Common Carotid Artery Lumen Segmentation in B-mode Ultrasound Transverse View Images
Author(s) -
Xin Yang,
Mingyue Ding,
Liantang Lou,
Ming Yuchi,
Wu Qiu,
Yue Sun
Publication year - 2011
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2011.05.03
Subject(s) - segmentation , lumen (anatomy) , transverse plane , canny edge detector , ultrasound , common carotid artery , artificial intelligence , computer vision , histogram , image segmentation , computer science , biomedical engineering , carotid arteries , mathematics , radiology , medicine , edge detection , image processing , surgery , image (mathematics)
To evaluate atherosclerosis, common carotid artery (CCA) lumen segmentation requires outlining the intima contour on transverse view of B-mode ultrasound images. The lumen contours are automatically segmented using a morphology method in this paper. The proposed method is based on self-adaptive histogram equalization, non-linear filtering, Canny edge detector and morphology methods. Experiments demonstrated that the merit (FOM) value of lumen segmentation is 0.705. The comparison between proposed method and manual contours on 180 transverse images of the CCA showed a mean absolute error of 0.47±0.13 mm and mean max distance of 2.08± 0.63 mm respectively. These results compare favorably with a clinical need for reducing use variability.
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