ACO classification of thermogram symmetry features for breast cancer diagnosis
Tóm tắt
Breast cancer is the most commonly diagnosed form of cancer in women. While mammography is the standard modality for detecting breast cancer, it has been shown that medical thermography, which uses cameras with sensitivities in the thermal infrared, is also well suited for the task, especially in dense tissue and for small tumors. In this paper, we present an approach of analysing breast thermograms that first extracts a series of image features describing bilateral (a)symmetry between left and right breast regions, and then uses these features in a subsequent classification step. For the classification, we employ an ant colony optimisation based pattern recognition algorithm that is shown to provide a concise rule base with good classification performance.
Tài liệu tham khảo
Acharya UR, Ng EYK, Tan J-H, Sree SV (2012) Thermography based breast cancer detection using texture features and support vector machine. J Med Syst 36(3):1503–1510
American Cancer Society. Cancer facts and figures. http://www.cancer.org/docroot/STT/stt_0.asp
Anbar N, Milescu L, Naumov A, Brown C, Button T, Carly C, AlDulaimi K (2001) Detection of cancerous breasts by dynamic area telethermometry. IEEE Eng Med Biol Mag 20(5):80–91
Boquete L, Ortega S, Miguel-Jimnez JM, Rodrguez-Ascariz JM, Blanco R (2012) Automated detection of breast cancer in thermal infrared images, based on independent component analysis. J Med Syst 36(1):103–111
Dorigo M, Stuetzle T (2004) Ant colony optimization. MIT Press, Cambridge
Gautherie M (1983) Thermobiological assessment of benign and maligant breast diseases. Am. J. Obstet. Gynecol. 147(8):861–869
Haralick RM (1979) Statistical and structural approaches to texture. Proc IEEE 67(5):786–804
Head JF, Wang F, Lipari CA, Elliott RL (2000) The important role of infrared imaging in breast cancer. IEEE Eng Med Biol Mag 19:52–57
Jones BF (1998) A reappraisal of infrared thermal image analysis for medicine. IEEE Trans Med Imaging 17(6):1019–1027
Keyserlingk JR, Ahlgren PD, Yu E, Belliveau N, Yassa M (2000) Functional infrared imaging of the breast. IEEE Eng Med Biol Mag 19(3):30–41
Kovahi R, Sahami M (1996) Error-based and entropy-based discretization of contiuous features. In: 2nd international conference on knowledge discovery and data mining, pp 114–119
Mookiaha MRK, Acharyaa UR, Ng EYK (2013) Data mining technique for breast cancer detection in thermograms using hybrid feature extraction strategy. Quant InfraRed Thermogr J 9(2):151–165
Otero FEB, Freitas AA, Johnson CG (2008) cAnt-Miner: an ant colony classification algorithm to cope with continuous attributes. In: Ant colony optimization and swarm intelligence, pp 48–59
Parpinelli RS, Lopes HS, Freitas AA (2002) Data mining with an ant colony optimization algorithm. IEEE Trans Evol Comput 6(4):321–332
Qi H, Snyder WE, Head JF, Elliott RL (2000) Detecting breast cancer from infrared images by asymmetry analysis. In: 22nd IEEE international conference on engineering in medicine and biology
Schaefer G, Nakashima T, Zavisek M, Yokota Y, Drastich A, Ishibuchi H (2007) Thermography breast cancer diagnosis by fuzzy classification of statistical image features. In: IEEE international conference on fuzzy systems, pp 1096–1100
Schaefer G, Zavisek M, Nakashima T (2009) Thermography based breast cancer analysis using statistical features and fuzzy classification. Pattern Recognit 42(6):1133–1137
Tan TZ, Quek C, Ng GS, Ng EYK (2007) A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure. Expert Syst Appl 33(3):652–666
Tang X, Ding H, Yuan Y, Wang Q (2008) Morphological measurement of localized temperature increase amplitudes in breast infrared thermograms and its clinical application. Biomed Signal Process Control 3:312–318
Uematsu S (1985) Symmetry of skin temperature comparing one side of the body to the other. Thermology 1(1):4–7
Zavisek M, Drastich A (2005) Thermogram classification in breast cancer detection. In: 3rd European medical and biological, engineering conference, pp 1727–1983