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

摘要

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.