Deformable B-solids and implicit snakes for 3D localization and tracking of SPAMM MRI data
Computer Vision and Image Understanding
Analysis of Cardiac Function from MR Images
IEEE Computer Graphics and Applications
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrated Quantitative Analysis of Tagged Magnetic Resonance Images
Proceedings of the First International Workshop on Functional Imaging and Modeling of the Heart
Phase-Driven Finite Element Model for Spatio-temporal Tracking in Cardiac Tagged MRI
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Bandpass Optical Flow for Tagged MR Imaging
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Analysis of tagged cardiac MRI sequences
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Selective diffusion for oriented pattern extraction: Application to tagged cardiac MRI enhancement
Pattern Recognition Letters
MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
A novel T-CAD framework to support medical image analysis and reconstruction
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
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The noninvasive assessment of cardiac function is of first importance for the diagnosis of cardiovascular diseases. Among all medical scanners only a few enables radiologists to evaluate the local cardiac motion. Tagged cardiac MRI is one of them. This protocol generates on Short-Axis (SA) sequences a dark grid which is deformed in accordance with the cardiac motion. Tracking the grid allows specialists a local estimation of cardiac geometrical parameters within myocardium. The work described in this paper aims to automate the myocardial contours detection in order to optimize the detection and the tracking of the grid of tags within myocardium. The method we have developed for endocardial and epicardial contours detection is based on the use of texture analysis and active contours models. Texture analysis allows us to define energy maps more efficient than those usually used in active contours methods where attractor is often based on gradient and which were useless in our case of study, for quality of tagged cardiac MRI is very poor.