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Digital Pathology Resources

Welcome to the Digital Pathology resources page: a curated list of presentation videos, slide decks, reports and posters.

These resources were produced from our Digital Pathology series of events. The next related conferences are:

Presentation Videos

Kidney Medicine in the Digital Age: Single Cell Sequencing and Artificial Intelligence

Kim Solez & Ishita Moghe

Accelerating the impact of AI through 100% digitization of pathology workflow

Panel discussion featuring Peter Hamilton, David Snead, Jo Martin, Juan Antonio Retamero Diaz and Neil Mesher

How Digitisation Can Improve Pathology Service – the Danish Experience

Vera Jacqueline Marita Timmermans, Clinical Associate Professor, Part-time Lecturer

Nuclear Morphometry and Cancer Biomarker Development

Beatrice Knudsen, Professor of Biomedical Sciences, Pathology Director, Translational Pathology & Scientific Director of Translational Research Core, Cedars-Sinai

Migrating Algorithms Beyond the Development Sandbox

Eric Wirch, CTO & Managing Director at Corista

Applications of Artificial Intelligence for Immuno-oncology and Precision Medicine

George Lee, Bristol-Myers Squibb

Interpretable Discriminative Modelling of Cellular Phenotypes for Digital Pathology

Gustavo Rohde, Associate Professor, Biomedical Engineering & Electrical and Computer Engineering, University of Virginia

Dr. Strangelove, or: How I Learned to Stop Worrying and Love the Machine

David West, CEO, Proscia

Reports

The Benefits of Computational Pathology

Digital Pathology as a Diagnostic Tool

Poster Presentations

Standing on the Shoulders of Giants – Towards a winning FP9 proposal

Dr. Patrick Jackman

Up-converting nanoparticles as a tool for histopathological tissue evaluation with multiplexing and machine learning potential

Krzysztof Krawczyk, Stefan Andersson-Engels and Anders Sjögren

Convolutional neural network for colonoscopy tissue segmentation and classification

Capucine Bertrand, Saïma Ben Hadj, Catherine Guettier, Jean-François Fléjou, Jean-Yves Scoazec, Jean-François Pomerol, Pauline Baldo

Tumor budding in brightfield immunostained colon sections

Michaela Benz, Volker Bruns, Malte Kötter, Serop Baghdadlian, Matthias Bergler, Markus Eckstein, Regine Schneider- Stock, Christian Münzenmayer, Arndt Hartmann, Carol Geppert

On the verge of clinical outcome prediction: humans teaching machines – machines teaching humans

Kubach J. & Neuner C., Kobow K., Coras R., Bluemcke I., Jabari S.

High Proximity Between T cells and PD-L1+ Cells in HPV Negative Oropharyngeal Cancer Predicts Poor Outcome

A. M. Tsakiroglou, M. Fergie, K. Oguejiofor, K. Linton, D. Thompson, P. L. Stern, S. Astley, C. West and R. J. Byers

Single-Cell Sequencing & Artificial Intelligence: Bringing Kidney Transplantation to the Digital Age & Beyond

Ishita Moghe, BSc and Kim Solez, MD

Deep learning based detection of tumor tissue compartments improves prognostic immunoprofiling in muscle-invasive bladder cancer

Katharina Nekolla, et al

Preliminary Studies in the use of the Foldscope Paper Microscope for Diagnostic Analysis of Crystals in Urine: Issues in the Analysis of Liquid Samples and Potential Applications in Low Budget/Low Tech Regions of the World

R. Calder, MetroWest Medical Center, D. Stevens, Good Samaritan Hospital Medical Center, Z. Leifer, NYCPM

Distinction of Benign and Malignant Breast Histology Through Deep Learning

Jerome Cheng, MD Department of Pathology, Michigan Medicine, Ann Arbor, Michigan

Biomarker Colocalization Analysis of a Virtual 12-plex using Discovery Chromogenic Dyes and Tissuealign Co-Registration Software

Benjamin Freiberg and Regan Baird, Visiopharm

Multimodal Image Analysis: Relationship Between Pathological Image and Microscopic Ultrasound Image

S. Kashio, T. Ogawa, K. Nakano, et al., Graduate School of Science and Engineering, Chiba University

Truthful Promotion of Pathology – Building Nonfictional Models of the World to Train Sentient Artificial Intelligence

Ishita Moghe and Kim Solez, University of Alberta, Edmonton, Alberta, Canada

Machine Learning Approach to Tumor Immune Infiltrate Analysis from H&E Images

Rishi R. Rawat, Madiha Hussain, David B. Agus, et al., Lawrence J. Ellison Institute for Transformative Medicine, USC

Automatic Detection of Slides to Rescan for Whole Slide Imaging Scanner

Hossain Md Shakhawat, Tokyo Institute of Technology, Tomoya Nakamura, Japan Science and Technology Agency, Fumikazu Kimura, Shinshu University et al

A Deep Learning-based Model of Normal Histology

Tobias Sing, Imtiaz Hossain, Holger Hoefling et al, Novartis Institutes for BioMedical Research

Toward the Automation of Fluorescence In Situ Hybridization (FISH) Scoring Using a Confocal Whole Slide Image Scanner and Image Analysis Software

Naohiro Uraoka, Xiujun Fu, Paul Matises, et al., Memorial Sloan Kettering Cancer Center, New York

Presentation Slides

Up-Converting NanoParticles as a powerful tool for tissue evaluation

KRZYSZTOF KRAWCZYK, R&D Manager, Lumito AB

Using Modern Technologies in Digital Pathology to Diagnose Children With Cancer in Malawi From 7,400 Miles Away

Yuchun Ding, Research Associate, University of Newcastle

Melanoma Diagnosis and Staging using Digital Pathology

Prof. Mrinal Mandal, University of Alberta

Kidney Medicine in the Digital Age: Single-Cell Sequencing & AI

Ishita Moghe & Kim Solez, University of Alberta

Applications of deep neural networks for of digital pathology (and embryo) image classification

Iman Hajirasouliha, Cornell University

Disease processes by pixel analysis – the new era of digital pathology

David Snead, Consultant Histopathologist and Clinical Service Lead, (CWPS and UHCW NHS Trust)

An Image Retrieval System for Digital Pathology

Manfredo Atzori, HES-SO, Valais-Wallis

Digital Pathology at John Hopkins

Alexander Baras, Assistant Professor, Oncology, Urology, & Oncology

Implementation of day-to-day Digital Pathology in the US market

Drazen M. Jukic, Associate Professor, University of Florida

PRS: Co-resident Objective Measure of IHC Stain Performance for Process QC and Diagnostic Aid

Frederick Husher, Chief R&D, PRS Ltd.

Applied Digital Pathology in Colon and Lung Cancer Research

Viktor H. Koelzer, Pathologist & SNSF Research Fellow, University of Oxford and University of Birmingham

Open and Collaborative Software for Digital Pathology

Raphael Maree, Research Fellow, University of Liège

Digital Pathology – Implementing it in a Leading Cancer Centre

Pedro Oliveira, Pathologist, Hospital da Luz

Digital Pathology Customer Survey Results – 100% digital slides

Jasper Peeters, Head of Product Management Digital Pathology Solutions, Philips