DocumentCode
683771
Title
Pattern analysis of imaging markers in abdominal aortic aneurysms
Author
Pham, Tuan D. ; Golledge, Jonathan
Author_Institution
Center for Adv. Inf. Sci. & Technol., Univ. of Aizu, Aizu-wakamatsu, Japan
fYear
2013
fDate
16-18 Dec. 2013
Firstpage
154
Lastpage
159
Abstract
Abdominal aortic aneurysm is a serious vascular disease, which is the progressive dilation of the abdominal aorta caused by the weakening of the aortic wall. Its rupture has been known as a significant cause of mortality for adults older than sixty-five years of age. Screening and assessment of abdominal aortic aneurysms are currently performed by either ultrasound or computed tomography, with the latter technology being the current gold standard. Each abdominal aortic aneurysm is different having varying percentage of size, thrombus, and calcification. These imaging markers play a critical role in determining rupture risk and therefore management of treatment. We propose here a novel application of a nonlinear dynamical model and stochastic pattern classification of abdominal aortic aneurysm imaging markers for rupture risk prediction on computed tomography scans.
Keywords
biomechanics; cardiovascular system; computerised tomography; diseases; fracture; medical image processing; nonlinear dynamical systems; pattern classification; physiological models; stochastic processes; abdominal aortic aneurysm imaging markers; calcification percentage variation; computed tomography scans; nonlinear dynamical model; rupture risk prediction; size percentage variation; stochastic pattern classification; thrombus percentage variation; ultrasound; vascular disease; Aneurysm; Biomedical imaging; Computed tomography; Hidden Markov models; Image segmentation; Stochastic processes; Abdominal aortic aneurysm; computed tomography; imaging markers; nonlinear dynamics; pattern classification; stochastic modeling; vascular disease;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics (BMEI), 2013 6th International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-2760-9
Type
conf
DOI
10.1109/BMEI.2013.6746925
Filename
6746925
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