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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25086

Title: CT-based Automatic Identification and Localization of the Right Phrenic Nerve
Authors: Bamps, Kobe
Cuypers, Céline
Claesen, Luc
Koopman, Pieter
Issue Date: 2017
Publisher: IEEE
Citation: Wang, Lipo; Zhou, Mei; Sun, Li; Qiu, Song; Liu, Hongying (Ed.). Proceedings 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics CISP-BMEI 2017, IEEE,p. 4B-1-4B-6
Status: In Press
Abstract: Atrial fibrillation is a cardiac arrhythmia that causes irregular contraction of the atria. It is caused by parasitic electric signals via the pulmonary veins. Current treatment methods involve point-by-point RF ablation, cryoablation or laser balloon ablation. Ablation creates a circumferential lesion resulting in an electrical isolation of the pulmonary veins, thereby disabling the parasitic signals causing atrial fibrillation. During ablation there is a danger that the right phrenic nerve (PN) is damaged, having a serious impact on the respiratory capability of the patient. This paper presents new automatic image processing methods and algorithms to identify and localize the right phrenic nerve starting from high quality CT scans. Nerve tissue is nearly undetectable from CT scan images. To select the most probable locations of PN candidates, a new algorithm: EXSAC is proposed. Based on CT scans of 27 test cases, the PN could be automatically identified in 89% of the cases, in comparison to the manual localization by a heart surgeon.
URI: http://hdl.handle.net/1942/25086
ISBN: 9781538619360
Category: C1
Type: Proceedings Paper
Appears in Collections: Research publications

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