Interpretable deep learning‐based hippocampal sclerosis classification
Abstract Objective To evaluate the performance of a deep learning model for hippocampal sclerosis classification on the clinical dataset and suggest plausible visual interpretation for the model prediction. Methods T2‐weighted oblique coronal images of the brain MRI epilepsy protocol performed on pa...
Main Authors: | Dohyun Kim, Jungtae Lee, Jangsup Moon, Taesup Moon |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-12-01
|
Series: | Epilepsia Open |
Subjects: | |
Online Access: | https://doi.org/10.1002/epi4.12655 |
Similar Items
-
Hippocampal Sclerosis and Febrile Status Epilepticus
by: J Gordon Millichap, et al.
Published: (2014-05-01) -
Hippocampal Malrotation: A Genetic Developmental Anomaly Related to Epilepsy?
by: Ting-Ying Fu, et al.
Published: (2021-04-01) -
Longitudinal hippocampal atrophy in hippocampal sclerosis of aging
by: Janice X. Li, et al.
Published: (2023-01-01) -
Diagnostic Performance of MRI Volumetry in Epilepsy Patients With Hippocampal Sclerosis Supported Through a Random Forest Automatic Classification Algorithm
by: Juan Pablo Princich, et al.
Published: (2021-02-01) -
Hippocampal sclerosis – cause or consequence of mesial temporal lobe epilepsy in children?
by: Adriana Gabriela Albeanu, et al.
Published: (2012-03-01)