A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis

A generalized deep learning network for fractional anisotropy reconstruction: Application to epilepsy and multiple sclerosis

Fractional anisotropy (FA) is a quantitative map sensitive to microstructural properties of tissues in vivo and it is extensively used to study the healthy and pathological brain. This map is classically calculated by model fitting (standard method) and requires many diffusion weighted (DW) images f...

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Bibliographic Details
Main Authors: Marta Gaviraghi, Antonio Ricciardi, Fulvia Palesi, Wallace Brownlee, Paolo Vitali, Ferran Prados, Baris Kanber, Claudia A. M. Gandini Wheeler-Kingshott
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Neuroinformatics
Subjects:
deep learning
fractional anisotropy
diffusion weighted MRI
reduced acquisition time
temporal lobe epilepsy
multiple sclerosis
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2022.891234/full

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https://www.frontiersin.org/articles/10.3389/fninf.2022.891234/full

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