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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 | Source: | 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 | 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. | Keywords: | phrenic nerve; atrial fibrillation; pulmonary vein isolation; laser balloon ablation; cardiac arrythmia; DICOM, CT scan; medical image processing; RANSAC | Document URI: | http://hdl.handle.net/1942/25086 | ISBN: | 9781538619377 | DOI: | 10.1109/CISP-BMEI.2017.8302179 | ISI #: | 000464407100280 | Rights: | 2017 IEEE | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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P1715 CT-Based Automatic Identification and Localization of the Right Phrenic Nerve.pdf Restricted Access | Peer-reviewed author version | 840.48 kB | Adobe PDF | View/Open Request a copy |
bamps2017.pdf Restricted Access | Published version | 1.49 MB | Adobe PDF | View/Open Request a copy |
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