A lot of medical diagnostics problems are related to the reconstruction of three dimension (3D) images from the cross sections of the regions of interest. Such reconstructions are very desirable for evaluation of disease or planning of surgical treatment. This paper reviews recent 3D preprocessing work of authors in human brain blood vessels structure recognition and localization of aneurysms as well as analysis of the right ventricular of the human heart. Here we present some approximation techniques for generation of reformatted images.

Abstract. A right heart ventricle has a complex and irregular shape, this obscures analysis of ventricle surface movements. We are trying to quantitative evaluate morphological changes of right ventricle surface, these changes appear during heart beat cycle, between different age groups, due to heart diseases, and other factors. A method for such evaluation would open new possibilities for insights into heart function, disease course extrapolation and other. We see this as a multistage task, where the first step is partitioning whole surface into smaller, more manageable regions, and the second step is to analyse each region separately. In this paper we present a new algorithm for partitioning the medial axis of right heart ventricle surface. Such partitioning leads to division of surface into smaller regions with clear shape. The proposed algorithm first computes medial axis from sampled ventricle surface. Later, the medial axis is filtered and smoothed, and third, we compute curvature map and use it as weights in Dijkstra's algorithm for curvature guided partitioning. Algorithm provides a way for fully automatic partitioning of medial manifold into separate medial scaffolds and a semi automatic way for additional curvature based division of medial scaffolds.

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