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Automatic initialization for active contour model in breast cancer detection utilizing conventional ultrasound and Color Doppler.

Authors :
Keatmanee C
Makhanov SS
Kotani K
Lohitvisate W
Thongvigitmanee SS
Source :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2017 Jul; Vol. 2017, pp. 3248-3251.
Publication Year :
2017

Abstract

Regular examination of breasts may prevent and help to cure because breast cancer is treatable when it is detected early. Therefore, a breast cancer screening modality being sensitivity and cost-effective like ultrasonic imaging modality (US), is strongly required. In addition, the combination of a conventional US and its adjunct, Color Doppler has been proved for decreasing the rate of false-positive in breast cancer diagnosis. Thus, combination of these imaging modalities in a breast cancer segmentation would provide some benefits as well. An effective method for feature segmentation, active contour model has been widely utilized for decades. A crucial stage that affects the performance of active contour model is the initialization. This paper proposes a novel method for an automatic initialization of active contour model designed specifically for US-based imaging modalities. The method estimates an initial contour by utilizing the fusion of conventional US and Color Doppler. Examples and comparisons with three state-of-the-art automatic initialization methods are demonstrated to present the advantages of the proposed method. The evaluation results show high accuracy of initialization as well as fast convergence to features of interest.

Details

Language :
English
ISSN :
2694-0604
Volume :
2017
Database :
MEDLINE
Journal :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Publication Type :
Academic Journal
Accession number :
29060590
Full Text :
https://doi.org/10.1109/EMBC.2017.8037549