Collaboration:College of William and Mary

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Abstract

This project has 3 goals:

Deliver guaranteed quality Image-to-Mesh (I2M) conversion tools for non-rigid registration of brain MRI. Specifically, we are interested to extend, for medical images, the traditional Delaunay-based mesh generation methods and develop a prototype software module for real-time I2M conversion that will simultaneous address four fundamental I2M conversion problems: image fidelity, sliver elimination, and guaranteed gradation and size optimality of the mesh as well termination of the FE-mesh process.
Develop real-time non-rigid registration of MRI images to meet the time constrains imposed by neurosurgery. Specifically use cooperative hardware architectures (based on multi-core and GPUs) that can be easily deployed in (or next to) the Operating Room without hindering routine surgery procedures to implement real-time non-rigid registration software which is accurate and robust.
improve accuracy of non-rigid registration of brain MRI by utilizing the resources of the TeraGrid infrastructure. Our first objective is to perform a feasibility study to exploit the use distributed grid computing resources in order to provide computational platform for image processing during image-guided neurosurgery. In addition we want to demonstrate that we can utilize the vast resources of nation-wide platforms like the TeraGrid to facilitate large experimental studies of image processing algorithms to improve our understanding of their behavior under different inputs.

This project is a funded in part from NSF and John Simon Guggenheim Foundation