TY - JOUR A1 - Mayer, Julius A1 - Baum, Daniel A1 - Ambellan, Felix A1 - von Tycowicz, Christoph A1 - for the Alzheimer’s Disease Neuroimaging Initiative, T1 - Shape-based Disease Grading via Functional Maps and Graph Convolutional Networks with Application to Alzheimer’s Disease JF - BMC Medical Imaging N2 - Shape analysis provides methods for understanding anatomical structures extracted from medical images. However, the underlying notions of shape spaces that are frequently employed come with strict assumptions prohibiting the analysis of incomplete and/or topologically varying shapes. This work aims to alleviate these limitations by adapting the concept of functional maps. Further, we present a graph-based learning approach for morphometric classification of disease states that uses novel shape descriptors based on this concept. We demonstrate the performance of the derived classifier on the open-access ADNI database differentiating normal controls and subjects with Alzheimer’s disease. Notably, the experiments show that our approach can improve over state-of-the-art from geometric deep learning. Y1 - 2024 U6 - https://doi.org/10.1186/s12880-024-01513-z VL - 24 ER -