Breast cancer can be more easily treated and the treatment be more effective the earlier the cancer is discovered. It is estimated that a palpable tumor may has been in existence an average of seven years. According to the statistics published in the cover story of Time Magazine, January 14, 1991, one American woman in ten will get breast cancer, why and what can be done?Since then, the incidence rate has risen. On the basis of current rates, one out of eight women will be affected by this disease in their lifetime (Feuer, E.J. et. al., The life time risk of developing breast cancer, J. Natl. Cancer Inst., 85, pp. 892-897, 1993). It is a well-recognized health hazard. Any method which can aid in the discovery of suspicious growths at an earlier and smaller stage and before it becomes overt can have great benefit in reducing the human toll of breast cancer. Strong medical evidence has shown that early detection for breast cancer is crucial in order to save thousands of women's lives and the survival rate can be as high as 82%. RSSIPL is currently developing and investigating various effective computer-aided diagnostic (CAD) systems for detection, segmentation and classification of microcalcifications and masses. A joint effort of this research includes Dr. San-Kan Lee who is the Chairman of Diagnostic Radiology in Taichung Veterans General Hospital in Taiwan and Professor Pau-Choo Chung with the Department of Electrical Engineering at National Cheng Kung University, Tainan, Taiwan. Our goal is to focus on breast cancer early detection and develop computer-aided design (CAD) screening systems for clinical applications. So far, we have developed two prototype CAD systems which will be integrated with the existing Picture Archiving and Communication System (PACS) currently implemented in Taichung Veterans General Hospital. One is a mammography screening system which has been filed by UMBC for a patent. Another is a 3-D surgical navigation system that can be used to localize clustered microcalcifications for surgical navigation for needle biopsy. It already patented in Taiwan and is currently filed by National Science Council in Taiwan for a US patent.

Patent Awarded

  1. P. C. Chung, C.S. Lo, C.-I Chang, S.K. Lee and C.-W. Yang, 3-D Localization of Clustered Microcalcifications Using Cranio-Caudal and Medio-Lateral Oblique Views, US Patent, number 6,614,921 B1, September 2, 2003
  2. P.C. Chung, S.K. Lee, C.-I Chang, C.W. Yang and C.S. Lo, 3-D Localization of Clustered Microcalcifications Using Cranio-Caudal and Medio-Lateral Oblique Views, Patent and Trademark Office of Taiwan, January 12, 2000, Patent Number 121,953.
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Patents Pending

  1. C.-I Chang, C.-S. Lo, P.-C. Chung, S.-K. Lee and C.-W. Yang, Computer-Assisted Mammography Screening to Detect and Classify Microcalcifications, August 15, 2000.
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Ph.D. Dissertation

  1. Chien-Shun Lo, Computer-Aided System for Diagnosis of Clustered Microcalcifications in Mammograms, June 2000 (co-advisor with Professor Pau-Choo Chung in Taiwan)
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Ph.D. Dissertation in progress

  1. Sheng-Chi Yang, Design and Development of Computer-Aided Mammography Screening System for Mass Detection, Department of Electrical Engineering, National Cheng Kung University.
  2. Y. Chen, Mass Detection and Classification for Mammography, Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County.
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Master Thesis

  1. Y. Liao, Mass Detection in Mammography Using Texture Analysis, June 2002 (co-advisor with Professor Shu-Mei Guo)
  2. R. Marvel, Multiscale Analysis for Feature Enhancement in Digital Mammography Department of Computer Science and Electrical Engineering, M.S. Thesis, University of Maryland Baltimore County, MD, May 1996.
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Honors and Awards

  1. Best paper award Chinese Journal of Radiology for S.-K. Lee, S.-C. Yang, P.C. Chung, C.-S. Lo, C.-W. Yang and C.-I Chang, Three dimensional localization of microcalcification on X-ray mammograms, by
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Journal Publications

  1. S.K. Lee, P.-C. Chung, C.-I Chang, C.-S. Lo, T. Lee, G.-C. Hsu and C.-W. Yang, ¡§Classification of clustered microcalcifications using a shape cognitron,¡¨Neural Networks vol. 16, pp. 121-132, 2003
  2. S.M. Guo, P.S. Liao, Y.C. Liao, S.C. Yang, P.C. Chung and C.-I Chang, ¡§Mass detection in mammography using texture analysis,¡¨Chinese Journal of Radiology, vol. 28, no. 3, pp. 149-157, June 2003
  3. S.-C. Yang, S.-K. Lee, P.C. Chung, C.W. Yang,, T. Lee, G.-C. Hsu, C.-W. Yang C.-I Chang and C.-S. Luo, "A computer-aided diagnostic system for detection and segementation of clustered microcalcifications in digital mammograms," Chinese Journal of Radiology, vol. 27, no. 3, pp. 89-101, June 2002. (in Chinese)
  4. S.-K. Lee, S.-C. Yang, P.C. Chung, C.-S. Lo, C.-W. Yang and C.-I Chang, Three dimensional Localization of Microcalcification on X-ray mammograms, Chinese Journal of Radiology, vol. 26, No. 3, pp. 107-118, December 2001.(in Chinese)
  5. S.-K. Lee, C.-S. Lo, C.-M. Wang, P.-C. Chung, C.-I Chang, C.-W. Yang and P.-C. Hsu, A computer-aided design mammography screening system for detection and classification of microcalcifications, J. Medical Informatics, vol. 60, no. 1, pp. 29-57, Oct. 2000.
  6. C.-S. Lo, P.-C. Chung, S.-K. Lee, C.-I Chang, T. Lee, G.C. Hsu and C.W. Yang, Off-line mammography screening system embedded with hierarchically-coarse-to-fine techniques for the detection and segmentation of clustered Microcalcifications, Institute of Electronics, Information, Communication Engineers (IEICE) Transaction on Information and System, vol. E83-D, pp. 2161-2173, no. 12, December 2000.
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Conference Publications

  1. S.-C. Yang, P.C. Chung, C.-I Chang, S.K. Lee, Y.N. Chung, C.W. Yang, M.C. Lu and C.S. Lo An automated system for detection and segmentation of masses in digital mammograms, 5th World Multi-conference on Systemics, Cybernetics and Informatics, Orlando, Florida, USA, July 22-25, 2001.
  2. C.-S. Lo, S.-K. Lee, P.C. Chung and C.-I Chang, An automatic computerized system for detection and segmentation of clustered microcalcifications on mammograms, Proc. the 46th Annual Meeting of Radiological Society of Republic of China, Mar. 27-28, 1997, p. F157.
  3. C.-S. Lo, P.-C. Chung, C.-I Chang, and S.K. Lee, A computerized system for detection and segmentation of clustered microcalcifications, Joint Conf. 1996 International Computer Symposium, Dec. 19-21, Kaohsiung, Taiwan, ROC, pp. 247-253, 1996.
  4. B.-C. Hsu, P.-C. Chung and C.-I Chang, Automated system for detection and classification of microcalcifications in digital mammograms, Proc. CVGIP'96, Taiwan, ROC, 1996. (awarded for the best paper in the conference)
  5. P.-S. Liao, B.C. Hsu, C.-S. Luo, P.-C. Chung, T.-S. Chen, S.-K. Lee, L. Cheng and C.-I Chang, Automatic detection of microcalcifications in digital mammograms,18th Annual Int. Conf. IEEE Eng. in Med. and Bio. Society, Oct. 31-Nov. 3, 1996, Amsterdam, Netherlands.
  6. S.-C. Lo, P.-C. Chung, B.-C. Hsu, C.-I Chang, S.K. Lee and B.-S. Liao, An algorithm for detection and segmentation of clustered microcalcifications on mammograms,Proc. 2nd Medical Eng. Week of the World, Taipei, Taiwan, ROC, 1996.
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