Registration-based initialization during radiation therapy planning
Girish Gopalakrishnan, Rakesh Mullick · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
An established challenge in the field of image analysis has been the registration of images having a large initial misalignment. For example in chemo and Radiation Therapy Planning (RTP), there is often a need to register an image delineating a specific anatomy (usually in the surgery position) with that of a whole body image (obtained preoperatively). In such a scenario, there is room for a large misalignment between the two images that are required to be aligned. Large misalignments are traditionally handled in two ways: 1) Semi-automatically with a user initialization or 2) With the help of the origin fields in the image header. The first approach is user dependant and the second method can be used only if the two images are obtained from the same scanner with consistent origins. Our methodology extends a typical registration framework by selecting components that are capable of searching a large parameter space without settling on local optima. We have used an optimizer that is based on an Evolutionary Scheme along with an information theory based similarity metric that can address these needs. The attempt in this study is to convert a large misalignment problem to a small misalignment problem that can then be handled using application specific registration algorithms. Further improvements along local areas can be obtained by subjecting the image to a non-rigid transformation. We have successfully registered the following pairs of images without any user initialization: CTAC - simCT (neuro, lungs); MRPET/ CT (neuro, liver); T2-SPGR (neuro).