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Hello everyone,

Haven't written anything in a fair bit of time, but worry not! There is a new release of Dipy with a lot of new examples. This release now contains the Constrained Spherical Deconvolution code in addition to new metrics and reconstruction methods.

The Dipy paper is also out now, in open access. Head over here to check it out.

Some highlights of this new release are

  • Constrained Spherical Deconvolution (CSD)
  • Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE)
  • Sharpening Deconvolution Transform (SDT)
  • Signal-to-noise ratio estimation
  • Parallel processing enabled for all reconstruction models using peaks_from_model
  • Simultaneous peak and ODF visualization
  • Streamtube visualization
  • Electrostatic repulsion for sphere generation
  • Connectivity matrices and density maps
  • Streamline filtering through specific ROIs using target
  • Brain extraction and foreground extraction using median_otsu
  • RESTORE fitting for DTI
  • Westin's Tensor maps
  • Access to more publicly available datasets directly through Dipy functions.
  • 3x more tutorials than previous release

We also hope to have new denoising algorithms for the next version, the Non Local Means algorithm is already in a PR for the next release ;)

Also, our lab has submitted some abstracts to ISMRM 2014 and HBM 2014, so look out for that. I'll post about it when/if they get accepted, but be sure to check out our new work on tractography, HARDI and fibers specific metrics, new DSI processing techniques, some Dipy abstracts by Elef and my new machine learning, non local aware denoising technique.

And with that, until next time.


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