Tagged cardiac MRI: detection of myocardial boundaries by texture analysis

The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Cardiac tagged MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium. Tracking the grid allows the displacement estimation in the myocardium. The work described in this paper aims to automate the myocardial contours detection and the following of the grids of tags on Short-Axis and Long-Axis time sequences, in order to firstly optimize the 3D+T study of the parietal contractions and secondly make possible its clinical use. 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. The follow-up of the grid of tags that we have implemented is based on a grid of active contours (B-snakes) which part of the energy is calculated in the Fourier’s domain. The results obtained with our method is fully automatic and correct on Short-Axis as well as on Long-Axis sequences, when previous works on cardiac tagged MR images analysis always used manual contours detection.