Breast Cancer Classification and Precise Diagnosis using Breast MRI Data
Vidya K, Dr. M. Z. Kurian
Magnetic Resonance Imaging, Classifier Malignant/Benign tumor, Breast cancer
Precise diagnosis of the Breast cancer plays a pivotal role in deciding the treatment whether it is surgery or neo adjuvent chemotherapy. Accurate detection will avoid the unnecessary procedure and the removal of the breast. High resolution Magnetic Resonance Imaging (MRI) has been strongly incorporated as the imaging modality to measure the size of the tumor and hence the staging of the cancer in order to choose the best treatment for the patient. Therefore Detection of the tumor from the breast MRI and its classification performed by Computer Aided Diagnosis (CAD) based techniques has been a helping hand to the radiologist in taking the decision about the tumor. The aim of the proposed work is to segment and detect the tumor section from the MRI slices. This is done by initial thresholding followed by filtering and then extraction of foreground and background objects assisting in reliable classification. A statistical based approach is used for extracting the feature set followed by supervised learning classification. The detected tumor is extracted and compared with the data which is marked by the radiologist (ground truth data). Performance parameters such as sensitivity, specificity, accuracy and F values are calculated. Tumor is extracted from all the MRI slices of a patient and then its dimension is calculated at its widest part to know the stage for further treatment. Spearman correlation coefficient of 0.7079 is obtained by comparing the extracted tumor with radiologist data. Study outcome is also compared with the existing classification.
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Unique Paper ID: 156662

Publication Volume & Issue: Volume 9, Issue 4

Page(s): 466 - 473
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