A patch-based framework for new ITK functionality: Joint fusion, denoising, and non-local super-resolution

Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3570
In an earlier Insight Journal article, we introduced an ITK implementation of the adaptive patch-based image denoising algorithm described in [3]. We follow-up up that offering with a generalized non-local, patch-based ITK class framework and a refactored denoising class. In addition, we provide two ITK implementations of related, well-known algorithms. The first is a non-local super resolution method described in [1, 2]. The second is the multivariate joint label fusion algorithm of [4, 5] with additional extensions, denoted as “joint intensity fusion”, which will be described in a forthcoming manuscript. Accompanying these ITK classes are documented programming interfaces which use our previously introduced unique command line interface routines. Several 2-D examples on brain imaging data are provided to qualitatively demonstrate performance.
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Comment by Nick Tustison yellow
Here's a direct link to the github repo:

Comment by Pedro Henrique Bandeira Diniz yellow
Actually the .zip file is corrupted
Comment by Pedro Henrique Bandeira Diniz yellow
I think "download all" link is corrupted. Could u verify? Thanks in advance.

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Categories: Atlas-based segmentation, Filtering, Resampling, Segmentation
Keywords: non-local, Patch based , image denoising, super-resolution, joint fusion
Toolkits: ITK
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