Efficient Breast Segmentation and Pectoral Muscle Removal Technique in Wavelet Domain for Computer-Aided Diagnosis
DOI:
https://doi.org/10.5281/Keywords:
Pectoral muscle, Mediolateral oblique, Cranial-Caudal, Computer-aided detection systemAbstract
Accurate extraction of the breast boundary and reliable removal of the pectoral muscle are essential preprocessing steps for computer-aided diagnosis of breast cancer using mammographic images. In this work, a wavelet-domain framework is proposed to effectively segment the breast region and identify the pectoral muscle in mediolateral oblique (MLO) mammograms. The breast region is first delineated using multilevel wavelet decomposition, which enhances structural features while suppressing background noise and imaging artifacts. Subsequently, morphological operations are employed to refine the segmented region and to detect and eliminate the pectoral muscle. The proposed method was evaluated using 322 digital mammograms from the MIAS database, demonstrating high accuracy and robust performance for breast region extraction and pectoral muscle removal.
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