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

Fumi KAWAI; Satoshi KONDO; Keisuke HAYATA; Jun OHMIYA; Kiyoko ISHIKAWA; Masahiro YAMAMOTO

doi:10.1587/transinf.2014EDP7359

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

Fumi KAWAI, Satoshi KONDO, Keisuke HAYATA, Jun OHMIYA, Kiyoko ISHIKAWA, Masahiro YAMAMOTO

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Summary :

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.

Publication: IEICE TRANSACTIONS on Information Vol.E98-D No.7 pp.1353-1364

Publication Date: 2015/07/01

Publicized: 2015/04/13

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2014EDP7359

Type of Manuscript: PAPER

Category: Image Recognition, Computer Vision

Authors

Fumi KAWAI
  Panasonic Healthcare Co., Ltd.
Satoshi KONDO
  Panasonic Healthcare Co., Ltd.
Keisuke HAYATA
  Panasonic Healthcare Co., Ltd.
Jun OHMIYA
  Panasonic Healthcare Co., Ltd.
Kiyoko ISHIKAWA
  Yokohama Stroke and Brain Center
Masahiro YAMAMOTO
  Yokohama Stroke and Brain Center

Keyword

ultrasound, carotid artery, detection, support vector machine, local binary patterns

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Fumi KAWAI, Satoshi KONDO, Keisuke HAYATA, Jun OHMIYA, Kiyoko ISHIKAWA, Masahiro YAMAMOTO, "Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features" in IEICE TRANSACTIONS on Information, vol. E98-D, no. 7, pp. 1353-1364, July 2015, doi: 10.1587/transinf.2014EDP7359.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2014EDP7359/_p

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@ARTICLE{e98-d_7_1353,
author={Fumi KAWAI, Satoshi KONDO, Keisuke HAYATA, Jun OHMIYA, Kiyoko ISHIKAWA, Masahiro YAMAMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features},
year={2015},
volume={E98-D},
number={7},
pages={1353-1364},
abstract={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.},
keywords={},
doi={10.1587/transinf.2014EDP7359},
ISSN={1745-1361},
month={July},}

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TY - JOUR
TI - Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features
T2 - IEICE TRANSACTIONS on Information
SP - 1353
EP - 1364
AU - Fumi KAWAI
AU - Satoshi KONDO
AU - Keisuke HAYATA
AU - Jun OHMIYA
AU - Kiyoko ISHIKAWA
AU - Masahiro YAMAMOTO
PY - 2015
DO - 10.1587/transinf.2014EDP7359
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2015
AB - 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.
ER -