Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.

ABSTRACT:

Objective

Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients.

Methods

A total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then

SUBMITTER: Luckett PH 

PROVIDER: S-EPMC9177812 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature