An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
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
Combining Edge, Region, and Shape Information to Segment the Left Ventricle in Cardiac MR Images
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
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
Comprehensive Cardiovascular Image Analysis Using MR and CT at Siemens Corporate Research
International Journal of Computer Vision
Automatic Recovery of the Left Ventricular Blood Pool in Cardiac Cine MR Images
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Comprehensive Segmentation of Cine Cardiac MR Images
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Segmentation of Pathologic Hearts in Long-Axis Late-Enhancement MRI
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Left Ventricle Tracking Using Overlap Priors
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
Left Ventricle Segmentation from Heart MDCT
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Left Ventricle Segmentation via Graph Cut Distribution Matching
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Left Ventricle Segmentation Using Diffusion Wavelets and Boosting
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
FIMH'07 Proceedings of the 4th international conference on Functional imaging and modeling of the heart
4D ventricular segmentation and wall motion estimation using efficient discrete optimization
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Cardiac anchoring in MRI through context modeling
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
A 3d tool for left ventricle segmentation editing
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
A survey of shaped-based registration and segmentation techniques for cardiac images
Computer Vision and Image Understanding
Segmentation of the left ventricle in cardiac cine MRI using a shape-constrained snake model
Computer Vision and Image Understanding
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
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This paper describes a segmentation technique to automatically extract the myocardium in 4D cardiac MR and CT datasets. The segmentation algorithm is a two step process. The global localization step roughly localizes the left ventricle using techniques such as maximum discrimination, thresholding and connected component analysis. The local deformations step combines EM-based region segmentation and Dijkstra active contours using graph cuts, spline fitting, or point pattern matching. The technique has been tested on a large number of patients and both quantitative and qualitative results are presented.