high performance computing on graphics processing units: hgpu.org

PURPOSE: We present a system which supports deformable image registration guided by a haptic device. METHODS: The haptic device is tied to a block matching method where a set of uniformly distributed control points determine the block positions. Each control point constitutes a particle in a mass spring grid which limits the space of allowed movements to elastic movements. Control points are manipulated by the haptic device, and the negative gradient of the similarity metric over the corresponding block is rendered as a force on the haptic device guiding the user to a minimum of the optimization landscape. Fast update of forces was achieved by exploiting the GPU for computations of the similarity metric and for interpolation of the deformation field. RESULTS: We show that haptic guided registration facilitates faster and improved registration compared to using a purely visual alignment in a user study on synthetic images. We also demonstrate feasibility of applying the system on medical images through a comparison with an automatic block matching algorithm. A radiologist performing registration with the haptic registration system posted faster registration times and better registration results than the automatic block matching algorithm when using identical grid and block sizes. CONCLUSIONS: Possible applications of the system are refinement of registration results from automatic registration methods and construction of initial state used in automatic deformable registration methods.