Patch-Based Discrete Registration of Clinical Brain Images
Name
nihms837299.pdf
Description
Accepted version
Size
809.37 KB
Format
Unknown
Checksum (MD5)
8fb28ec89d26689289974d72187acee3
Author(s)
Dalca, Adrian Vasile
Rost, Natalia S.
Bobu, Andreea
Golland, Polina
Date Issued
2016
Publisher
Springer Nature America, Inc
Citation
Dalca, Adrian V., Bobu, Andreea, Rost, Natalia S. and Golland, Polina. 2016. "Patch-Based Discrete Registration of Clinical Brain Images."
Version
Author's final manuscript
Abstract
© Springer International Publishing AG 2016. We introduce a method for registration of brain images acquired in clinical settings. The algorithm relies on three-dimensional patches in a discrete registration framework to estimate correspondences. Clinical images present significant challenges for computational analysis. Fast acquisition often results in images with sparse slices, severe artifacts, and variable fields of view. Yet, large clinical datasets hold a wealth of clinically relevant information. Despite significant progress in image registration, most algorithms make strong assumptions about the continuity of image data, failing when presented with clinical images that violate these assumptions. In this paper, we demonstrate a non-rigid registration method for aligning such images. The method explicitly models the sparsely available image information to achieve robust registration. We demonstrate the algorithm on clinical images of stroke patients. The proposed method outperforms state of the art registration algorithms and avoids catastrophic failures often caused by these images. We provide a freely available open source implementation of the algorithm.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/978-3-319-47118-1_8
