Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Oct 7, 2024
Abstract
PURPOSE: This study investigates the application of Radiomic features within graph neural networks (GNNs) for the classification of multiple-epitope-ligand cartography (MELC) pathology samples. It aims to enhance the diagnosis of often misdiagnosed skin diseases such as eczema, lymphoma, and melanoma. The novel contribution lies in integrating Radiomic features with GNNs and comparing their efficacy against traditional multi-stain profiles.