Detection of Artery Regions in Lower Extremity Arteries from Non-Enhanced MR Imaging Based on Particle Filter Algorithms

Autor:	Akiyoshi Yamamoto, Seiji Ishikawa, Hyoungseop Kim, Yuiko Koga, Joo Kooi Tan
Rok vydání:	2013
Předmět:	Human-Computer Interaction medicine.anatomical_structure Artificial Intelligence Computer science medicine Computer Vision and Pattern Recognition Mr images Particle filter Mr imaging Biomedical engineering Artery
Zdroj:	Journal of Advanced Computational Intelligence and Intelligent Informatics. 17:318-323
ISSN:	1883-8014 1343-0130
Popis:	Recently, the arteries sclerosis obliterans (ASO) or called peripheral arterial disease (PAD) typically caused by chronic ischemia of limbs increases remarkably. As one of the diagnosis methods, the image diagnosis methods such as MR image are applied in medical fields. In this paper, we propose a vascular extraction method using fresh blood imaging (FBI) method, as well as apply it to computer aided diagnosis (CAD) system. Especially, to prevent the spread outside of the region and improve the segment accuracy of peripheral artery areas, we introduce particle filter algorithms. We performed our method on automatic artery regions detection using non-enhanced MR images. Furthermore, we compared the extracted results to gold standard data and analyzed accuracy by receiver operating characteristic (ROC). The effectiveness of our proposed method and satisfactory of its detected accuracy were confirmed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3fc8493b588dc9ff3ecc014b75eeb30e https://doi.org/10.20965/jaciii.2013.p0318 Zobrazit plný text záznamu