Shirvany Yazdan, Porras Antonio R, Kowkabzadeh Koushyar, Mahmood Qaiser, Lui Hoi-Shun, Persson Mikael
Department of Signals and Systems, Chalmers University of Technology and MedTechWest Center, Göteborg, Sweden.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1522-5. doi: 10.1109/EMBC.2012.6346231.
Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of the epileptic focus, preferably with non-invasive methods, is the main goal of the pre-surgical epilepsy diagnosis to decide if resection of brain tissue is possible. For evaluating the performance of the source localization algorithms in an actual clinical situation, realistic patient-specific human head models that incorporate the heterogeneity nature of brain tissues is required. In this paper, performance of two of the most widely used software packages for brain segmentation, namely FSL and FreeSurfer has been analyzed. Then a segmented head model from a package with better performance is used to investigate the effects of brain tissue segmentation in EEG source localization.
手术治疗已成为药物难治性癫痫患者的一种重要治疗选择。癫痫病灶的准确且解剖学上精确的定位，最好采用非侵入性方法，是术前癫痫诊断的主要目标，以确定是否可行脑组织切除术。为了在实际临床情况下评估源定位算法的性能，需要结合脑组织异质性的真实患者特异性人体头部模型。本文分析了两种最广泛使用的脑部分割软件包，即FSL和FreeSurfer的性能。然后使用来自性能更好的软件包的分割头部模型来研究脑部分割在脑电图源定位中的作用。
