Registration of multiple 3D ultrasound sectors in order to provide an extended field of view is important for the appreciation of larger anatomical structures at high spatial and temporal resolution. In this paper, we present a method for fully automatic spatio-temporal registration between two partially overlapping 3D ultrasound sequences. The temporal alignment is solved by aligning the normalized cross correlation-over-time curves of the sequences. For the spatial alignment, corresponding 3D Scale Invariant Feature Transform (SIFT) features are extracted from all frames of both sequences independently of the temporal alignment. A rigid transform is then calculated by least squares minimization in combination with random sample consensus. The method is applied to 16 echocardiographic sequences of the left and right ventricles and evaluated against manually annotated temporal events and spatial anatomical landmarks. The mean distances between manually identified landmarks in the left and right ventricles after automatic registration were (mean ± SD) 4.3 ± 1.2 mm compared to a reference error of 2.8 ± 0.6 mm with manual registration. For the temporal alignment, the absolute errors in valvular event times were 14.4 ± 11.6 ms for Aortic Valve (AV) opening, 18.6 ± 16.0 ms for AV closing, and 34.6 ± 26.4 ms for mitral valve opening, compared to a mean inter-frame time of 29 ms.

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The use of three-dimensional (3-D) echocardiography is limited by signal dropouts and narrow field of view. Data compounding is proposed as a solution to overcome these limitations by combining multiple 3-D recordings to form a wide field of view. The first step of the solution requires registration between the recordings both in the spatial and temporal dimension for dynamic organs such as the heart. Accurate registration between the individual echo recordings is crucial for the quality of compounded volumes. A temporal registration method based on a piecewise one-dimensional cubic B-spline in combination with multiscale iterative Farnebäck optic flow method for spatial registration was described. The temporal registration method was validated on in vivo data sets with annotated timing of mitral valve opening. The spatial registration method was validated using in vivo data and compared to registration with Procrustes analysis using manual contouring as a benchmark. The spatial accuracy was assessed in terms of mean of absolute distance and Hausdorff distance between the left ventricular contours. The results showed that the temporal registration accuracy is in the range of half the time resolution of the echo recordings and the achieved spatial accuracy of the proposed method is comparable to manual registration.

Temporal alignment of echocardiographic sequences enables fair comparisons of multiple cardiac sequences by showing corresponding frames at given time points in the cardiac cycle. It is also essential for spatial registration of echo volumes where several acquisitions are combined for enhancement of image quality or forming larger field of view. In this study, three different image-based temporal alignment methods were investigated. First, a method based on dynamic time warping (DTW). Second, a spline-based method that optimized the similarity between temporal characteristic curves of the cardiac cycle using 1D cubic B-spline interpolation. Third, a method based on the spline-based method with piecewise modification. These methods were tested on in-vivo data sets of 19 echo sequences. For each sequence, the mitral valve opening (MVO) time was manually annotated. The results showed that the average MVO timing error for all methods are well under the time resolution of the sequences.

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