The growing availability of novel interpretation techniques opened the way to the application of deep learning models in the clinical field, including neuroimaging, where their use is still largely underexploited. In this framework, we focus the stratification of Multiple Sclerosis (MS) patients in the Primary Progressive versus the Relapsing-Remitting state of the disease using a 3D Convolutional Neural Network trained on structural MRI data. Within this task, the application of Layer-wise Relevance Propagation visualization allowed detecting the voxels of the input data mostly involved in the classification decision, potentially bringing to light brain regions which might reveal disease state.
|Titolo:||Explainable 3D-CNN for multiple sclerosis patients stratication|
CRUCIANI, FEDERICA (Corresponding)
|Data di pubblicazione:||2021|
|Appare nelle tipologie:||04.01 Contributo in atti di convegno|