Title
Automatic Registration Of Mammograms Using Texture-Based Anisotropic Features
Abstract
In this paper, an automated registration framework is proposed to identify the differences between corresponding mammographic images. The deformation between a pair of mammograms is approximated based on the matching of corresponding features on two images. First, a novel technique is employed to match the breast boundaries, aiming to maximize the mutual information between their curvature maps. Then, we apply Gabor filters onto the interior region of breast image, and extract texture-based anisotropic features. The registration process is accomplished through the recovery of the deformation field, in which both the positional and orientational attributes of the landmarks are registered correctly. The proposed technique is evaluated on three pairs of image pairs selected from MIAS digital mammogram database. The experimental results show that our method successfully registers corresponding mammograms with little human intervention, and becomes a valuable tool for effective detection of breast abnormalities.
Year
DOI
Venue
2006
10.1109/ISBI.2006.1625055
2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3
Keywords
Field
DocType
skin,spline,image texture,image registration,feature extraction,strain,histograms,biomechanics,image segmentation,mutual information,breast cancer,anisotropic magnetoresistance,data mining,edge detection,deformation
Computer vision,Histogram,Mammography,Pattern recognition,Computer science,Image texture,Edge detection,Image segmentation,Feature extraction,Artificial intelligence,Mutual information,Image registration
Conference
ISSN
Citations 
PageRank 
1945-7928
6
0.48
References 
Authors
5
4
Name
Order
Citations
PageRank
Kexiang Wang11036.35
Hong Qin22120184.31
Paul R. Fisher3102.05
Wei Zhao4103.51