Chapter title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008
|
---|---|
Chapter number | 106 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008
|
Published in |
Lecture notes in computer science, January 2008
|
DOI | 10.1007/978-3-540-85990-1_106 |
Pubmed ID | |
Book ISBNs |
978-3-54-085989-5, 978-3-54-085990-1
|
Authors |
Li, Bo, Young, Alistair A, Cowan, Brett R, Young, Alistair A., Cowan, Brett R., Bo Li, Alistair A. Young, Brett R. Cowan |
Abstract |
We present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (CMR) cines. A GPU accelerated Levenberg-Marquardt non-linear least squares optimization procedure for finite element non-rigid registration was implemented on an NVIDIA graphics card using the OpenGL environment. Points were tracked from frame to frame using forward and backward incremental registration. The inner (endocardial) and outer (epicardial) boarders of the heart were tracked in six short axis cines with approximately 25 frames through the cardiac cycle in 36 patients with vascular disease. Contours placed by two independent expert observers using a semi-automatic ventricular analysis program (CIM version 4.6) were used as the gold standard. The method took 0.5 seconds per frame, and the maximum Hausdorff errors were less than 2 mm on average which was of the same order as the expert inter-observer error. In conclusion, GPU accelerated Levenberg-Marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in CMR images. |
Mendeley readers
Geographical breakdown
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United States | 6 | 16% |
New Zealand | 1 | 3% |
Spain | 1 | 3% |
Norway | 1 | 3% |
Unknown | 28 | 76% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 13 | 35% |
Researcher | 8 | 22% |
Student > Master | 4 | 11% |
Professor | 3 | 8% |
Student > Bachelor | 2 | 5% |
Other | 3 | 8% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 15 | 41% |
Engineering | 8 | 22% |
Agricultural and Biological Sciences | 5 | 14% |
Medicine and Dentistry | 2 | 5% |
Mathematics | 1 | 3% |
Other | 0 | 0% |
Unknown | 6 | 16% |