Presentation Slides

[For attendees of the Digital Pathology Congress only]

NB:  You will see that not all the presenters from the conference are listed below.  This is where the company or speaker have not given permission for release.  This is usually due to corporate rules or because there was unpublished material in the presentation.  In the case of the latter, we take the view that it is better to have exclusive presentations on the day, given before official publication, than to restrict the content of the conference by insisting on releasing such data in slide form, regardless of sensitivity or readiness for external examination.  We hope you feel the same way.

If you were a speaker and have not yet responded to our request for confirmation, please email to let us know if we can release your slides as a PDF.  If there are issues with release, let me know if we need to remove your name from the page or whether there are smaller issues and we can share a revised version of the slides.

These slides are provided as a courtesy by the authors, who retain copyright. This is not a publication and slides may be withdrawn at any time at the authors request.


ANIL PARWANI; Professor of Pathology and Biomedical Informatics, Vice-Chair of Anatomic Pathology, Wexner Medical Center, Ohio State University
Breaking the barriers: Whole Slide Imaging for Primary Diagnosis and Artificial Imaging Applications

THOMAS FUCHS; Associate Professor, Computational Pathology, Memorial Sloan Kettering Cancer Center; Weill Cornell Medicine
What Does It Take to Build a Petabyte Scale AI?

** Awaiting Permission to Release **

JOEL SALTZ; Cherith Professor and Founding Chair, Department of Biomedical Informatics, Stony Brook University
Whole Slide Imaging and High-End Computing Come Full Circle

DAVID WEST; CEO, Proscia               
Dr. Strangelove or: How I Learned to Stop Worrying and Love the Machine

ULYSSES BALIS; Professor of Pathology, Director, Division of Pathology Informatics & Computational Pathology Laboratory Section, Michigan Medicine, University of Michigan
A High-Performance Machine Learning Model System for Automated Segmentation, Classification and Differential Diagnosis Generation from Whole Slide Image Subject Matter

** Awaiting Permission to Release **

GERARDO FERNANDEZ; Associate Professor, Department of Pathology, Medical Director, Center for Computational and Systems Pathology, Icahn School of Medicine at Mount Sinai & The Mount Sinai Hospital
Artificial intelligence methods for grading human cancer

** Awaiting Permission to Release **

PETER CAIE; Senior Research Fellow, University of St Andrews, UK
Towards Precision Pathology through Automated image Analysis and Machine Learning

** Awaiting Permission to Release **

ERIC WIRCH; Chief Technology Officer and Managing Director, Corista
Migrating algorithms beyond the development sandbox


JOHN TOMASZEWSKI; SUNY Distinguished Professor, Peter A. Nickerson Professor and Chair, Department of Pathology and Anatomical Science, University at Buffalo, State University of New York
Traditional AI Approaches to Computational Histopathology

GUSTAVO KUNDE ROHDE; Associate Professor, Department of Biomedical Engineering, Department of Electrical and Computer Engineering, University of Virginia
Interpretable discriminative modeling of cellular phenotypes for digital pathology

GEORGE LEE; Digital Pathology Informatics Lead / Data Scientist, Translational Medicine, Bristol-Myers Squibb
Applications of Artificial Intelligence for Immuno-oncology and Precision Medicine

MICHAEL SURACE; Scientist, MedImmune
Validation of multiplex immunofluorescence panels using multispectral microscopy for immune-profiling of formalinfixed and paraffin-embedded human tumor tissues

** Awaiting Permission to Release **

BEATRICE KNUDSEN; Professor, Biomedical Sciences and Pathology and Laboratory Medicine, Director, Translational Pathology, Cedars Sinai Medical Center
Nuclear morphometry and cancer biomarker development


RICHARD LEVENSON; Professor and Vice Chair for Strategic Technologies, Department of Pathology and Laboratory Medicine, UC Davis Health, Sacramento, CA
Slide-free, real-time histology: cooler than frozens

YAIR RIVENSON; Postdoctoral Scholar, Ozcan Nano/Bio Photonics Lab, University of California Los Angeles
Deep Learning Microscopy for Enhanced Digital Pathology


DRAZEN JUKIC; Dermatopathologist, Georgia Dermatopathology; Associate Professor, Mercer University School of Medicine, Department of Medical Education; Associate Professor, Department of Dermatology, University of Florida; Consultant Pathologist, James A. Haley VA Medical Center, Pathology and Laboratory Medicine Service
Implementation of day-to-day digital pathology in the US market

JASPER PEETERS; Head of Product Management Digital Pathology Solutions, Philips
Digital Pathology Customer survey results -100% digital sites

DOUGLAS HARTMAN; Associate Professor of Pathology & Associate Director, Pathology Informatics, University of Pittsburgh
Determining how to integrate digital pathology into your lab

STEVEN HART; Assistant Professor of Biomedical Informatics, Mayo Clinic
Digital Pathology at The Intersection of Big Data, AI, and Genomics

Poster Presentations

Click Here for Poster Abstracts

Collation of all abstracts presented in poster form over the 2 days. 

Click Here For The Poster Summary

Actual posters approved for release:

The Paradox of Exclusion of the Most Interesting Futuristic Subjects from
Meeting Programs and Summit Papers
Ishita Moghe and Kim Solez, University of Alberta, Edmonton, Alberta, Canada

Truthful Promotion of Pathology – Building Nonfictional Models of the World
to Train Sentient Artificial Intelligence
Ishita Moghe and Kim Solez, MD
Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada

Quantitative spatial analysis of single or multiplexed biomarkers on whole slide digital pathology images
in a hospital-based multi-modality core facility

Trevor D. McKee PhD, Jade Bilkey, Mark Zaidi, Sehrish Butt MSc, Abhishek Rawat PhD,
Fred Fu MSc, Justin Grant PhD MBA, David A. Jaffray PhD ABMP
STTARR Innovation Centre, Toronto, Canada

A deep learning-based model of normal histology
Tobias Sing1*, ImtiazHossain1*, Holger Hoefling1*, Arno Doelemeyer1, Chandrassegar Saravanan2, Alessandro Piaia1,
 KunoWuersch1, Vincent Romanet1, Wolfgang Zipfel1, Mike Steeves2, Oliver Turner3*, Pierre Moulin1*
1Novartis Institutes for BioMedicalResearch, Basel, Switzerland; 2Novartis Institutes for BioMedicalResearch, Cambridge, MA, USA;
3Novartis Institutes for BioMedicalResearch, East Hanover, NJ, USA
*These authors contributed equally

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
Rebecca Calder 2,4, DPM, MLS(ASCP)CM, Daniel Stevens 3,4, DPM, MLS(ASCP)CM and Zev Leifer, Ph.D. 1
1 Professor of Microbiology and Pathology, New York College of Podiatric Medicine (NYCPM), New York, NY (
2 Podiatric Resident, MetroWest Medical Center, Framingham, MA (
3 Podiatric Resident, Good Samaritan Hospital Medical Center, West Islip, NY (
4 Work done while undergraduate student at NYCPM

For further information please contact;

Scott Taylor
+44 (0) 1865 849841

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