Robust Automatic Pectoral Muscle Segmentation from Mammograms Using Texture Gradient and Euclidean Distance Regression

In computer-aided diagnosis (CAD) of mediolateral oblique (MLO) view of mammogram, the accuracy of tissue segmentation highly depends on the exclusion of pectoral muscle. Robust methods for such exclusions are essential as the normal presence of pectoral muscle can bias the decision of CAD. In this...

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Veröffentlicht in:	Journal of digital imaging Jg. 29; H. 1; S. 115 - 125
Hauptverfasser:	Bora, Vibha Bafna, Kothari, Ashwin G., Keskar, Avinash G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2016 Springer Nature B.V
Schlagworte:	Algorithms Automation Breast Neoplasms - diagnostic imaging Computer aided design Databases, Factual Female Humans Imaging Mammography - methods Medicine Medicine & Public Health Muscles Pattern Recognition, Automated - methods Pectoralis Muscles - diagnostic imaging Radiographic Image Interpretation, Computer-Assisted - methods Radiology Regression Reproducibility of Results Segmentation Surface layer Texture Pectoral muscle detection Computer aided diagnosis Hough transform Euclidean distance regression Mammograms Texture gradient
ISSN:	0897-1889, 1618-727X, 1618-727X
Online-Zugang:	Volltext
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