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Stéfan van der Walt
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We are very happy to announce a new release of Diffusion Imaging in Python (Dipy). #neuroscience   #brain   #neuroimaging   #Python   #mri   #scientificresearchpublishing   #neurology  

Here is a summary of the most important new features and developments.

DIPY 0.8.0 (Released on Tuesday, 6 Jan 2015)

Nonlinear Image-based Registration (SyN)

An implementation of the Symmetric Normalization method for nonlinear diffeomorphic registration. This implementation is lightweight, and does not depend on ITK or ANTS. It is written entirely in Python and Cython.

Streamline-based Linear Registration (SLR)

A new method that allows direct registration of bundles of streamlines. Especially useful for creating atlases of specific types of bundles.

Linear Fascicle Evaluation (LiFE)

This is a Python implementation of a new method for evaluation of tractrography solutions.

Sparse Fascicle Model (SFM)

A new signal reconstruction method , added to the large stack of reconstruction models already available in Dipy, including implementations of CSD and SHORE.

Non-local means denoising (NLMEANS)

Denoising is a technique that can boost most of your analysis techniques as it can increase the signal to noise ratio of your data. We started this new module by implementing a very generic denoising technique that can be used also for fMRI and T1 images.

New modular tracking machinery

This is a collection of new objects which allows rapid development of new fiber tracking algorithms. 

In summary, since January 2014 (version 0.7.1), we closed 388 issues and merged 155 pull requests. The project now has a total of more than 4000 commits and 29 contributors.

We would appreciate if you could forward this information to any interested individuals or labs.

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We are excited to finally be releasing "Effective Computation in Physics - Field Guide to Research with Python" published by O'Reilly Media. This has been a labor of us over the past year. You can purchase the book here (http://shop.oreilly.com/product/0636920033424.do) or check out our website (http://physics.codes/) for more information.

We are hoping for friendly technical review comments from readers. We will be incorporating these as we go.  Please understand that as an early release, parts of this book remain "raw and unedited." Many updates have already been made which may not be yet pushed up to the early release version.

We would love to see this be a supplemental course textbook, used as an introduction for new graduate or undergraduate students in research, and so on. if you are an educator and want to use this book in such a capacity, we'd love to hear from you. Now is your opportunity to influence the final product to best fit your needs!

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Ran into this little guy on our jog last night...
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The scikit-image paper is out!

https://peerj.com/articles/453/

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Over the last year I've worked with some awesome folks (+Kester Tong  +Mark Sandler, +Corinna Cortes , +Matthew Turk,  +Gideon Mann  +Arnaud Sahuguet, +Adam Berenzweig) to understand how people collaborate on data analysis and to build better tools to support them. Yesterday, with the help of +Fernando Perez and +Wes McKinney we revealed this work at PyCon APAC.

We've created an interactive, collaborative analytics tool by integrating Google Docs, Chrome, and IPython. You can open a notebook from Drive. You can share notebooks like you would share a Google Doc. You can comment and edit collaboratively, in realtime. There is zero setup, because all the computation happens in Chrome. You can even quickly and easily package your analytics pipeline into a GUI for folks that don't want to program. In effect, you can go from zero to analytics with little impedance.  

What's even better is that you can build on our work. It will all be open source on top of public Google APIs. We'll have a larger Google Research blog post about this work when we release the code and the Chrome application.
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Russian Lunar Lander Prototype Rediscovered | Part-Time Scientists
"An incredible piece of Apollo time space legacy has been rediscovered in a Russian hangar! It's the equivalent of the NASA Apollo program's lunar landing module." 

"From a historical and technical advancement point of view it's actually sad that Russia stopped it's efforts on sending people to the moon after the Apollo program turned out to be a success."

Lunniy Kabina  "lunar cabin" for a single cosmonaut.

Credit: Part-Time Scientists
Part-Time Scientists Website: http://ptscientists.com
Part-Time Scientists Facebook Page:
https://www.facebook.com/PartTimeScientists

+Part-Time Scientists 
+Roscosmos (Unofficial) 
+Johnson Space Center 
+NASA Goddard 
+NASA's Marshall Center 

#Space   #Russia   #Moon   #Lunar   #Lander #Soviet #LK #Spacecraft   #Cosmonaut   #Zond #Roscosmos #Apollo #NASA #ЛК #Россия
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