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Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study
Epilepsia ( IF 5.6 ) Pub Date : 2020-06-13 , DOI: 10.1111/epi.16574
Konrad Wagstyl 1 , Sophie Adler 2 , Birgit Pimpel 2 , Aswin Chari 2, 3 , Kiran Seunarine 2 , Sara Lorio 2 , Rachel Thornton 2, 3 , Torsten Baldeweg 2 , Martin Tisdall 2, 3
Affiliation  

This retrospective, cross‐sectional study evaluated the feasibility and potential benefits of incorporating deep‐learning on structural magnetic resonance imaging (MRI) into planning stereoelectroencephalography (sEEG) implantation in pediatric patients with diagnostically complex drug‐resistant epilepsy. This study aimed to assess the degree of colocalization between automated lesion detection and the seizure onset zone (SOZ) as assessed by sEEG.

中文翻译:

使用自动病变检测规划立体脑电图:回顾性可行性研究

这项回顾性、横断面研究评估了将结构磁共振成像 (MRI) 的深度学习纳入诊断为复杂耐药性癫痫儿科患者的立体脑电图 (sEEG) 植入计划中的可行性和潜在益处。本研究旨在评估自动病变检测与通过 sEEG 评估的癫痫发作起始区 (SOZ) 之间的共定位程度。
更新日期:2020-06-13
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