Introduction

The COMPAYL workshop will be held at MICCAI 2024 in Marrakech, Morocco on October 7th.

​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.

Important Dates

• Paper submission deadline: June 24th

• Paper decision notification: July 15th

• Day of the workshop: October 6th

Call for Papers

COMPAYL emphasizes multimodal image analysis with a focus on computational pathology. We seek papers that cover multimodal image analysis, but always with a focus on computational pathology Submissions unrelated to computational pathology or histopathology will be deemed out of scope.

Topics of interest include, but are not limited to:

• Artificial intelligence and foundation models for multimodal data analysis, including pathology.

• Integration of digital pathology with genomics, radiology, and textual data.

• Advances in spatial transcriptomics and whole-slide image analysis.

• Techniques for stain normalization, tissue structure segmentation, and image registration.

• Developments in immunohistochemistry scoring, including multiplexing.

• Innovations in local and cloud-based analysis tools.

• Research on predictive and prognostic tissue biomarkers.

• Strategies for integrating and validating computational pathology in clinical workflows.

Organizing Committee

Francesco Ciompi, Radboud University Medical Center (Netherlands)

Nadieh Khalili, Radboud University Medical Center, Nijmegen (Netherlands)

Linda Studer, Radboud University Medical Center (Netherlands)

Milda Poceviciute, Linköping University (Sweden) and Radboud University Medical Center (Netherlands)

Amjad Khan, University of Bern (Switzerland)

Mitko Veta, Eindhoven University of Technology (Netherlands)

Yiping Jiao, Nanjing University of Information Science and Technology (China)

Neda Haj-Hosseini, Linköping University (Sweden)

Hao Chen, The Hong Kong University of Science and Technology (Hong Kong)

Shan Raza and Fayyaz Minhas, University of Warwick (UK)

Program Committee

Inti Zlobec, University of Bern (Switzerland)

Nikolay Burlutskiy, AstraZeneca (UK)

Veronica Vilaplana, Universitat Politècnica de Catalunya (Spain)

Biagio Brattoli, Lunit.io (South Korea)

Henning Muller, HES-SO (Switzerland)

Manfredo Atzori, University of Padova (Italy)

Shan Raza, University of Warwick (UK)

Fayyaz Minhas, University of Warwick (UK)

For more information, please visit the COMPAYL website.