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

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish
Title of host publicationThe Era of Interactive Media
PublisherSpringer New York
Pages303-312
Number of pages10
Volume9781461435013
ISBN (Electronic)9781461435013
ISBN (Print)1461435005, 9781461435006
DOIs
Publication statusPublished - 2013 Oct 1

Fingerprint

Electron energy levels
Ultrasonics
Surface roughness

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

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. In The Era of Interactive Media (Vol. 9781461435013, pp. 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. Vol. 9781461435013 Springer New York, 2013. pp. 303-312
@inbook{31e0b1c401cf47dfa2acdee7b9084f46,
title = "A novel 2D wavelet level energy for breast lesion classification on ultrasound images",
abstract = "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.",
author = "Liao, {Yueh Ching} and Hung, {King Chu} and Shu-Mei Guo and Wang, {Po Chin} and Yang, {Tsung Lung}",
year = "2013",
month = "10",
day = "1",
doi = "10.1007/978-1-4614-3501-3_25",
language = "English",
isbn = "1461435005",
volume = "9781461435013",
pages = "303--312",
booktitle = "The Era of Interactive Media",
publisher = "Springer New York",
address = "United States",

}

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. in The Era of Interactive Media. vol. 9781461435013, Springer New York, pp. 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. Vol. 9781461435013 Springer New York, 2013. p. 303-312.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - A novel 2D wavelet level energy for breast lesion classification on ultrasound images

AU - Liao, Yueh Ching

AU - Hung, King Chu

AU - Guo, Shu-Mei

AU - Wang, Po Chin

AU - Yang, Tsung Lung

PY - 2013/10/1

Y1 - 2013/10/1

N2 - 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.

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.

UR - http://www.scopus.com/inward/record.url?scp=84929547487&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84929547487&partnerID=8YFLogxK

U2 - 10.1007/978-1-4614-3501-3_25

DO - 10.1007/978-1-4614-3501-3_25

M3 - Chapter

AN - SCOPUS:84929547487

SN - 1461435005

SN - 9781461435006

VL - 9781461435013

SP - 303

EP - 312

BT - The Era of Interactive Media

PB - Springer New York

ER -

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