Computational Pathology embodies the synergy of Digital Pathology, Medical Image Analysis, Computer Vision, and Machine Learning.
The huge amount of information and data available in multi-gigapixel histopathology images makes digital pathology the perfect use case for advanced image analysis techniques. For this reason, deep learning and artificial intelligence have successfully powered computational pathology research in recent years.
COMPAY is the second MICCAI workshop on Computational Pathology.
This full-day workshop aims to bring together scientific researchers, medical experts and industry partners working in the field of computational pathology, in order to push further innovative and clinically relevant solutions for digital pathology. We aim at providing a platform for scientific discussion on computational pathology with a focus on (but not limited to) artificial intelligence and deep learning, which can help foster cooperative projects on an international level.
The scope of the workshop includes, but is not limited to, the following topics:
- Artificial intelligence and Deep Learning for Computational Pathology
- Stain normalization/standardization
- Detection, classification and segmentation of tissue structures (cells, glands etc.)
- Detection and discovery of predictive and prognostic tissue biomarkers
- Whole-slide image analysis
- Registration of whole-slide images
- Immunohistochemistry scoring
- Multiplexed staining
- Unlabeled multiplexing
- Crowdsourcing for ground truth collection and machine learning applications
- Applications of computational pathology in the clinic
The workshop will consist of invited talks, oral and poster presentations of accepted peer-reviewed papers.
We accept submission of 8-page papers containing original research on computational pathology.
Submission deadline: July 18 (Extended deadline)
This year, we are organizing a hackathon on computational pathology in conjunction with the COMPAY workshop. More details about the event can be found in the hackathon website: https://lysto.grand-challenge.org
For questions related to the workshop, send an email to email@example.com