@inproceedings{54e153f09115415dbe6322a805a9d33d,
title = "Sparse representation for white matter fiber compression and calculation of inter-fiber similarity",
abstract = "Recent years have brought about impressive reconstructions of white matter architecture, due to the advance of increasingly sophisticated MRI based acquisition methods and modeling techniques. These result in extremely large sets of streamelines (fibers) for each subject. The sets require large amount of storage and are often unwieldy and difficult to manipulate and analyze. We propose to use sparse representations for fibers to achieve a more compact representation. We also propose the means for calculating inter-fiber similarities in the compressed space using a measure, which we term: Cosine with Dictionary Similarity Weighting (CWDS). The performance of both sparse representations and CWDS is evaluated on full brain fiber-sets of 15 healthy subjects. The results show that a reconstruction error of slightly below 2 mm is achieved, and that CWDS is highly correlated with the cosine similarity in the original space.",
author = "Moreno, {Gali Zimmerman} and Guy Alexandroni and Nir Sochen and Hayit Greenspan",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; null ; Conference date: 17-10-2016 Through 21-10-2016",
year = "2017",
doi = "10.1007/978-3-319-54130-3_11",
language = "אנגלית",
isbn = "9783319541297",
series = "Mathematics and Visualization",
publisher = "Springer Heidelberg",
pages = "133--143",
editor = "Andrea Fuster and Yogesh Rathi and Marco Reisert and Enrico Kaden and Aurobrata Ghosh",
booktitle = "Computational Diffusion MRI - MICCAI Workshop",
address = "גרמניה",
}