Breast Skin-Line Segmentation Using Contour Growing

Authors:
Robert Martí;Arnau Oliver;David Raba;Jordi Freixenet
Affiliations:
Computer Vision and Robotics Group, University of Girona, Av. Lluís Santaló 17071, Spain;Computer Vision and Robotics Group, University of Girona, Av. Lluís Santaló 17071, Spain;Computer Vision and Robotics Group, University of Girona, Av. Lluís Santaló 17071, Spain;Computer Vision and Robotics Group, University of Girona, Av. Lluís Santaló 17071, Spain
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Year:
2007

Citing 4
Cited 4

Edge Detection and Ridge Detection with Automatic Scale Selection

International Journal of Computer Vision
Detection of line junctions and line terminations using curvilinear features

Pattern Recognition Letters
The use of multi-scale monogenic signal on structure orientation identification and segmentation

IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Breast segmentation with pectoral muscle suppression on digital mammograms

IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II

Automatic microcalcification and cluster detection for digital and digitised mammograms

Knowledge-Based Systems
A boosting based approach for automatic micro-calcification detection

IWDM'10 Proceedings of the 10th international conference on Digital Mammography
Pectoral muscle segmentation: A review

Computer Methods and Programs in Biomedicine
Estimation of the breast skin-line in mammograms using multidirectional Gabor filters

Computers in Biology and Medicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel methodology to obtain the breast skin line in mammographic images. The breast edge provides important information of the breast shape and deformation which is posteriorly used by other processing techniques, typically mammographic image registration and abnormality detection. The proposed methodology is based on applying edge detection algorithms and scale space concepts. The proposed method is a particular implementation (application focused) of a growing active contour with common considerations. Quantitative and qualitative evaluation is provided to show the validity of the approach.