This paper presents a study aimed to the realization of a novelmultiresolution registration framework. The transformationfunction is computed iteratively as a composition of local deformationsdetermined by the maximization of mutual information.At each iteration, local transformations are joint together using fuzzy kernel regression. This technique represents the core of the mothod and it’s formally described from a probabilistic perspective. It avoids blocking artifacts and allows to keep the final deformation spatially congruent and smooth.Both qualitative and quantitative experimental results show that this approach is equally effective for registering datasets acquired from both single and multiple diagnostic modalities.
|Numero di pagine||4|
|Stato di pubblicazione||Published - 2009|
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Signal Processing