Introduction to algorithms
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
The Pyramid Match Kernel: Efficient Learning with Sets of Features
The Journal of Machine Learning Research
A string matching approach for visual retrieval and classification
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
A CNN based algorithm for retinal vessel segmentation
ICC'08 Proceedings of the 12th WSEAS international conference on Circuits
Automatic Selection of Keyframes from Angiogram Videos
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
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In this paper we address the problem of finding similar coronary angiograms from a database of angiograms using a new constrained nonrigid shape model for the description of coronary arteries. The model captures the non-rigid variations in the artery shapes while still preserving the overall perceptual spatial layout based on the articulation constraints between arteries. Shape matching involves testing for class membership using the constraints specified in the model. The shape similarity method is demonstrated in a similarity retrieval application on a large database of angiogram images.