AUTHOR=Liu Yixun , Kot Andriy , Drakopoulos Fotis , Yao Chengjun , Fedorov Andrey , Enquobahrie Andinet , Clatz Olivier , Chrisochoides Nikos P. TITLE=An ITK implementation of a physics-based non-rigid registration method for brain deformation in image-guided neurosurgery JOURNAL=Frontiers in Neuroinformatics VOLUME=8 YEAR=2014 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2014.00033 DOI=10.3389/fninf.2014.00033 ISSN=1662-5196 ABSTRACT=

As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block matching filter on average is about 10 times faster when 12 hyperthreaded multi-cores are used and about 83 times faster when the NVIDIA Tesla GPU is used in Dell Workstation.