The aim of this work is to create a library for Boolean operations on 3D polygonal meshes. Resulting library has to support open models, its memory requirements shouldn't exceed those of existing solutions and it should, ideally, support multiple models. Most of the existing solutions are vulnerable to arithmetic inaccuracies, or do not support open meshes. The solution is based on Adaptive Mesh Booleans method which treats input models as adaptive surfaces. This method assumes that input models can be arbitrarily refined and no individual polygon is particularly important. Instead of computing exact polygon intersections, the input meshes are refined in intersection regions, intersecting polygons are discarded and created holes are closed. Advantages of this approach are robustness against numerical errors, support for open meshes, possibility to trade accuracy for computation time and ability to solve cases like co-planar and near-coincident regions. The resulting library offers three Boolean operations: union, difference and intersection.

This thesis presents various approaches for race track surface reconstruction based on different algorithms designated for these purposes. In addition to surface reconstruction it also offers proposals for polygon mesh filling in the unscanned areas around the track.

The dissertation thesis deals with 3D reconstruction of the temporomandibular joint from 2D slices of tissue obtained by magnetic resonance. The current practice uses 2D MRI slices in diagnosing. 3D models have many advantages for the diagnosis, which are based on the knowledge of spatial information. Contemporary medicine uses 3D models of tissues, but with the temporomandibular joint tissues there is a problem with segmenting the articular disc. This small tissue, which has a low contrast and very similar statistical characteristics to its neighborhood, is very complicated to segment. For the segmentation of the articular disk new methods were developed based on the knowledge of the anatomy of the joint area of the disk and on the genetic-algorithm-based statistics. A set of 2D slices has different resolutions in the x-, y- and z-axes. An up-sampling algorithm, which seeks to preserve the shape properties of the tissue was developed to unify the resolutions in the axes. In the last phase of creating 3D models standard methods were used, but these methods for smoothing and decimating have different settings (number of polygons in the model, the number of iterations of the algorithm). As the aim of this thesis is to obtain the most precise model possible of the real tissue, it was necessary to establish an objective method by which it would be possible to set the algorithms so as to achieve the best compromise between the distortion and the model credibility achieve.