Zou, P., Chan, P., Rockett, P. (2009) A model-based consecutive scanline tracking method for extracting vascular networks from 2-D digital subtraction angiograms. IEEE Transactions on Medical Imaging, 28 (2). pp. 241-249. ISSN 0278-0062. (doi:10.1109/TMI.2008.929100) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:78330)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1109/TMI.2008.929100 |
Abstract
We propose a new model-based algorithm for the automated tracking of vascular networks in 2-D digital subtraction angiograms. Consecutive scanline profiles are fitted by a parametric Imaging model to estimate local vessel center point, radius, edge locations and direction. An adaptive tracking strategy is applied with appropriate termination criteria to track each vessel segment. When tracking stops, to prevent premature termination and to detect bifurcations, a look ahead detection scheme is used to search for possible continuation points of the same vessel segment or those of its bifurcated segments. The proposed algorithm can automatically extract the majority of the vascular network without human interaction other than initializing the start point and direction. Compared to other tracking methods, the proposed method highlights accurate estimation of local vessel geometry. Accurate geometric information and a hierarchical vessel network are obtained which can be used for further quantitative analysis of arterial networks to obtain flow conductance estimates.
Item Type: | Article |
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DOI/Identification number: | 10.1109/TMI.2008.929100 |
Uncontrolled keywords: | Nonlinear model fitting, Vascular network modeling, Vessel extraction, Vessel tracking, X-ray angiograms, Nonlinear model fitting, Vascular network modeling, Vessel extraction, Vessel tracking, X-ray angiograms, algorithm, article, biological model, computer assisted diagnosis, digital subtraction angiography, human, image processing, methodology, Monte Carlo method, nonlinear system, Algorithms, Angiography, Digital Subtraction, Humans, Image Processing, Computer-Assisted, Models, Cardiovascular, Monte Carlo Method, Nonlinear Dynamics, Radiographic Image Interpretation, Computer-Assisted |
Divisions: | Divisions > Division of Natural Sciences > Kent and Medway Medical School |
Depositing User: | Philip Chan |
Date Deposited: | 07 Nov 2019 14:36 UTC |
Last Modified: | 14 Dec 2023 04:14 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/78330 (The current URI for this page, for reference purposes) |
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