Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features
We propose a fully automatic method for detecting the carotid artery from volumetric ultrasound images as a preprocessing stage for building three-dimensional images of the structure of the carotid artery. The proposed detector utilizes support vector machine classifiers to discriminate between carotid artery images and non-carotid artery images using two kinds of LBP-based features. The detector switches between these features depending on the anatomical position along the carotid artery. The detector narrows the search area for detection in consideration of the three-dimensional continuity of the carotid artery to suppress false positives and improve processing speed. We evaluate our proposed method using actual clinical cases. Accuracies of detection are 100 %, 87.5 % and 68.8 % for the common carotid artery, internal carotid artery, and external carotid artery sections, respectively. We also confirm that detection can be performed in real time using a personal computer.
KeywordsUltrasound Carotid Artery Detection Support Vector Machine Local Binary Pattern
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- 3.Barratt, D.C., Ariff, B.B., Humphries, K.N., Thom, S.A.Mc.G., Hughes, A.D.: Reconstruction and quantification of the carotid artery bifurcation from 3-D ultrasound images. IEEE Trans. Medical Imaging 23(5), 567–583 (2004)Google Scholar
- 7.Cao, Y., Pranata, S., Yasugi, M., Niu, Z., Nishimura, H.: Staggered multi-scale LBP for pedestrian detection. In: IEEE ICIP, pp. 449–452 (2012)Google Scholar
- 8.Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE CVPR, vol. 1, pp. 886–893 (2005)Google Scholar