The multidisciplinary domain 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.
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 at an international level.
COMPAY 2021 includes, but is not limited to, the following topics:
- Artificial intelligence and Deep Learning for Computational Pathology
- 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
COMPAY 2021 will be held virtually.
The workshop will consist of invited talks, oral and poster presentations of accepted peer-reviewed papers.
Accepted papers will be published in the open-access Proceedings of Machine Learning Research.
We also welcome submissions of open-source software, which will be demoed during the workshop.
At the end of the day, we will organize a panel discussion on the present and the future of computational pathology.