Conference proceeding
Vascular MR segmentation: wall and plaque
Proceedings of SPIE, Vol.5032(1), pp.1667-1675
Medical Imaging 2003: Image Processing
05/16/2003
DOI: 10.1117/12.481147
Abstract
Cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability is needed to allow institution of preventive measures before heart attack or stroke occur. A computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images is reported. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from 6 vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were -0.12±0.14 mm, 0.04±0.12mm, and -0.15±0.13 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Details
- Title: Subtitle
- Vascular MR segmentation: wall and plaque
- Creators
- Fuxing Yang - Univ. of Iowa (USA)Gerhard Holzapfel - Technishe Univ. Graz (Austria)Christian Schulze-Bauer - Technishe Univ. Graz (Austria)Rudolf Stollberger - Karl-Franzens-Univ. Graz (Austria)Daniel Thedens - Univ. of Iowa (USA)Lizann Bolinger - Univ. of Iowa (USA)Alan Stolpen - Univ. of Iowa (USA)Milan Sonka - Univ. of Iowa (USA)
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5032(1), pp.1667-1675
- Conference
- Medical Imaging 2003: Image Processing
- DOI
- 10.1117/12.481147
- ISSN
- 0277-786X
- Language
- English
- Date published
- 05/16/2003
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984047982602771
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