The response of pulmonary artery pressure to high altitude has not been studied in children. It is also not known whether the individual response is hereditary. Therefore, the response of pulmonary artery pressure to high altitude was measured in pre-pubertal children in comparison to that in their biological fathers.Echocardiography was performed at 450 m and over 3 days at 3,450 m. Systolic pulmonary artery pressure was estimated from the pressure gradient of tricuspid regurgitation.The increase in pulmonary artery pressure in children was greater than that in adults at day 1 of high altitude (15.5¡9.1 versus 7.9¡6.4 mmHg), but returned to adult levels on day 2. The increase in pulmonary artery pressure from low to high altitude of each child correlated with that in the father.Pre-pubertal children transiently develop greater pulmonary hypertension than their fathers when exposed to high altitude. The individual response of pulmonary pressure to high altitude seems to be at least partly hereditary.

Wavelet-based methods have become most popular for the compression of two-dimensional medical images and sequences. The standard implementations consider data sizes that are powers of two. There is also a large body of literature treating issues such as the choice of the "optimal" wavelets and the performance comparison of competing algorithms. With the advent of telemedicine, there is a strong incentive to extend these techniques to higher dimensional data such as dynamic three-dimensional (3-D) echocardiography [four-dimensional (4-D) datasets]. One of the practical difficulties is that the size of this data is often not a multiple of a power of two, which can lead to increased computational complexity and impaired compression power. Our contribution in this paper is to present a genuine 4-D extension of the well-known zerotree algorithm for arbitrarily sized data. The key component of our method is a one-dimensional wavelet algorithm that can handle arbitrarily sized input signals. The method uses a pair of symmetric/antisymmetric wavelets (10/6) together with some appropriate midpoint symmetry boundary conditions that reduce border artifacts. The zerotree structure is also adapted so that it can accommodate noneven data splitting. We have applied our method to the compression of real 3-D dynamic sequences from clinical cardiac ultrasound examinations. Our new algorithm compares very favorably with other more ad hoc adaptations (image extension and tiling) of the standard powers-of-two methods, in terms of both compression performance and computational cost. It is vastly superior to slice-by-slice wavelet encoding. This was seen not only in numerical image quality parameters but also in expert ratings, where significant improvement using the new approach could be documented. Our validation experiments show that one can safely compress 4-D data sets at ratios of 128:1 without compromising the diagnostic value of the images. We also display some more extreme compression results at ratios of 2000:1 where some key diagnostically relevant key features are preserved.

We present a new framework to estimate and visualize heart motion from echocardiograms. For velocity estimation, we have developed a novel multiresolution optical flow algorithm. In order to account for typical heart motions like contraction/expansion and shear, we use a local affine model for the velocity in space and time. The motion parameters are estimated in the least-squares sense inside a sliding spatio-temporal window.The estimated velocity field is used to track a region of interest which is represented by spline curves. In each frame, a set of sample points on the curves is displaced according to the estimated motion field. The contour in the subsequent frame is obtained by a least-squares spline fit to the displaced sample points. This ensures robustness of the contour tracking. From the estimated velocity, we compute a radial velocity field with respect to a reference point. Inside the time-varying region of interest, the radial velocity is color-coded and superimposed on the original image sequence in a semi-transparent fashion. In contrast to conventional Tissue Doppler methods, this approach is independent of the incident angle of the ultrasound beam.The motion analysis and visualization provides an objective and robust method for the detection and quantification of myocardial malfunctioning. Promising results are obtained from synthetic and clinical echocardiographic sequences.

High resolution multidimensional image data yield huge datasets. For compression and analysis, 2D approaches are often used, neglecting the information coherence in higher dimensions, which can be exploited for improved compression. We designed a wavelet compression algorithm suited for data of arbitrary dimensions, and assessed its ability for compression of 4D medical images. Basically, separable wavelet transforms are done in each dimension, followed by quantization and standard coding. Results were compared with conventional 2D wavelet. We found that in 4D heart images, this algorithm allowed high compression ratios, preserving diagnostically important image features. For similar image quality, compression ratios using the 3D/4D approaches were typically much higher (2-4 times per added dimension) than with the 2D approach. For low-resolution images created with the requirement to keep predefined key diagnostic information (contractile function of the heart), compression ratios up to 2000 could be achieved. Thus, higher-dimensional wavelet compression is feasible, and by exploitation of data coherence in higher image dimensions allows much higher compression than comparable 2D approaches. The proven applicability of this approach to multidimensional medical imaging has important implications especially for the fields of image storage and transmission and, specifically, for the emerging field of telemedicine.

Marker-based optical tracking systems are often used to track objects that are equipped with a certain number of passive or active point markers. Fixed configurations of these markers, so-called rigid bodies, can be detected by, for example, infrared stereo-based camera systems, and their position and orientation can be reconstructed by corresponding tracking algorithms. The main issue in designing the geometrical constellation of these markers and their 3D positions is to allow robust identification and tracking of multiple objects, and this design process is considered to be an essential and challenging task. At present, the design process is based on trial-and-error: the designer constructs a marker configuration, evaluates it in a given setup, and rearranges the marker positions within the configuration if necessary. Even though single ready-made rigid bodies permit sufficiently good tracking, it is not ensured that the corresponding arrangements of markers meet any quality criteria in terms of reliability and robustness. Furthermore, it is unclear whether it is possible to add further rigid bodies to the setup which are sufficiently distinguishable from the given ones. In this paper, we present an approach to semi-automatically generate marker-based rigid bodies which are optimal with respect to the properties of the tracking system for which they are used, e.g., granularity, accuracy, or jitter. Our procedure which is aimed at supporting the design process as well as improving tracking generates configurations for several devices associated with an arbitrary set of point-based markers. We discuss both the technical background of our approach and the results of an evaluation comparing the tracking quality of commercially available devices to the rigid bodies generated by our approach.