Segmentation of the Pectoral Muscle Boundary in Breast MR Images

Lee, Myungeun; Chen, Yanjuan; Kim, Soo-Hyung; Kim, Jonghyo

doi:10.1109/bibe.2011.60

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…This line is then smoothed using the repeated "cliff detection" algorithm to draw the pectoral boundary more accurately. In [13], authors proposed an approach for the detection of segmentation at the pectoral muscle boundary based on the structure tensor. Experimental results indicate that the proposed method distinguishes the pectoral muscle exactly with the segments [13].…”

Section: Introductionmentioning

confidence: 99%

“…In [13], authors proposed an approach for the detection of segmentation at the pectoral muscle boundary based on the structure tensor. Experimental results indicate that the proposed method distinguishes the pectoral muscle exactly with the segments [13]. In [14], authors conducted a study based on the positional characteristics of the pectoral muscle.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Single Sided Edge Marking Method for Detecting Pectoral Muscle in Digital Mammograms

Toz

Erdoğmuş

2018

Eng. Technol. Appl. Sci. Res.

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In the computer-assisted diagnosis of breast cancer, the removal of pectoral muscle from mammograms is very important. In this study, a new method, called Single-Sided Edge Marking (SSEM) technique, is proposed for the identification of the pectoral muscle border from mammograms. 60 mammograms from the INbreast database were used to test the proposed method. The results obtained were compared for False Positive Rate, False Negative Rate, and Sensitivity using the ground truth values pre-determined by radiologists for the same images. Accordingly, it has been shown that the proposed method can detect the pectoral muscle border with an average of 95.6% sensitivity.

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Section: Introductionmentioning

confidence: 99%