Research Article Open Access

A Novel Approach in Malignancy Detection of Computer Aided Diagnosis

S. Meenalosini1, J. Janet2 and E. Kannan1
  • 1 Department of CSE, Vel Tech Dr. RR and Dr. SR Technical University, Chennai, India
  • 2 Department CSE and IT, Dr. MGR Educational and Research Institute University, Chennai, India


Problem statement: Breast cancer is one of the most dangerous diseases that cause innumerable fatal in the female society. Early detection is the only way to reduce the mortality. Due to variety of factors sometimes manual reading of mammogram results in misdiagnosis. So that the diagnosis rate varies from 65-85%. Various computer aided detection techniques have been proposed for the past 20 years. Even then the detection rate is still not high. Approach: The proposed method consists of the following steps preprocessing, segmentation, feature extraction and classification. Noise, Artifact and pectoral region are removed in a preprocessing step. Contrast enhancement and Sobel operator with segmentation algorithm is used to segment the mass region. Feature extraction is performed on the segmented image using gray level co-occurrence matrix and local binary pattern method. Extracted features are classified using support vector machine. The performance of the proposed system is evaluated using partest method. Results: Proposed algorithm shows 98.8% sensitivity and 97.4% Specificity. Conclusion: The proposed algorithm is fully automatic and will be helpful in assisting the radiologists to detect the malignancy efficiently.

American Journal of Applied Sciences
Volume 9 No. 7, 2012, 1020-1029


Submitted On: 8 March 2012 Published On: 15 May 2012

How to Cite: Meenalosini, S., Janet, J. & Kannan, E. (2012). A Novel Approach in Malignancy Detection of Computer Aided Diagnosis. American Journal of Applied Sciences, 9(7), 1020-1029.

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  • Contrast Limited Adaptive Histogram Equalization (CLAHE)
  • Madio Lateral Oblique (MLO)
  • malignancy efficiently
  • dangerous threat
  • mammogram capturing process