Presentation 2015-03-03
A Study on Lesion Detection from Breast Ultrasound Images Based on Difference of Texture Change between Adjacent Regions
Yudai YAMAZAKI, Masaya IWATA, Hirokazu NOSATO, Eiichi TAKAHASHI, Hidenori SAKANASHI,
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Abstract(in English) In this paper, we propose a novel lesion detection method for breast ultrasound images. In breast ultrasound images, the change pattern of the lesion texture is different from the breast tissue. The proposed method detects a lesion on the basis of the difference in the change of texture in the focused region and the adjacent region. We demonstrate lesion detection in breast ultrasound images using proposed method, and confirmed effectiveness of the method
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Keyword(in English) Ultrasound Image / Computer Aided Detection / Lesion Detection / Abnormal Detection
Paper # MI2014-111
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Committee MI
Conference Date 2015/2/23(1days)
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Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Lesion Detection from Breast Ultrasound Images Based on Difference of Texture Change between Adjacent Regions
Sub Title (in English)
Keyword(1) Ultrasound Image
Keyword(2) Computer Aided Detection
Keyword(3) Lesion Detection
Keyword(4) Abnormal Detection
1st Author's Name Yudai YAMAZAKI
1st Author's Affiliation Graduate School of Systems and Information Engineering University of Tsukuba()
2nd Author's Name Masaya IWATA
2nd Author's Affiliation Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology
3rd Author's Name Hirokazu NOSATO
3rd Author's Affiliation Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology
4th Author's Name Eiichi TAKAHASHI
4th Author's Affiliation Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology
5th Author's Name Hidenori SAKANASHI
5th Author's Affiliation Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology
Date 2015-03-03
Paper # MI2014-111
Volume (vol) vol.114
Number (no) 482
Page pp.pp.-
#Pages 6
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