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Investigation of brain tissue segmentation error and its effect on EEG source localization

Yazdan Shirvany (Institutionen för signaler och system, Signalbehandling) ; Antonio Reyes Porras Péres (Institutionen för signaler och system) ; Koushyar Kowkabzadeh (Institutionen för signaler och system) ; Mahmood Qaiser (Institutionen för signaler och system, Biomedicinsk elektromagnetik) ; Hoi Shun Lui (Institutionen för signaler och system, Biomedicinsk elektromagnetik) ; Mikael Persson (Institutionen för signaler och system, Signalbehandling)
34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012, San Diego, CA, 28 August - 1 September 2012 (1557-170X). p. 1522-1525. (2012)
[Konferensbidrag, refereegranskat]

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.

Nyckelord: Brain segmentation, Brain tissue, Clinical situations, EEG source localization, Epileptic foci, Head model, Human head model, Noninvasive methods, Source localization, Surgical therapy

Denna post skapades 2013-01-08. Senast ändrad 2016-07-19.
CPL Pubid: 169568


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Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)
Institutionen för signaler och system (1900-2017)
Institutionen för signaler och system, Biomedicinsk elektromagnetik (2006-2017)



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Unsupervised Segmentation of Head Tissues from Multi-Modal Magnetic Resonance Images: With Application to EEG Source Localization and Stroke Detection