Skip to main content

Development of Breast Ultrasound CAD System for Screening

  • Conference paper
Digital Mammography (IWDM 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4046))

Included in the following conference series:

Abstract

Mass screening of breast cancer utilizing mammography (MMG) has been widely carried out. However, MMG might not be able to depict small impalpable masses in dense breast tissue clearly. We have developed a computer-aided detection (CAD) scheme in whole breast ultrasound (US) system for mass screening which has been developed by ALOKA CO., LTD., Japan. Our CAD scheme and image processing techniques have the following three benefits.

  1. 1

    Indication of mass candidates by our CAD scheme.

  2. 2

    Visualization of breast US images in two views of B-planes (CC View and ML View) and C-plane.

  3. 3

    Comparison of left and right breast images as in MMG.

The performance of the CAD scheme in detecting malignant masses on an initial study has a true positive fraction of 0.91 (10/11) at a 0.69 (633/924) false positive per image. Although mass screening utilizing US was not appropriate because images acquired by conventional hand probe were poor in reproduction, the problem could be solved in our system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Horsch, K., Giger, M.L., Venta, L.A., Vyborny, C.J.: Automatic segmentation of breast lesions on ultrasound. Med. Phys. 28, 1652–1659 (2001)

    Article  Google Scholar 

  2. Drukker, K., Giger, M.L., Horsch, K., Kupinski, M.A., Vyborny, C.J.: Computerized lesion detection on breast ultrasound. Med. Phys. 29, 1438–1446 (2002)

    Article  Google Scholar 

  3. Drukker, K., Giger, M.L., Vyborny, C.J., Mendelson, E.B.: Computerized detection and classification of cancer on breast ultrasound. Acad. Radiol. 11, 526–535 (2004)

    Article  Google Scholar 

  4. Kupinski, M.A., Giger, M.L.: Automated seeded lesion segmentation on digital mammograms. IEEE Trans. Med. Imaging 17, 510–517 (1998)

    Article  Google Scholar 

  5. Horsch, K., Giger, M.L., Venta, L.A., Vyborny, C.J.: Computerized diagnosis of breast lesions on ultrasound. Med. Phys. 29, 157–164 (2002)

    Article  Google Scholar 

  6. Chang, R.F., Chang-Chien, K.C., Chen, H.J., Chen, D.R., Takada, E., Moon, W.K.: Whole breast computer-aided screening using free-hand ultrasound, Computer Assisted Radiology and Surgery. In: Lemke, H.U., Inamrua, K., Doi, K., Vannier, M.W., Farman, A.G. (eds.) Proc. CARS 2005, pp. 1075–1080 (2005)

    Google Scholar 

  7. Huang, Y.L., Chen, D.R.: Watershed segmentation for breast tumor in 2-D sonography. Ultrasound in Medicine & Biology 30, 625–632 (2004)

    Article  Google Scholar 

  8. Chen, D.R., Chang, R.F., Chen, C.J., Ho, M.F., Kuo, S.J., Chen, S.T., Huang, S.J., Moon, W.K.: Classification of breast ultrasound images using fractal feature. Journal of Clinical Imaging 29, 235–245 (2005)

    Article  Google Scholar 

  9. Fukuoka, D., Hara, T., Fujita, H., Endo, T., Kato, Y.: Automated dtection and classification of masses on breast ultrasonograms and its 3D imaging technique. In: 5th International Workshop on Digital Mammography, Proc. IWDM 2000, pp. 182–188 (2001)

    Google Scholar 

  10. Hara, T., Fukuoka, D., Fujita, H., Endo, T., Kato, Y.: Development of CAD system for 3D breast ultrasound images. In: 6th International Workshop on Digital Mammography, Proc. IWDM 2002, pp. 368–371 (2002)

    Google Scholar 

  11. Ehrich, R.W.: A symmetric hysterisis smoothing algorithm that preserves principal features. CGIP8, 121–126 (1978)

    Google Scholar 

  12. Canny, J.F.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 9, 679–698 (1986)

    Article  Google Scholar 

  13. Vincent, L., Soille, P.: Watersheds in Digital Spaces: An efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Mach. Intell. 13, 583–598 (1991)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Fukuoka, D. et al. (2006). Development of Breast Ultrasound CAD System for Screening. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_53

Download citation

  • DOI: https://doi.org/10.1007/11783237_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35625-7

  • Online ISBN: 978-3-540-35627-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics