In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is proposed. The algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. The EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate a-priori information into the classification process. The probabilistic cardiac atlas has been constructed from the manual segmentations of 3D cardiac image sequences of 14 subjects. It provides space and time-varying probability maps for the left and right ventricle, the myocardium, and background structures such as the liver, stomach, lungs and skin. In addition to the probabilistic cardiac atlas, the segmentation algorithm incorporates spatial and temporal contextual information by using 4D Markov Random Fields (MRF). Validation against manual segmentations and computation of the correlation between manual and automatic segmentation on 249 3D volumes were calculated. Results show that the procedure can successfully segment the left ventricle (LV) (r=0.95), myocardium (r=0.83) and right ventricle (RV) (r=0.91).

Abstract. We propose a novel method for fully automated segmentation and tracking of the myocardium and left and right ventricles (LV and RV) using 4D MR images. The method uses non-rigid registration to elastically deform a cardiac atlas built automatically from 14 normal subjects. The registration yields robust performance and is particularly suitable for processing a sequence of 3D images in a cardiac cycle. Transformations are calculated to obtain the deformations between images in a sequence. The registration algorithm aligns the cardiac atlas to a subject specific atlas of the sequence generated with the transformations. The method relates images spatially and temporally and is suitable for measuring regional motion and deformation, as well as for labelling and tracking specific regions of the heart. In this work experiments for the registration, segmentation and tracking of a cardiac cycle are presented on nine MRI data sets. Validation against manual segmentations and computation of the correlation between manual and automatic tracking and segmentation on 141 3D volumes were calculated. Results show that the procedure can accurately track the left ventricle (r=0.99), myocardium (r=0.98) and right ventricle (r=0.96). Results for segmentation are also obtained for left ventricle (r=0.92), myocardium (r=0.82) and right ventricle (r=0.90).

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We describe a registration and tracking technique to integrate cardiac X-ray images and cardiac magnetic resonance (MR) images acquired from a combined X-ray and MR interventional suite (XMR). Optical tracking is used to determine the transformation matrices relating MR image coordinates and X-ray image coordinates. Calibration of X-ray projection geometry and tracking of the X-ray C-arm and table enable three-dimensional (3-D) reconstruction of vessel centerlines and catheters from bi-plane X-ray views. We can, therefore, combine single X-ray projection images with registered projection MR images from a volume acquisition, and we can also display 3-D reconstructions of catheters within a 3-D or multi-slice MR volume. Registration errors were assessed using phantom experiments. Errors in the combined projection images (two-dimensional target registration error--TRE) were found to be 2.4 to 4.2 mm, and the errors in the integrated volume representation (3-D TRE) were found to be 4.6 to 5.1 mm. These errors are clinically acceptable for alignment of images of the great vessels and the chambers of the heart. Results are shown for two patients. The first involves overlay of a catheter used for invasive pressure measurements on an MR volume that provides anatomical context. The second involves overlay of invasive electrode catheters (including a basket catheter) on a tagged MR volume in order to relate electrophysiology to myocardial motion in a patient with an arrhythmia. Visual assessment of these results suggests the errors were of a similar magnitude to those obtained in the phantom measurements.

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