A novel 2D wavelet level energy for breast lesion classification on ultrasound images

Yueh Ching Liao, King Chu Hung, Shu-Mei Guo, Po Chin Wang, Tsung Lung Yang

研究成果: Chapter

摘要

Infiltrative nature is a unique characteristic of breast cancer. Cross-sectional view of infiltrative nature can find a rough lesion contour on ultrasound image. Roughness description is crucial for clinical diagnosis of breast lesions. Based on boundary tracking, traditional roughness descriptors usually suffer from information loss due to dimension reduction. In this paper, a novel 2-D wavelet-based energy feature is proposed for breast lesion classification on ultrasound images. This approach characterizes the roughness of breast lesion contour with normalized spatial frequency components. Feature efficacies are evaluated by using two breast sonogram datasets with lesion contour delineated by an experienced physician and the ImageJ, respectively. Experimental results show that the new feature can obtain excellent performance and robust contour variation resistance.

原文English
主出版物標題The Era of Interactive Media
發行者Springer New York
頁面303-312
頁數10
9781461435013
ISBN(電子)9781461435013
ISBN(列印)1461435005, 9781461435006
DOIs
出版狀態Published - 2013 十月 1

指紋

Electron energy levels
Ultrasonics
Surface roughness

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

引用此文

Liao, Y. C., Hung, K. C., Guo, S-M., Wang, P. C., & Yang, T. L. (2013). A novel 2D wavelet level energy for breast lesion classification on ultrasound images. 於 The Era of Interactive Media (卷 9781461435013, 頁 303-312). Springer New York. https://doi.org/10.1007/978-1-4614-3501-3_25
Liao, Yueh Ching ; Hung, King Chu ; Guo, Shu-Mei ; Wang, Po Chin ; Yang, Tsung Lung. / A novel 2D wavelet level energy for breast lesion classification on ultrasound images. The Era of Interactive Media. 卷 9781461435013 Springer New York, 2013. 頁 303-312
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Liao, YC, Hung, KC, Guo, S-M, Wang, PC & Yang, TL 2013, A novel 2D wavelet level energy for breast lesion classification on ultrasound images. 於 The Era of Interactive Media. 卷 9781461435013, Springer New York, 頁 303-312. https://doi.org/10.1007/978-1-4614-3501-3_25

A novel 2D wavelet level energy for breast lesion classification on ultrasound images. / Liao, Yueh Ching; Hung, King Chu; Guo, Shu-Mei; Wang, Po Chin; Yang, Tsung Lung.

The Era of Interactive Media. 卷 9781461435013 Springer New York, 2013. p. 303-312.

研究成果: Chapter

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AB - Infiltrative nature is a unique characteristic of breast cancer. Cross-sectional view of infiltrative nature can find a rough lesion contour on ultrasound image. Roughness description is crucial for clinical diagnosis of breast lesions. Based on boundary tracking, traditional roughness descriptors usually suffer from information loss due to dimension reduction. In this paper, a novel 2-D wavelet-based energy feature is proposed for breast lesion classification on ultrasound images. This approach characterizes the roughness of breast lesion contour with normalized spatial frequency components. Feature efficacies are evaluated by using two breast sonogram datasets with lesion contour delineated by an experienced physician and the ImageJ, respectively. Experimental results show that the new feature can obtain excellent performance and robust contour variation resistance.

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Liao YC, Hung KC, Guo S-M, Wang PC, Yang TL. A novel 2D wavelet level energy for breast lesion classification on ultrasound images. 於 The Era of Interactive Media. 卷 9781461435013. Springer New York. 2013. p. 303-312 https://doi.org/10.1007/978-1-4614-3501-3_25