Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images

Chung Ming Lo, R. F. Chang, C. S. Huang, Wookyung Moon

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2 Citations (Scopus)

Abstract

The malignancy of breast tumors are evaluated via ultrasound images on clinical examination. As a second viewer, a computer-aided diagnosis (CAD) system was developed to classify the breast tumors using texture features to avoid misclassifying carcinomas. A total of 69 cases including 21 malignant and 48 benign masses were acquired. For intensity- invariant texture extraction, the ultrasound images were first transformed into ranklet images to reduce the effect of brightness variability. From the ranklet images, tumor texture and speckle texture were extracted and compared to those from the original ultrasound images for tumor diagnosis. In the trade-offs between sensitivity and specificity, the rankletbased tumor texture and speckle texture were all significantly better than those of the original US images (Az: 0.83 vs. 0.58, p-value=0.0009 and Az=0.80 vs. 0.56, p-value=0.02). The proposed CAD system using textures from intensity transformed sonographic images is robust to various gray-scale distributions and is more suitable in clinical use.

Original languageEnglish
Title of host publication1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering
EditorsShyh-Hau Wang, Fong-Chin Su, Ming-Long Yeh
PublisherSpringer Verlag
Pages124-127
Number of pages4
ISBN (Electronic)9783319122618
DOIs
StatePublished - 1 Jan 2015
Event1st Global Conference on Biomedical Engineering, GCBME 2014 and 9th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2014 - Tainan, Taiwan, Province of China
Duration: 9 Oct 201412 Oct 2014

Publication series

NameIFMBE Proceedings
Volume47
ISSN (Print)1680-0737

Other

Other1st Global Conference on Biomedical Engineering, GCBME 2014 and 9th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2014
CountryTaiwan, Province of China
CityTainan
Period9/10/1412/10/14

Fingerprint

Computer aided diagnosis
Tumors
Textures
Ultrasonics
Speckle
Luminance

Keywords

  • Breast cancer
  • Computer-aided diagnosis
  • Texture
  • Ultrasound

Cite this

Lo, C. M., Chang, R. F., Huang, C. S., & Moon, W. (2015). Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images. In S-H. Wang, F-C. Su, & M-L. Yeh (Eds.), 1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering (pp. 124-127). (IFMBE Proceedings; Vol. 47). Springer Verlag. https://doi.org/10.1007/978-3-319-11128-5_35
Lo, Chung Ming ; Chang, R. F. ; Huang, C. S. ; Moon, Wookyung. / Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images. 1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering. editor / Shyh-Hau Wang ; Fong-Chin Su ; Ming-Long Yeh. Springer Verlag, 2015. pp. 124-127 (IFMBE Proceedings).
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Lo, CM, Chang, RF, Huang, CS & Moon, W 2015, Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images. in S-H Wang, F-C Su & M-L Yeh (eds), 1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering. IFMBE Proceedings, vol. 47, Springer Verlag, pp. 124-127, 1st Global Conference on Biomedical Engineering, GCBME 2014 and 9th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2014, Tainan, Taiwan, Province of China, 9/10/14. https://doi.org/10.1007/978-3-319-11128-5_35

Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images. / Lo, Chung Ming; Chang, R. F.; Huang, C. S.; Moon, Wookyung.

1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering. ed. / Shyh-Hau Wang; Fong-Chin Su; Ming-Long Yeh. Springer Verlag, 2015. p. 124-127 (IFMBE Proceedings; Vol. 47).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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AU - Moon, Wookyung

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Y1 - 2015/1/1

N2 - The malignancy of breast tumors are evaluated via ultrasound images on clinical examination. As a second viewer, a computer-aided diagnosis (CAD) system was developed to classify the breast tumors using texture features to avoid misclassifying carcinomas. A total of 69 cases including 21 malignant and 48 benign masses were acquired. For intensity- invariant texture extraction, the ultrasound images were first transformed into ranklet images to reduce the effect of brightness variability. From the ranklet images, tumor texture and speckle texture were extracted and compared to those from the original ultrasound images for tumor diagnosis. In the trade-offs between sensitivity and specificity, the rankletbased tumor texture and speckle texture were all significantly better than those of the original US images (Az: 0.83 vs. 0.58, p-value=0.0009 and Az=0.80 vs. 0.56, p-value=0.02). The proposed CAD system using textures from intensity transformed sonographic images is robust to various gray-scale distributions and is more suitable in clinical use.

AB - The malignancy of breast tumors are evaluated via ultrasound images on clinical examination. As a second viewer, a computer-aided diagnosis (CAD) system was developed to classify the breast tumors using texture features to avoid misclassifying carcinomas. A total of 69 cases including 21 malignant and 48 benign masses were acquired. For intensity- invariant texture extraction, the ultrasound images were first transformed into ranklet images to reduce the effect of brightness variability. From the ranklet images, tumor texture and speckle texture were extracted and compared to those from the original ultrasound images for tumor diagnosis. In the trade-offs between sensitivity and specificity, the rankletbased tumor texture and speckle texture were all significantly better than those of the original US images (Az: 0.83 vs. 0.58, p-value=0.0009 and Az=0.80 vs. 0.56, p-value=0.02). The proposed CAD system using textures from intensity transformed sonographic images is robust to various gray-scale distributions and is more suitable in clinical use.

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BT - 1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering

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A2 - Su, Fong-Chin

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PB - Springer Verlag

ER -

Lo CM, Chang RF, Huang CS, Moon W. Computer-aided diagnosis of breast tumors using textures from intensity transformed sonographic images. In Wang S-H, Su F-C, Yeh M-L, editors, 1st Global Conference on Biomedical Engineering and 9th Asian-Pacific Conference on Medical and Biological Engineering. Springer Verlag. 2015. p. 124-127. (IFMBE Proceedings). https://doi.org/10.1007/978-3-319-11128-5_35