We present a longitudinal MR simulation framework which simulates the future neurodegenerative progression by outputting the predicted follow-up MR image and the voxel-based morphometry (VBM) map. This framework expects the patients to have at least 2 historical MR images available. The longitudinal and cross-sectional VBM maps are extracted to measure the affinity between the target subject and the template subjects collected for simulation. Then the follow-up simulation is performed by resampling the latest available target MR image with a weighted sum of non-linear transformations derived from the best-matched templates. The leave-one-out strategy was used to compare different simulation methods. Compared to the state-of-the-art voxel-based method, our proposed morphometry-based simulation achieves better accuracy in most cases.
@article{arxiv.1508.05683,
title = {Morphometry-Based Longitudinal Neurodegeneration Simulation with MR Imaging},
author = {Siqi Liu and Sidong Liu and Sonia Pujol and Ron Kikinis and Dagan Feng and Michael Fulham and Weidong Cai},
journal= {arXiv preprint arXiv:1508.05683},
year = {2015}
}
Comments
6 pages, 3 figures, preprint for journal publication