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. © 2013 Springer International Publishing.
CITATION STYLE
Kawai, F., Hayata, K., Ohmiya, J., Kondo, S., Ishikawa, K., & Yamamoto, M. (2013). Fully automatic detection of the carotid artery from volumetric ultrasound images using anatomical position-dependent LBP features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8184 LNCS, pp. 41–48). Springer Verlag. https://doi.org/10.1007/978-3-319-02267-3_6
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