title: GPU-accelerated interactive visualization and planning of neurosurgical interventions.
abstract: Advances in computational methods and hardware platforms provide efficient processing of medical-imaging datasets for surgical planning. For neurosurgical interventions employing a straight access path, planning entails selecting a path from the scalp to the target area that's of minimal risk to the patient. A proposed GPU-accelerated method enables interactive quantitative estimation of the risk for a particular path. It exploits acceleration spatial data structures and efficient implementation of algorithms on GPUs. In evaluations of its computational efficiency and scalability, it achieved interactive rates even for high-resolution meshes. A user study and feedback from neurosurgeons identified this methods' potential benefits for preoperative planning and intraoperative replanning.
authors.forename: Mario
authors.initials: M
authors.lastname: Rincón-Nigro
authors.forename: Nikhil V
authors.initials: NV
authors.lastname: Navkar
authors.forename: Nikolaos V
authors.initials: NV
authors.lastname: Tsekos
authors.lastname: Zhigang Deng
mesh_terms: D003196:Computer Graphics; D006801:Humans; D019635:Neurosurgical Procedures / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014584:User-Computer Interface