Vessel tractography using an intensity based tensor model

Çetin, Süheyla (2011) Vessel tractography using an intensity based tensor model. [Thesis]

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In the last decade, CAD (Coronary Artery Disease) has been the leading cause of death worldwide [1]. Extraction of arteries is a crucial step for accurate visualization, quantification, and tracking of pathologies. However, coronary artery segmentation is one of the most challenging problems in medical image analysis, since arteries are complex tubular structures with bifurcations, and have possible pathologies. Moreover, appearance of blood vessels and their geometry can be perturbed by stents, calcifications and pathologies such as stenosis. Besides, noise, contrast and resolution artifacts can make the problem more challenging. In this thesis, we present a novel tubular structure segmentation method based on an intensity-based tensor that fits to a vessel, which is inspired from diffusion tensor image (DTI) modeling. The anisotropic tensor inside the vessel drives the segmentation analogously to a tractography approach in DTI. Our model is initialized with a single seed point and it is capable of capturing whole vessel tree by an automatic branch detection algorithm. The centerline of the vessel as well as its thickness is extracted. We demonstrate the performance of our algorithm on 3 complex tubular structured synthetic datasets, and on 8 CTA (Computed Tomography Angiography) datasets (from Rotterdam Coronary Artery Algorithm Evaluation Framework) for quantitative validation. Additionally, extracted arteries from 10 CTA volumes are qualitatively evaluated by a cardiologist expert's visual scores.
Item Type: Thesis
Uncontrolled Keywords: Segmentation. -- CTA.-- Tubular structures. -- Branch detection. -- Vessel trees. -- Coronary arteries. -- Tensor estimation. -- Tractography. -- Tensor. -- Bölütleme. -- BTA. -- Borumsu yapılar. -- Dallanma algılama. -- Damar ağaçları. -- Koroner arterler. -- Tensör tahmini. -- Traktografi. -- Tensör.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Electronics
Faculty of Engineering and Natural Sciences
Depositing User: IC-Cataloging
Date Deposited: 18 Mar 2015 09:37
Last Modified: 26 Apr 2022 10:04

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