COMPAYL 2024

Computational Pathology is a multidisciplinary field encompassing the convergence of Digital Pathology, Medical Image Analysis, Computer Vision, and Machine Learning. The vast amount of information in 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 invited researchers to explore the potential of multimodal learning, large language and vision models (LLVMs) in combination with computational pathology. We published all accepted papers on Proceedings of Machine Learning Research, which you can find here. All accepted papers can also be found on OpenReview here.