Generation of Counterfactual Pathology Images for Observing Changes in Cellular Tissues with Cancerization Using Diffusion Models

Abstract

This paper describes the study of generating counterfactual pathology images for observing changes in cellular tissues associated with cancerization. Malignant lymphoma has more than 70 subtypes, and in the pathological diagnosis, a pathological image is observed to identify the subtype. Currently, there are no quantitative criteria for subtype identification, and pathologists conduct qualitative diagnoses based on their experience and intuition. Such qualitative diagnosis makes it difficult to guarantee diagnostic reproducibility, and it is desirable to develop quantitative criteria for subtype identification. Toward achieving diagnosis based on quantitative criteria, this study has tackled the generation of counterfactual pathology images using diffusion models, thereby visualizing changes in cellular tissues associated with cancerization. This paper describes the study of generating counterfactual pathology images by drawing on multiple reference papers.