ResectVol: A tool to automatically segment and characterize lacunas in brain images-Reference-Cited by-同舟云学术

ResectVol: A tool to automatically segment and characterize lacunas in brain images

Published:2021-10-12 Issue:4 Volume:6 Page:720-726
ISSN:2470-9239
Container-title:Epilepsia Open
language:en
Short-container-title:Epilepsia Open

Author:

Casseb Raphael F.¹^ORCID,Campos Brunno M.¹^ORCID,Morita‐Sherman Marcia²^ORCID,Morsi Amr²^ORCID,Kondylis Efstathios²^ORCID,Bingaman William E.²,Jones Stephen E.²,Jehi Lara²^ORCID,Cendes Fernando¹^ORCID

Affiliation:

1. Neuroimaging Laboratory Department of Neurology University of Campinas Campinas Brazil

2. Epilepsy Center Cleveland Clinic Foundation Cleveland Ohio USA

Funder

Foundation for the National Institutes of Health

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Wiley

Subject

Neurology (clinical),Neurology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/epi4.12546

Reference17 articles.

1. The current place of epilepsy surgery

2. Development and validation of nomograms to provide individualised predictions of seizure outcomes after epilepsy surgery: a retrospective analysis

3. Epidemiology of the epilepsies.

4. A Randomized, Controlled Trial of Surgery for Temporal-Lobe Epilepsy

5. Predicting seizure freedom after epilepsy surgery, a challenge in clinical practice

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4. Indirect structural changes and reduced controllability after temporal lobe epilepsy resection;Epilepsia;2024-01-19

5. Fully automatic segmentation of brain lacunas resulting from resective surgery using a 3D deep learning model;2023-11-17