Multiple Support Vector-based approach to Breast tumor recognition

• Autorzy: Jiang H. , Chen X. , Liu B.

Warianty tytułu

PL

Wykorzystanie metody MSVM do wykrywania guza piersi

• Języki publikacji: EN

Abstrakty

EN

Based on Multi-Support Vector Machine (MSVM),this paper provides a method of MSVM for breast tumor recognition to solve unfixed size and individual difference with the breast tumor. Support Vector Machine (SVM) on the eight direction of bump area is taken to generate vector classifier and to select Gauss kernel function as kernel function. The system application and test shows that the MSVM in breast tumor recognition achieved good result, and provide the reliable basis for further medical diagnosis. The breast tumor recognition accuracy achieved 97.3%.

PL

Opisano wykorzystanie metody MSVM (multi-support vector machine) do wykrywania guza piersi. Metoda generuje klasyfikator wektorowy w ośmiu kierunkach a selekcję cech przeprowadza się wykorzystując funkcje Gaussa jako kernel.

Słowa kluczowe

EN

Multi-Support Vector Machines; edge detection; tumor recognition

PL

metoda MSVB; guz piersi; rozpoznawanie wzoru

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 5b
• Strony: 105--107
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Jiang H.

autor

Chen X.

autor

Liu B.

• School of Computer Science and Engineering,Xi'an Technological University

Bibliografia

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• [4] WEN Hao,Ma Jin-sheng,et al.On Microcalcifications Detection in Mammograms Based on Morphological Grayscale Reconstruction[J].CT Theory and Applications, 2006,15(2):33-37. (in Chinese).
• [5] Liu,C.F.Babbs,E.J.Delp.Multiresolution detection of speculated lesions in digital mammo- rgrams[J].IEEE Transactions on Image Processing,2001,10(6):874-884.
• [6] DENG Nai-yang,TIAN Ying-jie.The New Method in data mining: Support vector machine [M]. Beijing:Science press,2004. (in Chinese).
• [7] V.N.Vapnik. The essence of statistical learning theory(ZHANG Xue-gong translation)[M]. Beijing:Tsinghua University Press,2000. (in Chinese).
• [8] ZHU Jia-qun. Support vector machine and application of support vector machine technol- ogy in image segmentation of medical image visualization[D]. Nanjing University of Science & Technology,2007. (in Chinese)Infor [8] .
• [9] DUAN Rui,GUAN Yi-hong.Multi-threshold value segmentation approach for medical images[J].Journal of Computer Applications, 2008,28(S2):196-197.(in Chinese).
• [10] GAO Ni.Research and application of support vector machine technology in computer-aided medical diagnosing system for breast cancer[D]. Northwest University, 2009. (in Chinese).