[dmritool-discussion] new commits on C++11 and sampling scheme
Jian Cheng
jian.cheng.1983 at gmail.com
Tue Feb 28 12:21:18 PST 2017
Dear all,
I updated dmritool for C++11 with better efficiency.
I also released some codes for algorithms and demos on uniform single
and multiple shell sampling scheme design.
If you are interested in sampling scheme design, please check the
tutorial for the updates.
https://diffusionmritool.github.io/tutorial_qspacesampling.html
Here are the updates in details (see the news
https://diffusionmritool.github.io/news.html#dmritool-now-uses-c-11):
* We use C++11 in DMRITool now.
o NDArray now is more efficient with C++11.
o The codes have to be built with gcc (>= 4.8), ITK (>= 4.9).
Please check the building instruction
<https://diffusionmritool.github.io/building.html>.
* Some algorithms and demos on sampling scheme design are released.
o Please check the updated tutorial on sampling scheme design
<https://diffusionmritool.github.io/tutorial_qspacesampling.html>.
o 1-Opt: SamplingSchemeQSpace1OptEstimation
<https://diffusionmritool.github.io/commands/SamplingSchemeQSpace1OptEstimation.html>,
a new greedy algorithm which refines a given initialization. It
can fix a known issue of IMOC
<https://diffusionmritool.github.io/commands/SamplingSchemeQSpaceIMOCEstimation.html>
when the number of samples is large. See the tutorial
<https://diffusionmritool.github.io/tutorial_qspacesampling.html#sampling-schemes-by-imoc-1-opt-cnlo>.
o CNLO: OptimalSamplingSingleShellCNLO
<https://diffusionmritool.github.io/matlabfiles/OptimalSamplingSingleSubset.html>
for single-shell scheme design.
o CNLO: OptimalSamplingMultiShellCNLO
<https://diffusionmritool.github.io/matlabfiles/OptimalSamplingMultiShellCNLO.html>
for multiple-shell scheme design.
o jointly use IMOC + 1-Opt + CNLO for sampling scheme design:
+ demo for single shell scheme
<https://diffusionmritool.github.io/demos/demo_singleshell_IMOC_1Opt_CNLO.html>
+ demo for multiple shell scheme
<https://diffusionmritool.github.io/demos/demo_mutishell_IMOC_1Opt_CNLO.html>
Thanks.
best,
Jian Cheng
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