The mechanisms driving Multiple Sclerosis (MS) are still largely unknown, calling for new methods allowing to detect and characterize tissue degeneration since the early stages of the disease. Our aim is to decrypt the microstructural signatures of the Primary Progressive versus the Relapsing-Remitting state of disease based on diffusion and structural MRI data.
|Titolo:||Interpretable Deep Learning as a means for decrypting disease signature in Multiple Sclerosis|
CRUCIANI, FEDERICA (Corresponding)
|Data di pubblicazione:||2021|
|Appare nelle tipologie:||01.01 Articolo in Rivista|