title: An Example-Based Brain MRI Simulation Framework.
abstract: The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
authors.forename: Qing
authors.initials: Q
authors.lastname: He
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
authors.forename: Snehashis
authors.initials: S
authors.lastname: Roy
authors.affiliation: Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
authors.forename: Amod
authors.initials: A
authors.lastname: Jog
authors.affiliation: Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
authors.forename: Dzung L
authors.initials: DL
authors.lastname: Pham
keywords: brain MRI simulation; example based method; inhomogeneity field; regression ensemble