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Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010

Volume 6362 of the series Lecture Notes in Computer Science pp 404-411

High-Fidelity Meshes from Tissue Samples for Diffusion MRI Simulations

  • Eleftheria PanagiotakiAffiliated withCarnegie Mellon UniversityCentre for Medical Image Computing, Department of Computer Science, University College London
  • , Matt G. HallAffiliated withCarnegie Mellon UniversityCentre for Medical Image Computing, Department of Computer Science, University College London
  • , Hui ZhangAffiliated withCarnegie Mellon UniversityCentre for Medical Image Computing, Department of Computer Science, University College London
  • , Bernard SiowAffiliated withCarnegie Mellon UniversityCentre for Medical Image Computing, Department of Computer Science, University College LondonCentre for Advanced Biomedical Imaging, University College London
  • , Mark F. LythgoeAffiliated withCarnegie Mellon UniversityCentre for Advanced Biomedical Imaging, University College London
  • , Daniel C. AlexanderAffiliated withCarnegie Mellon UniversityCentre for Medical Image Computing, Department of Computer Science, University College London

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Abstract

This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.