Thermography Based Breast Cancer Detection Using Texture Features and Support Vector Machine
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Breast cancer is a leading cause of death nowadays in women throughout the world. In developed countries, it is the most common type of cancer in women, and it is the second or third most common malignancy in developing countries. The cancer incidence is gradually increasing and remains a significant public health concern. The limitations of mammography as a screening and diagnostic modality, especially in young women with dense breasts, necessitated the development of novel and more effective strategies with high sensitivity and specificity. Thermal imaging (thermography) is a noninvasive imaging procedure used to record the thermal patterns using Infrared (IR) camera. The aim of this study is to evaluate the feasibility of using thermal imaging as a potential tool for detecting breast cancer. In this work, we have used 50 IR breast images (25 normal and 25 cancerous) collected from Singapore General Hospital, Singapore. Texture features were extracted from co-occurrence matrix and run length matrix. Subsequently, these features were fed to the Support Vector Machine (SVM) classifier for automatic classification of normal and malignant breast conditions. Our proposed system gave an accuracy of 88.10%, sensitivity and specificity of 85.71% and 90.48% respectively.
KeywordsBreast cancer Texture Classifier Support vector machine Malignant
Authors thank Goh Yan Kun and Abdul Mutalib Bin Abdul Hamid for helping in running the codes, and acknowledge and thank Dr. Llewellyn Sim, Senior Consultant, Department of Diagnostic Radiology, Singapore General Hospital, Singapore, for providing the thermogram images.
- 1.Ahmad, Z., Khurshid, A., Qureshi, A., Idress, R., Asghar, N., and Kayani, N., Breast carcinoma grading, estimation of tumor size, axillary lymph node status, staging, and nottingham prognostic index scoring on mastectomy specimens. Indian J. Pathol. Microbiol. 52:477–481, 2009.CrossRefGoogle Scholar
- 2.http://www.who.int/cancer/detection/breastcancer/en/index1.html (Last accessed Aug 2010).
- 3.http://www.who.int/healthinfo/global_burden_disease/2004_report_update/en/ (Last accessed on Aug 2010).
- 4.Coleman, M. P., Quaresma, M., Berrino, F., Lutz, J. M., De Angelis, R., Capocaccia, R., Baili, P., Rachet, B., Gatta, G., Hakulinen, T., Micheli, A., Sant, M., Weir, H. K., Elwood, J. M., Tsukuma, H., Koifman, S., E Silva, G. A., Francisci, S., Santaquilani, M., Verdecchia, A., Storm, H. H., and Young, J. L., Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol. 9:730–756, 2008.Google Scholar
- 7.Elmore, J. G., Wells, C. F., and Carol, M. P. H., Variability in radiologists interpretation of mammograms. N. Engl. J. Med. 331:99–104, 1993.Google Scholar
- 10.Gautherine, M., and Gros, C., Contribution of infrared thermography to early diagnosis, pretheraputic prognosis and post-irradiation follow-up of breast carcinomas. Med. Mundi. 21:135–149, 1976.Google Scholar
- 11.Gros, C., Gautherine, M., and Bourjat, P., Prognosis and post therapeutic follow-up of breast cancers by thermography. Bibl. Radiol. 6:77–90, 1975.Google Scholar
- 14.Louis, K., Walter, J., and Gautherie, M., Long-term assessment of breast cancer risk by thermal imaging. Prog. Clin. Biol. Res. 107:279–301, 1982.Google Scholar
- 15.Amalric, R., Giraud, D., Altschuler, C., Amalric, F., Spitalier, J. M., Brandone, H., Ayme, Y., and Gardiol, A. A., Does infrared thermography truly have a role in present-day breast cancer management? Prog. Clin. Biol. Res. 107:269–78, 1982.Google Scholar
- 17.Jakubowska, T., Wiecek, B., Wysocki, M., and Drews-Peszynski, C., Thermal Signatures for Breast Cancer Screening - Comparative Study. Proc. IEEE EMBS Conf. Cancun, Mexico, 2003.Google Scholar
- 20.Tuceryan, M., and Jain, A. K., Texture analysis. in: C.H. Chen, L.F. Pau, and P.S.P. Wang, (Eds.), Handbook of pattern recognition & computer vision, 1993.Google Scholar
- 22.Ng, E. Y. K., Chen, Y., Ung, L. N., Fok, S. K., and Wan, I. S. Y., Thermography as an Indicator of Breast Blood Perfusion. Proc. 10th Inl. Conf. on Biomed. Eng., Singapore Ed: JCH Goh, Humanities Press 275–276, 2000.Google Scholar
- 24.Thermography Guidelines (TG), Standards and Protocols in Clinical Thermographic Imaging, http://www.iact-org.org/professionals/thermog-guidelines.html, 2002 (Last accessed Aug 2010).
- 25.Amalu, W. C., Hobbins, W. B., Head, J. F., and Elliott, R. L., Infrared imaging of the breast—an overview. In Biomedical Engineering Handbook, CRC Press, chapter 25-1 to 25–21, 2006.Google Scholar
- 26.Ammer, K., and Ring, E. F. L., Standard procedures for infrared imaging in medicine. In Biomedical Engineering Handbook, CRC Press, chapter 36-1 to 36–14, 2006.Google Scholar
- 27.Qi, H., Kuruganti, P. T., and Snyder, W. E., Detecting breast cancer from thermal infrared images by asymmetry analysis. In Biomedical Engineering Handbook, CRC Press, ch. 27-1 to 27–14, 2006.Google Scholar
- 28.Ring, E. F. J., and Ammer, K., The technique of infra red imaging in medicine. Thermology Intl. 10:7–14, 2000.Google Scholar
- 29.Jung, A., and Zuber, J., Thermographic methods in medical diagnostics. Med, Warsaw, 1998.Google Scholar
- 30.Head, J. F., Lipari, C. A., Wang F., and Elliot, R. L., Image analysis of digitized infrared images of the breasts from a first generation infrared imaging system. Proc 19th Intl. Conf. IEEE/EMBS Chicago, IL. USA, 1997.Google Scholar
- 32.Gonzalez, R. C., and Woods, R. E., Digital image processing, 2nd edition. Prentice Hall, New Jersey, 2001.Google Scholar
- 37.Brekelmans, C. T. M., Westers, P., Faber, J. A. J., Peeters, P. H. M., and Collette, H. J. A., Age specific sensitivity and sojourn time in a breast cancer screening programme (DOM) in The Netherlands: a comparison of different methods. J. Epidemiol. Community Health 50:68–71, 1996.CrossRefGoogle Scholar
- 41.Wiecek, B., Wiecek, M., Strakowski, R., Jakubowska, T., and Ng, E.Y.K., Wavelet-based thermal image classification for breast screening and other medical applications, chp. 12, Eds E. Y. K. Ng, U. R. Acharya, and J. S. Suri, Performance evaluation techniques in multi-modality breast cancer screening, Diagnosis and Treatment, American Scientific Publishers, 2010.Google Scholar