide Viewer
  • Digital Pathology Utility In The Future
  • Digital Pathology Versus Traditional Microscopy
  • Digital Pathology Workflow
  • Digital Skin Cancer And Screening
  • Digital Storage Devices
  • Eczema Pathogenesis
  • Immunohistochemistry
  • Improving WSI Workflow Efficiency
  • Pathology Access Through Mobile Devices
  • Pathology Access Through Mobile Devices
  • Pathology Acquisitions, Processing, Archiving And Retrieval Of WSI
  • Pathology Analysis
  • Pathology Automation
  • Pathology Automation Through Digitalization
  • Pathology Cloud Computing
  • Pathology Digital Analysis Software
  • Pathology Improving WSI Workflow Efficiency
  • Pathology Informatics
  • Pathology Integrate
  • Pathology Manage
  • Pathology PACS
  • Pathology Sharing
  • Pathology Teaching Program
  • Pattern Recognition In Digital Instruments
  • Precision / Personalized Medicine
  • Psoriasis Pathogenesis
  • Quantitative Image Analysis Research
  • Reactive Erythemas
  • Squamous Cell Carcinoma
  • Strategy And Technology
  • Surgical Pathology
  • Tissue Based Research / Imaging
  • Virtual Dermatopathology
  • Visualization Methods For Diagnosis
  • Vitiligo