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Software

(this page is currently under development)

  • Medical Image Computing
    • BioFEM

      A near real-time web-service that relies on an efficient and fault-tolerant distributed library (developed in collaboration with our colleagues at Harvard Medical School and INRIA), for non-rigid registration of brain MR images. This software, for the first time in clinical practice (on 8th of November 2005), was used to complete (on several clusters with about 150 nodes at W&M) the non-rigid registration between pre-operative MRI and fMRI and intra-operative MRI during an open brain surgery at Brigham and Women's Hospital (BWH). During the last year this work was used routinely (at least once a month) at BWH for clinical studies. The results of these activities are presented in NeuroImageJournal07, IEEE/ACM SC06.

    • RGMesh

      An open source implementation of an adaptive tetrahedral mesh generator particularly targeted for non-rigid FEM registration of MR images. While many medical imaging applications require robust mesh generation, there are few codes available. Moreover, most of the practical implementations are commercial. The algorithm we have implemented has been previously evaluated for simulations of highly deformable objects, and the preliminary results show its applicability to the targeted application. The implementation we describe is open source and will be available within Insight Toolkit.

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  • N-D Signed Parallel Exact Euclidean Distance Transform
An open software for three-dimensional signed parallel implementation of the exact Euclidean distance transform algorithm developed by Maurer et al. with a theoretical complexity of O(n/p) for n voxels and p threads. Through this parallelization and efficient use of data structures we obtain approximately 3 times mean speedup on standard tests on a 4-processor machine compared with the current ITK exact Euclidean distance transform filter.

  • Accuracy Assessment for Image Alignment of Brain MRI

An open software implement and an error estimation protocol in the Insight Toolkit (ITK) for assessing the accuracy of image alignment. We base this error estimation on a robust version of the HausdorffDistance (HD) metric applied to the recovered edges of the images. The robust modifications we introduce to the HD metric significantly reduce the amount of outliers in the local distance error estimation. We evaluate the accuracy of our protocol on synthetically deformed images. We provide the source code and datasets to reproduce this evaluation. The proposed method is shown to improve error assessment when it is compared with conventional HD methods. This approach has many applications including local estimation and visual assessment of registration error and registration parameter selection.

  • Parallel Mesh Generation
    • Medial Axis Domain Decomposition
    • Parallel Constrained Delaunay Mesh (PCDM) Generation
    • Parallel Uniform Delaunay Mesh Refinement (PDR)
    • Parallel Graded Delaunay Refinement Method
    • Parallel Advancing Front Method
    • Parallel Terminal Edge Bisection
    • Parallel Out-of-Core for Constrained Delaunay Mesh
    • Parallel Out-of-Core Delaunay Refinement
    • Multigrain Parallel Delaunay Mesh Generation
    • Parallel Optimistic Delaunay Mesh Refinement

  • Parallel Computing
    • DMCS

      The Data Movement and Control Substrate (DMCS) implements low-latency and one-sided message passing communication primitives using Active Messages paradigm.

    • MOL

      Mobile Object Layer (MOL) implements (on top of DMCS) a global address space and automatic message forwarding in the context of data migration

    • CLAM

      The Communication Layer for Asynchronous Mobile (CLAM) computations is designed to combine the functionality of DMCS and MOL in order to improve efficiency and incorporate the lessons we learned from the use of its predecessor systems

    • LBL

      The Load Balancing Layer (LBL) provides support for dynamic load balancing; LBL has been implemented on top of DMCS/MOL and CLAM.

    • CrayDMCS

      The CrayDMCS library implements DMCS on top of Remote Memory Access Communication subsystem for the Cray XT3 architecture

If you have any suggestion for this page, please contact Dr. Nikos Chrisochoides.