Investigating Reinforcement Learning for Histopathological Image Analysis

Mohamad Mohamad, Francesco Ponzio, Maxime Gassier, Nicolas Pote, Damien Ambrosetti, Xavier Descombes

2025

Abstract

In computational pathology, whole slide images represent the primary data source for AI-driven diagnostic algorithms. However, due to their high resolution and large size, these images undergo a patching phase. In this paper, we approach the diagnostic process from a pathologist’s perspective, modeling it as a Sequential decision-making problem using reinforcement learning. We build a foundational environment designed to support a range of whole slide applications. We showcase its capability by using it to construct a toy goal-conditioned Navigation environment. Finally, we present an agent trained within this environment and provide results that emphasize both the promise of reinforcement learning in histopathology and the distinct challenges it faces.

Paper Citation

in Harvard Style

Mohamad M., Ponzio F., Gassier M., Pote N., Ambrosetti D. and Descombes X. (2025). Investigating Reinforcement Learning for Histopathological Image Analysis. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING; ISBN 978-989-758-731-3, SciTePress, pages 369-375. DOI: 10.5220/0013300900003911

in Bibtex Style

@conference{bioimaging25,
author={Mohamad Mohamad and Francesco Ponzio and Maxime Gassier and Nicolas Pote and Damien Ambrosetti and Xavier Descombes},
title={Investigating Reinforcement Learning for Histopathological Image Analysis},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING},
year={2025},
pages={369-375},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013300900003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING
TI - Investigating Reinforcement Learning for Histopathological Image Analysis
SN - 978-989-758-731-3
AU - Mohamad M.
AU - Ponzio F.
AU - Gassier M.
AU - Pote N.
AU - Ambrosetti D.
AU - Descombes X.
PY - 2025
SP - 369
EP - 375
DO - 10.5220/0013300900003911
PB - SciTePress