Assessment of myocardial deformations from untagged cardiac cine MRI.

This paper presents a method for the assessment of left ventricular myocardial deformations from untagged cardiac cine MRI. Firstly, a level set segmentation process is applied on the dataset to detect both endocardial and epicardial boundaries. Then the successive contours are matched using an original procedure that consists in an alignment followed by a morphing process. From the matched contours, we deduced an initial velocity of the contour points that will be used in a Thin-Plate Splines approximation method for estimating of the velocity flow on the complete myocardial structure. Finally, local measurements of ventricular deformations are derived from the velocity flow. The validation of the method is performed both mathematically and by comparing the measurements to those obtained on the same patients with the HARmonic Phase reference (HARP) method applied on matched tagged MR images.

MR/CT multimodal registration of short-axis slices in CT volumes.

This paper deals with the registration of Magnetic Resonance (MR) and Computerized Tomography (CT) cardiac images. We use a multimodal iconic algorithm based on the maximisation of the mutual information of the joint histogram of two images. We apply it to the registration of MR and CT cardiac images. The purpose is to determine in a (3D+t) CT data volume, short-axis slices that correspond to the (2D+t) short-axis MR slices, acquired on the same patient. The couples of images should be similar according to their spatial position, orientation and cardiac cycle phase. We used the Powell's direction set optimization method for the maximisation of the mutual information, which gives good results with an appropriate initialization.

Segmentation of cardiac cine-MR images and myocardial deformation assessment using level set methods.

In this paper, we present an original method to assess the deformations of the left ventricular myocardium on cardiac cine-MRI. First, a segmentation process, based on a level set method is directly applied on a 2D + t dataset to detect endocardial contours. Second, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process based on a level set approach. Finally, local measurements of myocardial deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results to the measurements achieved on the same patients by an expert using the semi-automated HARP reference method on tagged MR images.