title: Segmentation of wall and plaque in in vitro vascular MR images.
abstract: Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. 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 six 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 -0.1 +/- 0.1, 0.0 +/- 0.1, and -0.1 +/- 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
authors: Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA.
authors: Fuxing
authors: F
authors: Yang
authors: Gerhard
authors: G
authors: Holzapfel
authors: Christian
authors: C
authors: Schulze-Bauer
authors: Rudolf
authors: R
authors: Stollberger
authors: Daniel
authors: D
authors: Thedens
authors: Lizann
authors: L
authors: Bolinger
authors: Alan
authors: A
authors: Stolpen
authors: Milan
authors: M
authors: Sonka
mesh_terms: D001161:Arteriosclerosis / Q000000981:diagnostic imaging / Q000473:pathology; D005263:Femoral Artery / Q000000981:diagnostic imaging* / Q000473:pathology*; D006801:Humans; D007083:Iliac Artery / Q000000981:diagnostic imaging* / Q000473:pathology*; D008279:Magnetic Resonance Imaging; D011856:Radiographic Image Enhancement; D012044:Regression Analysis; D017539:Tunica Intima / Q000000981:diagnostic imaging* / Q000473:pathology*