Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive segmentation with Intelligent Scissors
Graphical Models and Image Processing
Medical Image Analysis: Progress over Two Decades and the Challenges Ahead
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection With Information-Based Maximum Discrimination
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Learning-Based Object Detection in Cardiac MR Images
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Variational Approach for the Segmentation of the Left Ventricle in Cardiac Image Analysis
International Journal of Computer Vision
Automatic Hybrid Segmentation of Dual Contrast Cardiac MR Data
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Automatic Segmentation of the Left Ventricle in Cardiac MR and CT Images
International Journal of Computer Vision
Robust active shape models: a robust, generic and simple automatic segmentation tool
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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This paper describes a segmentation technique to automatically extract the myocardium in 4D cardiac MR images for quantitative cardiac analysis and the diagnosis of patients. An approximate outline of the left ventricle is obtained either from automatic localization based on the maximum discrimination method or from copying a template shape during propagation. The histogram of the image is analyzed and divided into peaks using the EM algorithm to produce a region-based segmentation. This result and the image gradient are combined to obtain candidate boundanes for the left ventricle by deforming the contour using a graph search active contour approach. The final boundary is chosen using a minimum cut graph algorithm, spline fitting, or point pattern matching to maintain the shape of the template. We have experimented with the proposed method on a large number of patients and present some quantitative and qualitative results.