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The submission is now open here!

​Computational Pathology is a multidisciplinary field that encompasses the convergence of Digital Pathology, Medical Image Analysis, Computer Vision, and Machine Learning. The vast amount of information contained within multi-gigapixel histopathology images positions digital pathology as an ideal use case for advanced image analysis methods. Consequently, deep learning and artificial intelligence have played a pivotal role in advancing computational pathology research in recent years. Furthermore, the integration of pathology data with other medical examinations holds great promise for enhancing diagnostic accuracy and treatment outcomes.


To explore these possibilities with the MICCAI community, after three editions (2018, 2019, 2021) of workshops in Computational Pathology, this year COMPAY embraces the burgeoning field of multimodaL data with pathology and becomes COMPAYL [kuhm·pile].


With the COMPAYL workshop, we invite researchers to explore the potential of multimodal learning, large language and vision models (LLVMs) in combination with computational pathology. (Articles without multi-modal data are of course welcome too.) See the Call for Papers page for details on the scope of COMPAYL. 

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