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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. 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. key words: ultrasound, carotid artery, detection, support vector machine, local binary patterns

Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features