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Detection and Extraction of Vascular Networks using Hough Transform


Vascular diseases are a main health problem, representing 28% of deaths worldwide and 66% of all diseases affecting the Brazilian population. Thus, it is important that researches in prevention and treatment of this type of disease increase. Moreover, there are several demands, such as computational tools capable of analyzing and extracting attributes from non-invasive images. The scope of this work is the analysis and extraction of data from magnetic resonance angiography and computed tomography angiography images by highlighting blood vessels. In this context, this thesis aims the development of a novel computational tracking and feature extraction method for vascular networks from 3D images. Our approach presents the following steps: First, identify the vessel cross-sections along it using the Hough transform. Then, compute a matrix composed of second order partial derivatives of image intensity to identify the direction of the vessel. Perform a feature analysis of the vessel contour to classify the bifurcation point, and finally, identify the direction of the new branch in a bifurcation point. The main contribution of this Thesis is the two new measures developed, called radius ratio and bifurcation measure, the radius ratio is capable to distinguish between a region with bifurcation, stents or without both of them. The bifurcation measure is a linear combination that allows to classify a region as bifurcation or not. Tests were performed in order to verify the proposed approach effectiveness, using both synthetic images and real images. The results showed the method is capable to track 91% of synthetic vascular networks varying the seed point and 76% varying the level of noise. Also, we performed tests in real images and by visual evaluation, we could observed that the proposed method was able to track vessels and identify bifurcations from different parts of the body. This approach allows to calculate, in the future, the density of bifurcations in a vascular network, the distance between them, the stenosis and aneurysms grading and characterize specific vessels. In addition, the vascular networks extraction allows the study of the angiogenesis phenomena and vascular anomalies.

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August 30, 2012
Auditório Antonio Gilioli, bloco A 
Cidade Universitária
São Paulo
Maysa Malfiza Garcia de Macedo
Prof. Dr. Jackowski, Marcel Parolin
Theses USP
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