Deep learning for the diagnosis of mesial temporal lobe epilepsy.

ABSTRACT:

Objective

This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracies of AI and neurosurgical physicians for MTLE with the hippocampus as the epileptogenic area.

Method

In this study, we used an AI program to diagnose MTLE. The image sets were processed using a code written in Python 3.7.4. and analyzed using Open Computer Vision 4.5.1. The deep learning model, which was a fine-tuned VGG16 model, consisted of several layers. The diagnostic accuracies of AI and board-certified neurosurgeons were compared.

Results

AI detected the hippocampi automatically and diagnosed MTLE with the hippocampu

SUBMITTER: Sakashita K 

PROVIDER: S-EPMC9949622 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature