Filters








1,998 Hits in 7.3 sec

Digital Imaging in Pathology: Whole-Slide Imaging and Beyond

Farzad Ghaznavi, Andrew Evans, Anant Madabhushi, Michael Feldman
2013 Annual Review of Pathology  
Today, digitization of entire glass slides at near the optical resolution limits of light can occur in 60 s. Whole slides can be imaged in fluorescence or by use of multispectral imaging systems.  ...  Digital imaging is unlocking the potential to integrate primary image features into high-dimensional genomic assays by moving microscopic analysis into the digital age.  ...  tissue classification.  ... 
doi:10.1146/annurev-pathol-011811-120902 pmid:23157334 fatcat:g7ba47thmjfvhbos7dxke4nsoy

Beyond "bad news": the diagnosis, prognosis and classification of lymphomas and lymphoma patients in the age of biomedicine (1945-1995)

Peter Keating, Alberto Cambrosio
2003 Medical history  
Confronted with this demand, clinicians have sometimes hesitated before pronouncing on the future.3 Philosophers have suggested that part ofthe clinicians' reluctance to predict lies in the fact that modem  ...  prognostic information comes from statistics about classes or groups ofpatients and so does not apply directly to individuals.4 The problem ofprognosis is further  ...  classification.70 Rappaport's prognosis was embedded in part in a new architectural analysis of the lymph node biopsy specimens.  ... 
pmid:12905916 pmcid:PMC1044630 fatcat:frlqq2ux5jf47d65u2llufcxom

Beyond the microscope: interpreting renal biopsy findings in the era of precision medicine

Serena M Bagnasco
2018 AJP - Renal Physiology  
The kidney biopsy remains the gold standard for the diagnosis of renal disease, but the field of renal pathology is evolving, classification of renal parenchyma lesions and histopathological diagnostic  ...  criteria are undergoing more validation and updates, and new technologies and assays are sought to improve efficiency and accuracy of the diagnostic process.  ...  Test of the reproducibility for scoring glomerular and tubulointerstitial features ("descriptors") among 12 pathologists on whole slide images (WSI) of kidney biopsies showed good to excellent concordance  ... 
doi:10.1152/ajprenal.00407.2018 pmid:30280602 fatcat:7gtprx57ova3jkarvh2wjcdt2y

Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images [article]

Bruno Korbar, Andrea M. Olofson, Allen P. Miraflor, Katherine M. Nicka, Matthew A. Suriawinata, Lorenzo Torresani, Arief A. Suriawinata, Saeed Hassanpour
2017 arXiv   pre-print
In this work, we built an automatic image-understanding method that can accurately classify different types of colorectal polyps in whole-slide histology images to help pathologists with histopathological  ...  analysis tasks.  ...  Image Annotation High-resolution histology images for colorectal polyp samples are large— most of the slides encompass normal tissue and only a small part of a whole-slide image is actually related  ... 
arXiv:1703.01550v2 fatcat:nxppmg3rinevflzw7vbuuyrp2m

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning [article]

Łukasz Rączkowski, Marcin Możejko, Joanna Zambonelli, Ewa Szczurek
2019 bioRxiv   pre-print
Finally, we utilise our model to segment whole-slide images of colorectal tissue and compute segmentation-based spatial statistics.  ...  Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice.  ...  Multiple machine learning methods go beyond the tasks of tissue type classification and whole-slide segmentation, confirming there is more information about the patients encrypted in histopathological  ... 
doi:10.1101/658138 fatcat:blex4hpurve3ni5bt7ankl665q

Finding a Needle in the Haystack: Attention-Based Classification of High Resolution Microscopy Images [article]

Naofumi Tomita, Behnaz Abdollahi, Jason Wei, Bing Ren, Arief Suriawinata, Saeed Hassanpour
2018 arXiv   pre-print
Existing work has used a sliding window for crop classification, followed by a heuristic to determine the label for the whole slide.  ...  Due to the large size of these images, they cannot be transferred into GPU memory, so there are currently no end-to-end deep learning architectures for their analysis.  ...  Acknowledgment This research was supported in part by a National Institutes of Health grant, P20GM104416.  ... 
arXiv:1811.08513v1 fatcat:yd3pp6jojza4disy2bnh3dsx54

New unified insights on deep learning in radiological and pathological images: Beyond quantitative performances to qualitative interpretation

Yoichi Hayashi
2020 Informatics in Medicine Unlocked  
Next, we review limitations of DL in pathology in regard to histopathology and cytopathology.  ...  reason for this classification in the form of if-then rules.  ...  DP concerns all aspects of the processing of digitized histopathology slides, including image analysis.  ... 
doi:10.1016/j.imu.2020.100329 fatcat:ka6e7bs3h5e7lpnueup5obfrzm

Deep representation learning for domain adaptatable classification of infrared spectral imaging data [article]

Arne P. Raulf, Joshua Butke, Claus Küpper, Frederik Großerueschkamp, Klaus Gerwert, Axel Mosig
2019 bioRxiv   pre-print
involve iterative procedures that are computationally demanding, so that computation time required for preprocessing does not keep pace with recent progress in infrared microscopes which can capture whole-slide  ...  To validate the robustness of the resulting classifier, we demonstrate that a network trained on embedded tissue can be transferred to classify fresh frozen tissue.  ...  ACKNOWLEDGEMENT We want to thank Angela Kallenbach-Thieltges for providing the RF classifier for FFPE tissue thin sections.  ... 
doi:10.1101/584227 fatcat:6gcv3zvjura3hmpoqmgaa2chgq

Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning [article]

Bin Li, Yin Li, Kevin W. Eliceiri
2021 arXiv   pre-print
We address the challenging problem of whole slide image (WSI) classification. WSIs have very high resolutions and usually lack localized annotations.  ...  WSI classification can be cast as a multiple instance learning (MIL) problem when only slide-level labels are available.  ...  YL also acknowledges the support by the UW VCRGE with funding from WARF.  ... 
arXiv:2011.08939v3 fatcat:igrzeve6ergnlk6bn35peh4kcy

Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks

Baris Gecer, Selim Aksoy, Ezgi Mercan, Linda G. Shapiro, Donald L. Weaver, Joann G. Elmore
2018 Pattern Recognition  
We present a system that classifies whole slide images (WSI) of breast biopsies into five diagnostic categories.  ...  Finally, the saliency and classification maps are fused for pixel-wise labeling and slide-level categorization.  ...  Aksoy were supported in part by the Scientific and Technological Research Council of Turkey (grant 113E602) and in part by the GEBIP Award from the Turkish Academy of Sciences. E. Mercan, L. G.  ... 
doi:10.1016/j.patcog.2018.07.022 pmid:30679879 pmcid:PMC6342566 fatcat:vu3mtusfrfcgra3raunmplk6fy

Classification and Retrieval of Digital Pathology Scans: A New Dataset [article]

Morteza Babaie, Shivam Kalra, Aditya Sriram, Christopher Mitcheltree, Shujin Zhu, Amin Khatami, Shahryar Rahnamayan, H.R. Tizhoosh
2017 arXiv   pre-print
We use the whole scan images of 24 different tissue textures to generate 1,325 test patches of size 1000×1000 (0.5mm×0.5mm).  ...  In this paper, we introduce a new dataset, Kimia Path24, for image classification and retrieval in digital pathology.  ...  The "Kimia Path24" Dataset We had 350 whole scan images (WSIs) from diverse body parts at our disposal. The images were captured by TissueScope LE 1.0 1 .  ... 
arXiv:1705.07522v1 fatcat:dgtdqjc7h5byvfhuosyfxqqu3y

Classification and Retrieval of Digital Pathology Scans: A New Dataset

Morteza Babaie, Shivam Kalra, Aditya Sriram, Christopher Mitcheltree, Shujin Zhu, Amin Khatami, Shahryar Rahnamayan, Hamid R. Tizhoosh
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We use the whole scan images of 24 different tissue textures to generate 1,325 test patches of size 1000×1000 (0.5mm×0.5mm).  ...  In this paper, we introduce a new dataset, Kimia Path24, for image classification and retrieval in digital pathology.  ...  The "Kimia Path24" Dataset We had 350 whole scan images (WSIs) from diverse body parts at our disposal. The images were captured by TissueScope LE 1.0 1 .  ... 
doi:10.1109/cvprw.2017.106 dblp:conf/cvpr/BabaieKSMZKRT17 fatcat:otz2wako3rbgxjiwkhqeicz7du

Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks [article]

Jingwen Wang, Richard J. Chen, Ming Y. Lu, Alexander Baras, Faisal Mahmood
2019 arXiv   pre-print
In this work, we propose a weakly-supervised approach for grade classification in tissue micro-arrays (TMA) using graph convolutional networks (GCNs), in which we model the spatial organization of cells  ...  Previous work in deep learning-based objective Gleason grading requires manual pixel-level annotation.  ...  analysis,” Com- works for an automatic classification of prostate tissue slides puterized Medical Imaging and Graphics, vol. 35, no. 7-8, pp.  ... 
arXiv:1910.13328v2 fatcat:cxhdf6ipjzahphg2p66mkj3aqe

Artificial Intelligence-Based Image Classification for Diagnosis of Skin Cancer: Challenges and Opportunities [article]

Manu Goyal, Thomas Knackstedt, Shaofeng Yan, Saeed Hassanpour
2020 arXiv   pre-print
A large number of skin lesion datasets are available publicly, and researchers have developed AI-based image classification solutions, particularly deep learning algorithms, to distinguish malignant skin  ...  lesions from benign lesions in different image modalities such as dermoscopic, clinical, and histopathology images.  ...  M.G. contributed to the literature review and analysis of the study and drafting the manuscript.  ... 
arXiv:1911.11872v3 fatcat:hez3zmpfgzar3cjpa4ye67xczi

Deep Learning Models Combining for Breast Cancer Histopathology Image Classification

Hela Elmannai, Monia Hamdi, Abeer AlGarni
2021 International Journal of Computational Intelligence Systems  
The proposed design allows an extension to whole-slide histology images classification.  ...  To this end, automating the analysis and the diagnosis allows to improve the accuracy and to reduce processing time.  ...  ACKNOWLEDGMENTS The authors would like to thank the Center for Promising Research in Social Research and Women's Studies Deanship of Scientific Research at Princess Nourah University for funding this Project  ... 
doi:10.2991/ijcis.d.210301.002 fatcat:3url2cppfbf27n25ec2fbivx4a
« Previous Showing results 1 — 15 out of 1,998 results