Scale Invariant Metrics of Volumetric Datasets
Name
Raviv-2015-Scale invariant.pdf
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2.07 MB
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Checksum (MD5)
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Author(s)
Raskar, Ramesh
Raviv, Raviv
Date Issued
February 2015
Journal
SIAM Journal on Imaging Sciences
Publisher
Society for Industrial and Applied Mathematics
Citation
Raviv, Dan, and Ramesh Raskar. “Scale Invariant Metrics of Volumetric Datasets.” SIAM J. Imaging Sci. 8, no. 1 (January 2015): 403–425. © 2015, Society for Industrial and Applied Mathematics
Version
Final published version
Abstract
Nature reveals itself in similar structures of different scales. A child and an adult share similar organs yet dramatically differ in size. Comparing the two is a challenging task to a computerized approach as scale and shape are coupled. Recently, it was shown that a local measure based on the Gaussian curvature can be used to normalize the local metric of a surface and then to extract global features and distances. In this paper we consider higher dimensions; specifically, we construct a scale invariant metric for volumetric domains which can be used in analysis of medical datasets such as computed tomography (CT) and magnetic resonance imaging (MRI).
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1137/140987675
