@inproceedings{7a6dca9e81924bbcab7a2823f5ee4454,
title = "Rank-2 model-order selection in diffusion tensor MRI: Infromation complexity based on the total Kullback-Leibler divergence",
abstract = "Diffusion-weighted MRI (DW-MRI) can assess the integrity of white matter (WM) structures in the human brain. Multi-compartment analysis of DW-MRI requires an estimate of the number of compartments to permit unbiased estimation of the diffusion shape in a single fibers as well as crossing fascicles. We propose a new, rotation-invariant measure to assess the suitability of a model by a measure for information complexity (ICOMP) based on the total Kullback-Leibler divergence (TKLD). ICOMP-TKLD is evaluated on simulated data and on data from the Human Connectome Project. Compared to the state-of-the-art, ICOMP-TKLD is the only method that yields reliable model-order selection in both homogeneous and heterogeneous WM regions. Therefore, ICOM-TKLD may open the way for structure-adaptive estimation of diffusion properties of the entire brain.",
keywords = "DTI, model selection",
author = "Jianfei Yang and Poot, {Dirk H.J.} and Caan, {Matthan W.A.} and Vos, {Frans M.} and {Van Vliet}, {Lucas J.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "https://doi.org/10.1109/ISBI.2015.7164022",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "926--929",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
address = "United States",
}