Pectoral Muscle Removal in Digital Mammograms Using Region Based Standard Otsu Technique

Jacinta C. Anusionwu (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
Vincent C. Chijindu (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
Joy N. Eneh (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
ThankGod I. Ozue (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
Nnabuike Ezukwoke (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
Mamilus A. Ahaneku (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria)
Edward C. Anoliefo (Electronic & Computer Engineering Department University of Nigeria, Nsukka Enugu State, Nigeria.)
Walter A. Ohagwu (Electrical & Electronic Engineering Department Enugu State University of Science & Technology, Enugu State)

Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 11, No 2: June 2023

Mammography is usually the first preference of imaging diagnostic modalities used for detection of breast cancer in the early stage. Two projections Cranio Caudal (CC) and Medio-Lateral Oblique (MLO) which depict different degrees for visualizing the breast are used during digital mammogram acquisition and the MLO view shows more breast tissue and Pectoral Muscle (PM) area when compared to CC view. Although, the PM is a criterion used to show proper positioning, it can result in biased results of mammographic analysis like: cancer detection and breast tissue density estimation, because the PM area has similar or even higher intensity than breast tissue and breast lesions if present. This paper proposed a Region Based Standard Otsu thresholding method for the elimination of PM area present in MLO mammograms. The proposed algorithm was implemented using 322 digital mammograms from the Mammographic Image Analysis Society (MIAS) database, and the difference between the PM detected and the manually drawn PM region by an expert was evaluated. The results showed an average: Jaccard Similarity Index, False Positive Rate (FPR) and False Negative Rate (FNR) of 93.2%, 3.54% and 5.68% respectively and also an acceptable rate of 95.65%