Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Image Segmentation and Asymmetry Analysis of Breast Thermograms for Tumor Detection

Print
PDF
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 50 - Number 9
Year of Publication: 2012
Authors:
Pragati Kapoor
S. V. A. V. Prasad
Seema Patni
10.5120/7803-0932

Pragati Kapoor, S v a v Prasad and Seema Patni. Article: Image Segmentation and Asymmetry Analysis of Breast Thermograms for Tumor Detection. International Journal of Computer Applications 50(9):40-45, July 2012. Full text available. BibTeX

@article{key:article,
	author = {Pragati Kapoor and S.v.a.v. Prasad and Seema Patni},
	title = {Article: Image Segmentation and Asymmetry Analysis of Breast Thermograms for Tumor Detection},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {50},
	number = {9},
	pages = {40-45},
	month = {July},
	note = {Full text available}
}

Abstract

Breast Cancer is the most commonly diagnosed form of cancer in women. Infrared Thermography is a promising technology for breast cancer detection. But analysis of Breast thermograms has often been subjective and has resulted in inconsistency in the diagnosis of breast diseases by thermography. The fast growing tumor has a higher metabolic rate and associated increase in local vascularisation. It will cause the occurrence of some asymmetric heat patterns. Clinical interpretation of a breast thermogram is primarily based on the asymmetry analysis of these heat patterns visually and subjectively. In this paper, a new approach for automatic segmentation of Region of Interest and asymmetry analysis of breast thermograms is implemented. Canny edge detection operator and gradient operator are used to first segment the region of interest. Further asymmetry analysis is performed according to seven extracted features. The abnormality of a breast thermogram is clearly indicated by the features. A GUI is further created in Matlab to make the approach effectual, feasible and for Real Time analysis. 31 thermograms of normal and 11 thermograms of abnormal volunteers were taken.

References

  • Sherring, Varsha, 2009 Mediating Breast Cancer in India, NCA 94th Annual Convention, San Diego, CA.
  • Frize, M, Herry, C, Roberge, R, Processing of thermal images to detect Breast Cancer: A comparison, in proc. 2nd Joint IEEE EMBS/BMES Conf. , Houston, TX, pp. 1159-1160, 2002.
  • Mital, M, Scott, E. P. , Thermal Detection of Embedded Tumors Using Infrared Imaging, J. Bio-Mechanical. Engineering, 129(1) (2007) 33-39.
  • Jiang, L. J. , Ng, E Y K, Yau, W Y, Jiang, S. Wu X D, A Perspective on Medical IR Imaging, Int. J. Med. Eng. Technol. 29 (6) (2005) 257-267.
  • Kapoor, Pragati, Prasad, S. V. A. V, et al. , 2010 Real Time Intelligent Thermal Analysis approach for early diagnosis of breast cancer, International Journal of computer applications, vol. 1, no. 5, pp. 22-24.
  • Hongshan, Yu and Yaonan Wang, 2004 An Improved Canny Edge Detection Algorithm, [J], Computer Engineering and Application, vol 40, pp. 27-29.
  • Canny, J. A Computational approach to edge detection IEEE Trans, Pattern Anal and Machine Intelligence, vol. 6, 1995 pp. 679-698.
  • Qin, Xujia, jiang, Jionghui, Wang, Weihong, Fan, Zhang, Canny operator based level set segmentation algorithm for medical images, 2007, 1st International Conference on Bioinformatics & Biomedical Engineering [C], ICBBE, 2007, pp. 892-895.
  • Keyserlingk, J. R. , Ahlgren, P. D. , Yu, E, Belliveau, N. , Yassa, M. , Functional Infrared Imaging of the Breast: Historical Perspectives, Current Application and Future Considerations, Biomedical Engineering Handbook, CRC Press, 2006.
  • Head, Jonathan F, Wang, Fen, Lipari, The Important Role of Infrared Imaging in Breast Cancer, IEEE Engineering in Medicine and Biology, June 2000.
  • Jones, B. F. , A Reappraisal of the Use of Infrared Thermal Image Analysis in Medicine, IEEE Tran. Med Imaging, 17(6) 1998, 1019-1027.
  • Ng E. Y. K. , Ung L. N. , et al. , 2001 Statistical Analysis of Healthy and Malignant Breast Thermography, Journal of Medical Engineering and Technology, vol. 25, pp. 253-263.
  • Head, J. F. , Elliott, R. L. , Infrared Imaging: Making Progress in Fulfilling its Medical Promise, IEEE Engineering. Med. Biol. Mag. 21 (2002), 80-85.
  • G, Schaefer, Zavisek, M. , Nakashima, T, Thermography Based Breast Cancer Analysis Using Statistical Features and Fuzzy Classification, Elsevier-Pattern Recognition, 47 (2009) 1133-1137.
  • Anbar, Michael, Milescu, Lorin, Naumov, Aleksey, Brown, Cheryl, Detection of Cancerous Breasts by Dynamic Area Thermometry, IEEE Engineering in Medicine & Biology, Sept 2001.
  • Ng, E. Y. K. , Fok, S. C. , Peh, Y. C. , Ng, F. C. and Sim, L. S. J. , 2002 Computerized detection of breast cancer with artificial intelligence and thermograms, International Journal of Medical Engineering & Technology, 26(4):152-157.
  • Ng, E Y K, Sudarshan, NM, Computer Simulation in Conjunction With Medical Thermography as an Adjunct Tool For Early Detection of Breast Cancer, BMC Cancer Journal V. 4, 2004.