IEICE TRANSACTIONS on Information
Automatic Detection of the Carotid Artery Location from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features
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
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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://global.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},}
Copy
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 -
English
