@ARTICLE{DrRuSt03, author = {Robert Strzodka and Marc Droske and Martin Rumpf}, title = {Fast Image Registration in {DX9} Graphics Hardware}, journal = {Journal of Medical Informatics and Technologies}, year = {2003}, volume = {6}, pages = {43--49}, month = {Nov}, abstract = {The analysis of image time series requires a correlation of the information between two images. The gradient flow registration is a method for correlating this information by successively minimizing an appropriate energy along its gradient. A graphics hardware implementation of this approach to image registration is presented. The gradient flow formulation makes use of a robust multi-scale regularization, an efficient multi-grid solver and an effective time-step control. The locality of the involved operations implies a data-flow which is very well suited for an acceleration in the streaming architecture of the DX9 graphics hardware. Therefore the implementation promises very high performance, however the appropriate graphics hardware is not available before February. Currently the examples have been computed on a emulator, but the implementation will run unchanged on the soon released graphics hardware.}, pdf = {http://numod.ins.uni-bonn.de/research/papers/public/DrRuSt03.pdf}, html = {http://numerik.math.uni-duisburg.de/people/strzodka/projects/IP/} }