Bio Image Analysis.ORG

Description :

Histological image analysis plays a crucial role in cancer diagnosis and prognosis, yet pixel-based analysis methods often lack interpretability and struggle to capture complex relationships among entities within tissues. This project focuses on introducing a novel approach that shifts from pixel-based analysis to entity-based analysis in histology, leveraging Graph Neural Networks (GNNs) to provide interpretable insights and enhanced control over biological priors

Pré-requis : Deep learning (Pytorch), Basic knowledge of graph theory

Travail demandé : After conducting a state-of-the-art review on graph neural networks, the student will develop and train a pipeline for classifying tumor malignancy using extracted biological entities to create a knowledge graph. The performance of this approach will be evaluated against baseline pixel-based methods. Additionally, the student will explore visualization and interpretability techniques.