Automatic tracking of the aorta in cardiovascular MR images using deformable models

Presents a new algorithm for the robust and accurate tracking of the aorta in cardiovascular magnetic resonance (MR) images. First, a rough estimate of the location and diameter of the aorta is obtained by applying a multiscale medial-response function using the available a priori knowledge. Then, t...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 1997-10, Vol.16 (5), p.581-590
Main Authors: Rueckert, D., Burger, P., Forbat, S.M., Mohiaddin, R.D., Yang, G.Z.
Format: Article
Language:English
Subjects:
Algorithms
Aorta - anatomy & histology
Aorta - physiology
Automation
Biological and medical sciences
Biomedical imaging
Blood Pressure
Blood vessels
Blood Volume
Cardiology
Cardiovascular system
Compliance
Computer Simulation
Deformable models
Humans
Image Processing, Computer-Assisted
Image segmentation
Investigative techniques, diagnostic techniques (general aspects)
Iterative methods
Magnetic resonance
Magnetic Resonance Imaging
Markov Chains
Mathematical models
Medical imaging
Medical sciences
Models, Cardiovascular
Observer Variation
Optimization methods
Pattern Recognition, Automated
Radiodiagnosis. Nmr imagery. Nmr spectrometry
Reproducibility of Results
Robustness
Robustness (control systems)
Simulated annealing
Stochastic Processes
Vascular Capacitance
Volume measurement
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Description
Summary:Presents a new algorithm for the robust and accurate tracking of the aorta in cardiovascular magnetic resonance (MR) images. First, a rough estimate of the location and diameter of the aorta is obtained by applying a multiscale medial-response function using the available a priori knowledge. Then, this estimate is refined using an energy-minimizing deformable model which the authors define in a Markov-random-field (MRF) framework. In this context, the authors propose a global minimization technique based on stochastic relaxation. Simulated annealing (SA), which is shown to be superior to other minimization techniques, for minimizing the energy of the deformable model. The authors have evaluated the performance and robustness of the algorithm on clinical compliance studies in cardiovascular MR images. The segmentation and tracking has been successfully tested in spin-echo MR images of the aorta. The results show the ability of the algorithm to produce not only accurate, but also very reliable results in clinical routine applications.
ISSN:0278-0062
1558-254X
DOI:10.1109/42.640747