iMIL4PATH: A Semi-Supervised Interpretable Approach for Colorectal Whole-Slide Images

A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer

(2022) Cowan Ho et al.   Scientific Reports

Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities

(2022) Diana Montezuma et al.   Diagnostics

Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review

(2022) Athena Davri et al.   Diagnostics

Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence

(2021) K. S. Wang et al.   BMC Medicine

CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance

(2021) Sara P. Oliveira et al.   Scientific Reports

Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images

(2021) Gang Yu et al.   Nature Communications

Digital Pathology Workflow Implementation at IPATIMUP

(2021) Catarina Eloy et al.   Diagnostics

A Survival Guide for the Rapid Transition to a Fully Digital Workflow: The “Caltagirone Example”

(2021) Filippo Fraggetta et al.   Diagnostics

Recommendations for Follow-Up After Colonoscopy and Polypectomy: A Consensus Update by the US Multi-Society Task Force on Colorectal Cancer

(2020) Samir Gupta et al.   GASTROINTESTINAL ENDOSCOPY

Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours

(2020) Osamu Iizuka et al.   Scientific Reports

Post-polypectomy colonoscopy surveillance: European Society of Gastrointestinal Endoscopy (ESGE) Guideline – Update 2020

(2020) Cesare Hassan et al.   ENDOSCOPY

Current and future applications of artificial intelligence in pathology: a clinical perspective

(2020) Emad A Rakha et al.   JOURNAL OF CLINICAL PATHOLOGY

Weakly-Supervised Classification of HER2 Expression in Breast Cancer Haematoxylin and Eosin Stained Slides

(2020) Sara P. Oliveira et al.   Applied Sciences-Basel

Current Trends of Artificial Intelligence for Colorectal Cancer Pathology Image Analysis: A Systematic Review

(2020) Nishant Thakur et al.   Cancers

Evaluation of a Deep Neural Network for Automated Classification of Colorectal Polyps on Histopathologic Slides

(2020) Jason W. Wei et al.   JAMA Network Open

Automatic deep learning-based colorectal adenoma detection system and its similarities with pathologists

(2020) Zhigang Song et al.   BMJ Open

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

(2019) Gabriele Campanella et al.   NATURE MEDICINE

Image analysis and machine learning in digital pathology: Challenges and opportunities

(2016) Anant Madabhushi et al.   MEDICAL IMAGE ANALYSIS

Assessment of algorithms for mitosis detection in breast cancer histopathology images

(2015) Mitko Veta et al.   MEDICAL IMAGE ANALYSIS

A disease of growth

(2015) David Holmes   NATURE

Colorectal cancer

(2015) Herb Brody   NATURE

Reproducibility of the Villous Component and High-grade Dysplasia in Colorectal Adenomas

(2013) Dipti Mahajan et al.   AMERICAN JOURNAL OF SURGICAL PATHOLOGY

The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

(2013) Kenneth Clark et al.   JOURNAL OF DIGITAL IMAGING