The creation of 2D ultrasound mosaics is becoming a common clinical practice with a high clinical value. The next step coming along with the increasing availability of 2D array transducers is the creation of 3D mosaics. In the literature of ultrasound registration, the alignment of multiple images has not yet been addressed. Therefore, we propose registration strategies, which are able to cope with problems arising by multiple image alignment. We use pair-wise registration with a consecutive Lie normalization and simultaneous registration, which urges the usage of multivariate similarity measures. In this thesis, we propose alternative multivariate extensions based on a maximum likelihood framework. Due to the higher computational cost of simultaneous registration, we describe possibilities for speeding them up, among others, the usage of a stochastic pyramid. We also present methods to reduce speckle noise and to detect shadow in ultrasonographic volumes, to improve the overall registration performance. For the compounding of the final volume, a variety of approaches are listed, ranging from general to advanced ones. Experimental results, on multiple ultrasound data sets, show the good performance of the proposed registration strategies and similarity measures.     «

The creation of 2D ultrasound mosaics is becoming a common clinical practice with a high clinical value. The next step coming along with the increasing availability of 2D array transducers is the creation of 3D mosaics. In the literature of ultrasound registration, the alignment of multiple images has not yet been addressed. Therefore, we propose registration strategies, which are able to cope with problems arising by multiple image alignment. We use pair-wise registration with a consecutive Lie...     »