Free Online Course
BRIDGING THE GAP BETWEEN PATHOLOGY
AND COMPUTER SCIENCE
An Independent Digital Pathology Course
What You'll Learn on This FREE Course!
Learn #1:
"What were the beginnings of computational pathology? How far along are we now and where are we heading? What do we need to improve in the current setup to work better and faster?"
Learn #2:
"Which image analysis approach to choose for your pathology images? Should it be classical computer vision or deep learning-based approach? Object detection or semantic segmentation? After this event you will know!"
Learn #3:
"What other type of data in addition to images can we leverage in computational pathology? How can we integrate them in the research pipeline and what does it mean in clinical pathology?"
MEET THE SPEAKERS
JEROEN VAN DER LAAK
Professor of computational Pathology at the Department of Pathology of the Radboud University Medical Center in Nijmegen & guest professor at the Center for Medical Image Science and Visualization (CMIV) in Linkoping, Sweden.
RESEARCH FOCUS:
Improving cancer diagnostics and prognostics with machine learning and large data sets in Pathology
GEERT LITJENS
Assistant Professor at Radboud University Nijmegen Medical Center
RESEARCH FOCUS:
Application of modern machine learning methods to oncological pathology (focus on prostate and pancreatic cancer)
FRANCESCO CIOMPI
Assistant Professor of Computational Pathology at Radboud University Medical Center, Nijmegen.
RESEARCH FOCUS:
AI in precision oncology, computer-aided diagnosis for large-scale digital pathology and multi-modal data
DAAN GEIJS
PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center
RESEARCH FOCUS:
Implementing deep learning in the daily routine of dermatopathologists
LESLIE TESSIER
PhD candidate in the in the Computational Pathology Group at Radboud University Nijmegen Medical Center & Resident Physician (Pathology), CHU Angers, France
RESEARCH FOCUS:
Automated assessment of tubule formation in breast cancer
LEANDER VAN EEKELEN
PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.
RESEARCH FOCUS:
Improving lung cancer immunotherapy with deep learning
MEYKE
HERMSEN
Study manager and PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.
RESEARCH FOCUS:
Deep learning applications for renal transplant pathology
KHRYSTYNA FARYNA
PhD candidate in the Computational Pathology Group at Radboud University Nijmegen Medical Center.
RESEARCH FOCUS:
Bridging the clinical integration gap for deep learning-based methods in computational pathology by improving model generalization
EDUARD CHELEBIAN
PhD candidate in the Department of Information Technology at Uppsala University, Sweden.
RESEARCH FOCUS:
How deep learning networks learn - intermediate representations of convolutional neural networks in histopathological imaging
MILDA POCEVICIUTE
PHD Candidate in the Computer Graphics and Image processing Group at Linköping University, Sweden.
RESEARCH FOCUS:
Explainable artificial intelligence (XAI), anomaly detection and uncertainty techniques for digital pathology
Made Possible By:
