ANN: DIPY 0.13.0

[Eleftherios Garyfallidis]

Hello all,

We are happy to announce a new public release of DIPY. This is mostly a
maintenance release with extra fixes, speedups and minor changes of
dependencies.

*DIPY 0.13 (Tuesday, 24 October 2017)*

This release received contributions from 13 developers (the full release
notes are at: http://nipy.org/dipy/release0.13.html)

*Highlights of this release include:*

- Faster Local PCA implementation.
- Fixed different issues with OpenMP and Windows / OSX.
- Replacement of cvxopt module by cvxpy.
- Replacement of Pytables module by h5py.
- Updated API to support latest numpy version (1.14).
- New user interfaces for visualization.
- Large documentation update.

To upgrade, run the following command in your terminal:

*pip install --upgrade dipy*

or

*conda install -c conda-forge dipy*


For any questions go to http://dipy.org, or send an e-mail to
neuroimag...@python.org

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

Expect mad features in release 0.14 (Jan 2018)!!!

On behalf of the DIPY developers,
Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro
http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 0.13.0

[Eleftherios Garyfallidis]

Hello all,

We are happy to announce a new public release of DIPY. This is mostly a
maintenance release with extra fixes, speedups and minor changes of
dependencies.

*DIPY 0.13 (Tuesday, 24 October 2017)*

This release received contributions from 13 developers (the full release
notes are at: http://nipy.org/dipy/release0.13.html)

*Highlights of this release include:*

- Faster Local PCA implementation.
- Fixed different issues with OpenMP and Windows / OSX.
- Replacement of cvxopt module by cvxpy.
- Replacement of Pytables module by h5py.
- Updated API to support latest numpy version (1.14).
- New user interfaces for visualization.
- Large documentation update.

To upgrade, run the following command in your terminal:

*pip install --upgrade dipy*

or

*conda install -c conda-forge dipy*


For any questions go to http://dipy.org, or send an e-mail to
neuroimag...@python.org

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

Expect mad features in release 0.14 (Jan 2018)!!!

On behalf of the DIPY developers,
Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro
http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 1.6.0

[Eleftherios Garyfallidis]

Hello all,


We are excited to announce a new release of DIPY: DIPY 1.6.0 is out from
the oven!


In addition, registration for the oceanic DIPY workshop 2023 (April 24-28)
is now open! Our comprehensive program is designed to equip you with the
skills and knowledge needed to master the latest techniques and tools in
structural and diffusion imaging.  An intense hands-on experience in Santa
Monica, Los Angeles! See the exquisite program here
<https://dipy.org/workshops/dipy-workshop-2023#Schedule> for this highly
anticipated event <https://dipy.org/workshops/dipy-workshop-2023>.



DIPY 1.6.0 (Monday, 16 January 2023)

The release 1.6.0 received contributions from 22 developers (the full
release notes are at:
https://dipy.org/documentation/1.6.0./release_notes/release1.6/).


Thank you all for your contributions and feedback!


Please click here
<https://dipy.org/documentation/1.6.0./api_changes/#dipy-1-6-0-changes> to
check 1.6.0 API changes.


Highlights of 1.6.0 release include:

   -

   NF: Unbiased groupwise linear bundle registration added.
   -

   NF: MAP+ constraints added.
   -

   Generalized PCA to less than 3 spatial dims.
   -

   Added positivity constraints to QTI.
   -

   New functionality to apply Symmetric Diffeomorphic Registration to
   points/streamlines.
   -

   New Human Connectome Project (HCP) data fetcher added.
   -

   New Healthy Brain Network (HBN) data fetcher added.
   -

   Multiple Workflows updated (DTIFlow, LPCAFlow, MPPCA) and added
   (RUMBAFlow).
   -

   Ability to handle VTP files.
   -

   Large codebase cleaning.
   -

   Large documentation update.
   -

   Closed 75 issues and merged 41 pull requests.

To upgrade or install <http://dipy.org/release0.10.html> DIPY


Run the following command in your terminal:
<http://dipy.org/release0.10.html>


pip install --upgrade dipy


or


conda install -c conda-forge dipy


This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.8.0+).


Please support us by citing DIPY in your papers using the following
DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>


Questions or suggestions?



For any questions go to https://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy

Finally, a new forum is available at
https://github.com/dipy/dipy/discussions


Have a wonderful time using the new version.


On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

Hurry up! Book your spot for the DIPY Workshop in LA! April 24-28 2023!!

[Eleftherios Garyfallidis]

Dear all,

Only a few spots are left. Register now: https://dipy.org/workshops/latest
 !!!

The complete program for the highly anticipated workshop is updated and
available in the link above.


DIPY is a powerful software library for analyzing and processing diffusion
MRI data. It is an open-source project with a large and active
community of contributors who are dedicated to advancing the field of
medical imaging. The DIPY workshop provides an excellent opportunity
for individuals to learn how to use this software effectively. The workshop
covers a broad range of topics, from basic concepts to advanced
techniques, and provides hands-on experience with the software. By
attending the DIPY workshop, you will not only learn how to use this
powerful tool, but also gain a deeper understanding of diffusion imaging
and machine learning for imaging in general. The workshop is led by
expert instructors who have extensive experience in both diffusion imaging
and DIPY, so attendees can be confident that they are receiving
accurate and up-to-date information.



[image: image.png]



In summary, the workshop offers:


   -

   Hands-on tutorials - Every single day of the 5 days !!!
   -

   Guided practice sessions (bring your data - optional)
   -

   Personalized certificates of attendance
   -

   Effective networking opportunities with one-to-one follow ups
   -

   Comprehensive explanation of theoretical foundations with practical
   examples
   -

   Access to latest and established methods with code and interfaces
   -

   Pointers to move beyond the current challenges and navigate hard to do
   analyses
   -

   Multiple clinical use cases (AZ, Parkinson’s etc.)





See above one of the many highlights of the workshop. Building synthetic
b0s (with Synb0) in DIPY 1.7.0!  More highlights here
<https://dipy.org/workshops/dipy-workshop-2023#Highlight>.

Please allow us to finish this email with a testimonial from one of our
last in person workshops:

This one is from an expert neuropsychologist:

“In recent years, I've found that many scientific conferences have become
plagued with pitfalls such as repetitive content, superficial networking,
and a focus

on self-promotion rather than genuine knowledge exchange. Attendees often
leave these events with a sense of disillusionment, feeling that their time
could

have been better spent elsewhere. The DIPY workshop, however, was a breath
of fresh air in this sea of mediocrity. It was highly interactive,
engaging, and

hands-on, with a genuine emphasis on learning and collaboration. The
organizers went above and beyond to create a welcoming and supportive
environment,

encouraging researchers of all backgrounds and expertise levels to
contribute their ideas and gain valuable insights. By addressing the
shortcomings of

traditional conferences, the DIPY workshop has rekindled my enthusiasm for
scientific events and has set a new standard for what a truly productive
and

inspiring gathering should be.”

We kept our promise! Get your tickets!

See you in the workshop!

Eleftherios Garyfallidis, PhD

Associate Professor

Intelligent Systems Engineering

Indiana University

Luddy Hall 700 N Woodlawn

Bloomington, IN 47408

DIPY <http://dipy.org/> | FURY <https://fury.gl/>
-- 
https://mail.python.org/mailman/listinfo/python-list

DIPY Workshop 2023 now to be held online! April 24-28.

[Eleftherios Garyfallidis]

Dear all,

Due to unexpected events we have had to make the decision to
transition our workshop
to a virtual format.
While this change was unexpected, we are well-prepared due to our previous
experience with our own online platform. Rest assured, we are fully
equipped to ensure that the virtual workshop will run smoothly.

It's worth noting that all talks this year will be conducted live, as
opposed to pre-recorded. So now we are offering the following updated and
flexible registration
options:

Silver : Starts from $200

   1.

   Listen to the talks live. Learn from the experts.
   2.

   3 days workshop, get the basic kit to strive in the diffusion imaging
   world.
   3.

   Ability to upgrade during the workshop.


Gold :  Starts from $500

Everything in Silver plus:

   1.

   Ability to attend study groups and to present your work.
   2.

   Full 5 days workshop.
   3.

   Certificate of attendance (Linkedin verifiable).


Platinum : Starts from $995

Everything in Gold plus:

   1.

   Provides additional preset hourly meetings with the DIPY developers
   beyond the workshop's duration. These will be 1 to 1 meetings to set up or
   improve your pipeline for your needs. Maximum 6 meetings. Each meeting will
   be 1 hour long.
   2.

   Provides access to the talks and all materials after the workshop.
   3.

   Ability to move to yearly long support.


Register now !

In summary, the workshop offers:


   -

   Hands-on tutorials - Every single day !!!
   -

   Guided practice sessions (bring your data)
   -

   Personalized certificates of attendance
   -

   Effective networking opportunities with one-to-one follow ups
   -

   Comprehensive explanation of theoretical foundations with practical
   examples
   -

   Access to latest and established methods with code and interfaces
   -

   Pointers to move beyond the current challenges and navigate hard to do
   analyses
   -

   Multiple clinical use cases (AZ, Parkinson’s, Stroke, etc.)


This year there is a higher level of focus in AI and ML. These technologies
have been transforming various industries, and now they are revolutionizing
medical imaging. By harnessing the power of advanced algorithms and vast
data sets, we have successfully integrated machine learning into our
imaging solutions, providing unparalleled accuracy and efficiency.


For those of you who are new to this. DIPY is an open source
software project
used for processing structural and diffusion imaging data. Join us for an
exciting in person workshop hosted online April 24-28.
https://dipy.org/workshops/latest

Our team of expert instructors will guide you through the fundamentals of
diffusion theory, data pre-processing, fiber tracking, and much more.
You'll have the opportunity to learn from industry-leading professionals,
ask questions, and network with like-minded peers.

Register today to secure your spot in this highly anticipated event. Now
online!!

https://dipy.org/workshops/dipy-workshop-2023#Registration


Happy to answer any questions you may have.

Thank you!,

DIPY team
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 1.4.1 Released!

[Eleftherios Garyfallidis]

Hello all,

We are happy to announce two new releases of DIPY: DIPY 1.4.0 and 1.4.1 are
out!

Please support us by citing DIPY in your papers using the following DOI:
10.3389/fninf.2014.8  <https://www.ncbi.nlm.nih.gov/pubmed/24600385>

DIPY 1.4.1 (Thursday, 6 May 2021) & 1.4.0 (Saturday, 13 March, 2021)


   -

   Release 1.4.1 received contributions from 11 developers (the full
   release notes are at:
   https://dipy.org/documentation/1.4.1./release_notes/release1.4.1/).
   -

   Release 1.4.0 received contributions from 8 developers (the full release
   notes are at:
   https://dipy.org/documentation/1.4.0./release_notes/release1.4/).


Thank you all for your contributions and feedback!

Please click here <https://dipy.org/documentation/1.4.1./api_changes/> to
check 1.4.1 API changes.

Please click here <https://dipy.org/documentation/1.4.0./api_changes/> to
check 1.4.0 API changes.

Highlights of 1.4.1 release include:

   -

   New surface seeding module for tractography named mesh.
   -

   Patch2Self and its documentation updated.
   -

   BUAN and RecoBundles documentation updated.
   -

   Standardization and improvement of the multiprocessing / multithreading
   rules.
   -

   Community and governance information added.
   -

   Large update of Cython code in compliance with the last standard.
   -

   Large documentation update.
   -

   Closed 61 issues and merged 28 pull requests.

Highlights of 1.4.0 release include:


   -

   New self-supervised denoising algorithm Patch2Self added.
   -

   Response function refactored and clarified.
   -

   B-tensor allowed with response functions.
   -

   Large Command Line Interface (CLI) documentation updated.
   -

   Public API for Registration added.
   -

   Large documentation update.
   -

   Closed 47 issues and merged 19 pull requests.


To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.7.0+).

Questions or suggestions?



For any questions go to https://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy

Finally, a new forum is available at
https://github.com/dipy/dipy/discussions

Have a wonderful time using the latest release.


On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 0.14.0

[Eleftherios Garyfallidis]

Hello all!

We are excited to announce a new *major release* of Diffusion Imaging in
Python (DIPY).

*DIPY 0.14 (Tuesday, 1rst May 2018)*

This release received contributions from *24 developers*. A warm thank you
to each one of you for your contribution.

The complete release notes are available at:
http://nipy.org/dipy/release0.14.html

*Highlights *of this release include:


   - *RecoBundles*: anatomically relevant segmentation of bundles
   - New super fast clustering algorithm: *QuickBundlesX*
   - New tracking algorithm:* Particle Filtering Tracking*.
   - New tracking algorithm: *Probabilistic Residual Bootstrap Tracking*.
   - New API for reading, saving and processing tractograms.
   - Fiber ORientation Estimated using Continuous Axially Symmetric Tensors
   (*FORECAST*).
   - New command line interfaces.
   - Deprecated fvtk (old visualization framework).
   - A range of new visualization improvements.
   - *Large documentation update*.

To upgrade, run the following command in your terminal:

*pip install --upgrade dipy*

or

*conda install -c conda-forge dipy*

This version of DIPY depends on recent versions of nibabel (2.1.0+).

For any questions go to http://dipy.org, or send an e-mail to
neuroimag...@python.org  or ask a question to our interactive chat room
available at https://gitter.im/nipy/dipy

On behalf of the DIPY developers,
Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro
http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 0.15.0 release

[Eleftherios Garyfallidis]

We are excited to announce a new release of Diffusion Imaging in Python
(DIPY).

DIPY 0.15 (Wednesday, 12 December 2018)

This release received contributions from 30 developers (the full release
notes are at: http://dipy.org/release0.15.html
<http://nipy.org/dipy/release0.12.html>)

Highlights of this release include:


   -

   Updated RecoBundles for automatic anatomical bundle segmentation.
   -

   New Reconstruction Model: qtau-dMRI signal representation.
   -

   New command line interfaces (e.g., dipy_slr).
   -

   New continuous integration with AppVeyor CI.
   -

   Nibabel Streamlines API now used almost everywhere for better memory
   management.
   -

   Compatibility with Python 3.7.
   -

   Many tutorials added or updated (5 New).
   -

   Large overall documentation update.
   -

   Moved visualization module to a new library: FURY.
   -

   Closed 287 issues and merged 93 pull requests.


Want to learn more?

The DIPY project is hosting an educational workshop March 11-15 at Indiana
University, USA. The event is sponsored by the National Institute of Health
(NIH). See topics and detailed information here:

https://workshop.dipy.org

The workshop will include tutorials on tracking, microstructure, and
statistical analysis. The workshop will also include a data accelerator
where you will be able to analyze your own data together with the DIPY
<http://dipy.org/> developers. More than 15 DIPY developers will be
available this year on site to help. All tutorials will run on 3 levels:
novice, intermediate and advanced. Register here <https://workshop.dipy.org>
.


To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (2.3.0+).

Questions or suggestions?

For any questions go to http://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 0.16.0 release

[Eleftherios Garyfallidis]

Hello all!,


We are excited to announce a new release of Diffusion Imaging in Python
(DIPY).

If you use DIPY in your research, please cite us using the following
DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>

DIPY 0.16 (Monday, 10 March 2019)

This release received contributions from 14 developers (the full release
notes are at: http://dipy.org/release0.16.html
<http://nipy.org/dipy/release0.16.html>). Thank you for your contributions
and feedback!

Highlights of this release include:

   -

   Horizon, medical visualization interface powered by QuickBundlesX.
   -

   New Tractometry tools: Bundle Analysis / Bundle Profiles.
   -

   New reconstruction model: IVIM MIX (Variable Projection).
   -

   New command line interface: Affine and Diffeomorphic Registration.
   -

   New command line interface: Probabilistic, Deterministic and PFT
   Tracking.
   -

   Integration of Cython Guidelines for developers.
   -

   Replacement of Nose by Pytest.
   -

   Documentation update.
   -

   Closed 103 issues and merged 41 pull requests.

Note:

   -

   DIPY 0.16.0 will be the last version to support Python 2. The next
   release, DIPY 1.0.0,  will support Python 3 only.



To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (2.3.0+).

Questions or suggestions?

For any questions go to http://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 1.0.0 - a historic release

[Eleftherios Garyfallidis]

We are excited to announce a new major and historic release of Diffusion
Imaging in Python (DIPY). DIPY 1.0.0 is out!

Please cite using the following DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>

DIPY 1.0.0 (Monday, 5 August 2019)

This release received contributions from 17 developers (the full release
notes are at:
https://dipy.org/documentation/1.0.0./release_notes/release1.0/). Thank you
all for your contributions and feedback!

A new DIPY era is starting: this release is compatible with python 3.5+ and
breaks backward compatibility with 0.x.x. Please click here
<https://dipy.org/documentation/1.0.0./api_changes/> to check API changes
or look at the end of this email. The 0.16.x series will have extended
bug-fix-only support for Python 2.7 until June 2020.

Highlights of this release include:

   -

   Critical API changes <https://dipy.org/documentation/1.0.0./api_changes/>
   -

   New awesome website <http://dipy.org>
   -

   Large refactoring of tracking API
   -

   New denoising algorithm: MP-PCA
   -

   New Gibbs ringing removal
   -

   New interpolation module: dipy.core.interpolation
   -

   New reconstruction models: Mean Signal DKI, MTMS-CSD
   -

   Increased coordinate systems consistency
   -

   New object to manage safely tractography data: StatefulTractogram
   -

   New command line interface for downloading datasets: FetchFlow
   -

   Horizon updated, medical visualization interface powered by QuickBundlesX
   -

   Removed all deprecated functions and parameters
   -

   Removed compatibility with Python 2.7
   -

   Updated minimum dependencies version (Numpy, Scipy)
   -

   All tutorials updated to API changes and 3 new added
   -

   Large documentation update
   -

   Closed 289 issues and merged 98 pull requests

Note:

   -

   DIPY 0.16.x will be the last series to support python 2. The next
   release, DIPY 1.0,  will support python 3 only.



To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (2.4.0+).

For visualization you need FURY (0.3.0+).

Questions or suggestions?



For any questions go to http://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors

API Changes

Some of the changes introduced in the 1.0 release will break backwards
compatibility with previous versions. This release is compatible with
Python 3.5+

Reconstruction

The spherical harmonics bases mrtrix and fibernav have been renamed to
tournier07 and descoteaux07 after the deprecation cycle started in the 0.15
release.

We changed dipy.data.default_sphere from symmetric724 to repulsion724 which
is more evenly distributed.

Segmentation

The API of dipy.segment.mask.median_otsu has changed in the following ways:
if you are providing a 4D volume, vol_idx is now a required argument. The
order of parameters has also changed.

Tractogram loading and saving

The API of dipy.io.streamlines.load_tractogram and
dipy.io.streamlines.save_tractogram has changed in the following ways: When
loading trk, tck, vtk, fib, or dpy) a reference nifti file is needed to
guarantee proper spatial transformation handling.

Spatial transformation handling

Functions from dipy.tracking.streamlines were modified to enforce the
affine parameter and uniform docstrings. deform_streamlines select_by_rois,
orient_by_rois, _extract_vals and values_from_volume.

Functions from dipy.tracking.utils were modified to enforce the affine
parameter and uniform docstring. density_map connectivity_matrix,
seeds_from_mask, random_seeds_from_mask, target, target_line_based, near_roi,
length and path_length were all modified.

The function affine_for_trackvis, move_streamlines, flexi_tvis_affine and
get_flexi_tvis_affine were deleted.

Functions from dipy.tracking.life were modified to enforce the affine
parameter and uniform docstring. voxel2streamline, setup and fit from class
FiberModel were all modified.

afq_profile from dipy.stats.analysis was modified in a similar way.

Simulations

   -

   dipy.sims.voxel.SingleTensor has been replaced by
   dipy.sims.voxel.single_tensor
   -

   dipy.sims.voxel.MultiTensor has been replaced by
   dipy.sims.voxel.multi_tensor
   -

   dipy.sims.voxel.SticksAndBall has been replaced by
   dipy.sims.voxel.sticks_and_ball

Interpolation

All interpolation functions have been moved to a new module name
dipy.core.interpolation

Tracking

The voxel_size parameter has been removed from the following function:

   -

   dipy.tracking.utils.connectivity_matrix
   -

   dipy.tracking.utils.density_map
   -

   dipy.tracking.utils.stre

ANN: DIPY 1.1.1 - a powerful release

[Eleftherios Garyfallidis]

We are excited to announce a new release of DIPY:


DIPY 1.1.1 is out! In addition:


a) A new 5 day workshop available during March 16-20 to learn the theory
and applications of the hundreds of methods available in DIPY 1.1.1
Intense!

See the exquisite program here <https://workshop.dipy.org>.

*b) Given the need for a myriad of new DIPY derivative projects, DIPY moved
to its own organization in GitHub. **Long live DIPY! *
*And therefore, *https://github.com/dipy/dipy* supersedes
https://github.com/nipy/dipy
<https://github.com/nipy/dipy> The old link will be available as a redirect
link for the next 6 months.*

c) Please support us by *citing** DIPY* in your papers using the following
DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>otherwise
the DIPY citation police will find you. ;)

DIPY 1.1.1 (Friday, 10 January 2020)

This release received contributions from 11 developers (the full release
notes are at:
https://dipy.org/documentation/1.1.1./release_notes/release1.1/). Thank you
all for your contributions and feedback!

Please click here <https://dipy.org/documentation/1.1.1./api_changes/> to
check API changes.

Highlights of this release include:

   -

   New module for deep learning DIPY.NN (uses TensorFlow 2.0).
   -

   Improved DKI performance and increased utilities.
   -

   Non-linear and RESTORE fits from DTI compatible now with DKI.
   -

   Numerical solutions for estimating axial, radial and mean kurtosis.
   -

   Added Kurtosis Fractional Anisotropy by Glenn et al. 2015.
   -

   Added Mean Kurtosis Tensor by Hansen et al. 2013.
   -

   Nibabel minimum version is 3.0.0.
   -

   Azure CI added and Appveyor CI removed.
   -

   New command line interfaces for LPCA, MPPCA and Gibbs Unringing.
   -

   New MTMS CSD tutorial added.
   -

   Horizon refactored and updated to support StatefulTractograms.
   -

   Speeded up all cython modules by using a smarter configuration setting.
   -

   All tutorials updated to API changes and 2 new tutorials added.
   -

   Large documentation update.
   -

   Closed 126 issues and merged 50 pull requests.

Note:

   -

   Have in mind that DIPY stopped supporting Python 2 after version 0.16.0.
   All major Python projects have switched to Python 3. It is time that you
   switch too.



To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.4.0+).

Questions or suggestions?



For any questions go to http://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 1.2.0

[Eleftherios Garyfallidis]

Hello all,


We are excited to announce a new release of DIPY: DIPY 1.2 is out!

Please support us by citing DIPY in your papers using the following DOI:
10.3389/fninf.2014.8  <https://www.ncbi.nlm.nih.gov/pubmed/24600385>

DIPY 1.2.0 (Wednesday, 9 September 2020)

This release received contributions from 27 developers (the full release
notes are at:
https://dipy.org/documentation/1.2.0./release_notes/release1.2/). Thank you
all for your contributions and feedback!

Please click here <https://dipy.org/documentation/1.2.0./api_changes/> to
check API changes.

Highlights of this release include:

- New command line interfaces for group analysis: BUAN.
- Added b-tensor encoding for gradient table.
- Better support for single shell or multi-shell response functions.
- Stats module refactored.
- Numpy's minimum version is 1.2.0.
- Fixed compatibilities with FURY 0.6+, VTK9+, CVXPY 1.1+.
- Added multiple tutorials for DIPY command line interfaces.
- Updated SH basis convention.
- Improved performance of tissue classification.
- Fixed a memory overlap bug (multi_median).
- Large documentation update (typography / references).
- Closed 256 issues and merged 94 pull requests.

Note:

   -

   Have in mind that DIPY does not support Python 2 after version 0.16.0.
   All major Python projects have switched to Python 3. It is time that you
   switch too.



To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.6.1+).

Questions or suggestions?



For any questions go to http://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy <https://gitter.im/nipy/dipy>

On behalf of the 110 DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
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ANN: DIPY 1.3.0

[Eleftherios Garyfallidis]

Hello all,

We are excited to announce a new release of DIPY: DIPY 1.3 is out!

Please support us by citing DIPY in your papers using the following DOI:
10.3389/fninf.2014.8  <https://www.ncbi.nlm.nih.gov/pubmed/24600385>

DIPY 1.3.0 (Wednesday, 3 November 2020)

This release received contributions from 27 developers (the full release
notes are at:
https://dipy.org/documentation/1.3.0./release_notes/release1.3/). Thank you
all for your contributions and feedback!

Please click here <https://dipy.org/documentation/1.3.0./api_changes/> to
check API changes.

Highlights of this release include:

- Gibbs ringing correction 10X faster.

- Spherical harmonics basis definitions updated.

- Added SMT2 metrics from mean signal diffusion kurtosis.

- New interface functions added to the registration module.

- New linear transform added to the registration module.

- New tutorials for DIPY command line interfaces.

- Fixed compatibility issues with different dependencies.

- Tqdm (multiplatform progress bar) dependency added.

- Large documentation update.

- Bundle section highlight from BUAN added in Horizon.

- Closed 134 issues and merged 49 pull requests.

Note:

Have in mind that DIPY does not support Python 2 after version 0.16.0. All
major Python projects have switched to Python 3. It is time that you switch
too.


To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.6.1+).

Questions or suggestions?



For any questions go to https://dipy.org, or send an e-mail to
d...@python.org 

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

Dipy 0.7.1 is now available for download!

[Eleftherios Garyfallidis]

Dear all,

We are very happy to announce another major release of Diffusion Imaging in
Python (Dipy).

http://dipy.org

Here we list some of the major new features:

*0.7.1 *(Thursday, 16 Jan 2014)

*Reconstruction*

* Constrained Spherical Deconvolution (CSD).
* Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE).
* Sharpening Deconvolution Transform (SDT).
* Signal-to-noise ratio estimation.
* RESTORE fitting for DTI.
* Westin's Tensor maps.

*Tracking*

* Enabled automated seeding in masks.
* Streamline filtering through specific ROIs using `target`.

*Segmentation*

* Brain and foreground extraction using median_otsu.

*Visualization*

* Streamtube visualization.
* Simultaneous peaks and ODF visualization.

*Connectivity *

* Connectivity matrices and density maps.

*Parallel processing*

* Parallel processing is possible for all reconstruction models using
`peaks_from_model`.

*Data access*

* Access to more publicly available datasets directly through Dipy
 functions.

*Installation*

* Installing Dipy is now easier and more universal.
* Available with pip, easy_install, neurodebian and other methods.
  http://dipy.org/installation.html

*Overall*

* 3x more tutorials than previous release.
  http://dipy.org/examples_index.html
* 2x more contributors from the previous release.
  http://dipy.org/developers.html


Yours sincerely,

On behalf of all Dipy developers
Eleftherios Garyfallidis
-- 
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DIPY 0.11.0 is now available for download

[Eleftherios Garyfallidis]

Dear all,


We are excited to announce a new public release of Diffusion Imaging in
Python (DIPY).

The 0.11 release follows closely on the heels of the 0.10 release,
resolving issues that existed in that release on the Windows 64 bit
platform. New features of the 0.11 and 0.10 release cycles include many
additional fixes and new frameworks. Here are some of the highlights:

DIPY 0.11.0 (Monday, 21 February 2016):

- New framework for contextual enhancement of ODFs.

- Compatibility with new version of numpy (1.11).

- Compatibility with VTK 7.0 which supports Python 3.x.

- Faster PIESNO for noise estimation.

- Reorient gradient directions according to motion correction parameters.

- Supporting Python 3.3+ but not 3.2.

- Reduced memory usage in DTI prediction.

- DSI now can use datasets with multiple b0s.

- Fixed different issues with Windows 64bit and Python 3.5.

DIPY 0.10.1 (Friday, 4 December 2015):

- Compatibility with new versions of scipy (0.16) and numpy (1.10).

- New cleaner visualization API, including compatibility with VTK 6, and
functions to create your own interactive visualizations.

- Diffusion Kurtosis Imaging (DKI): Google Summer of Code work by Rafael
Henriques.

- Mean Apparent Propagator (MAP) MRI for tissue microstructure estimation.

- Anisotropic Power Maps from spherical harmonic coefficients.

- A new framework for affine registration of images.

Detailed release notes can be found here:

http://dipy.org/release0.11.html

http://dipy.org/release0.10.html

To upgrade, run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

For the complete installation guide look here:

http://dipy.org/installation.html

For any questions go to http://dipy.org, or https://neurostars.org or send
an e-mail to neuroimag...@python.org

We also have a new instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis & Ariel Rokem

http://dipy.org/developers.html
-- 
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Happy new year with Dipy 0.8!

[Eleftherios Garyfallidis]

Dear all,


We are very happy to announce a new release of Diffusion Imaging in Python
(Dipy).


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.


Yours sincerely,


On behalf of the Dipy developers,

Eleftherios Garyfallidis

http://dipy.org
-- 
https://mail.python.org/mailman/listinfo/python-list

DIPY 0.9.2 is ready for download!

[Eleftherios Garyfallidis]

Dear all,

We are very happy to announce a new release of Diffusion Imaging in Python
(DIPY)

Here is a quick summary of our new features.

DIPY 0.9.2 (Wednesday, 18 March 2015)

* Anatomically Constrained Tissue Classifiers for Tracking
* Massive speedup of Constrained Spherical Deconvolution (CSD)
* Recursive calibration of response function for CSD
* New experimental framework for clustering
* Improvements and 10X speedup for Quickbundles
* Improvements in Linear Fascicle Evaluation (LiFE)
* New implementation of Geodesic Anisotropy
* New efficient transformation functions for registration
* Sparse Fascicle Model supports acquisitions with multiple b-values

Detailed release notes can be found here:
http://dipy.org/release0.9.html

Enjoy the upgrade. If you are using Pypi you just need to do:

*pip install --upgrade dipy*

For any questions go to http://dipy.org, or https://neurostars.org or send
an e-mail to nipy-de...@neuroimaging.scipy.org

DIPY will be an official exhibitor at HBM 2015 in Honolulu. Come and meet
us!

On behalf of the DIPY developers,
Eleftherios Garyfallidis
http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ctypes accessing functions with double pointers

[Eleftherios Garyfallidis]

Hello,

Is it possible using ctypes to call C functions from a shared object
containing double pointers e.g. int foo(float **i) and if yes how?

Best wishes,
Eleftherios
-- 
http://mail.python.org/mailman/listinfo/python-list

Re: ctypes accessing functions with double pointers

[Eleftherios Garyfallidis]

Thank you Chris :-)

On Mon, Nov 7, 2011 at 11:29 PM, Chris Rebert  wrote:

> On Mon, Nov 7, 2011 at 2:06 PM, Eleftherios Garyfallidis
>  wrote:
> > Hello,
> >
> > Is it possible using ctypes to call C functions from a shared object
> > containing double pointers e.g. int foo(float **i) and if yes how?
>
> (Untested conjecture:)
>
> import ctypes
> # ...create ctypes_wrapped_foo...
> the_float = ctypes.c_float(42.1)
> float_ptr = ctypes.byref(the_float)
> i = ctypes.byref(float_ptr)
> result_integer = ctypes_wrapped_foo(i)
>
> Cheers,
> Chris
>
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ANN: DIPY 0.12.0 release

[Eleftherios Garyfallidis]

We are excited to announce a new public release of Diffusion Imaging in
Python (DIPY).


DIPY 0.12 (Tuesday, 26 June 2017)

This release received contributions from 48 developers (the full release
notes are at: http://nipy.org/dipy/release0.12.html)

Highlights of this release include:


- IVIM Simultaneous modeling of perfusion and diffusion.
- MAPL, tissue microstructure estimation using Laplacian-regularized
MAP-MRI.
- DKI-based microstructural modelling.
- Free water diffusion tensor imaging.
- Denoising using Local PCA.
- Streamline-based registration (SLR).
- Fiber to bundle coherence (FBC) measures.
- Bayesian MRF-based tissue classification.
- New API for integrated user interfaces.
- New hdf5 file (.pam5) for saving reconstruction results.
- Interactive slicing of images, ODFs and peaks.
- Updated API to support latest numpy versions.
- New system for automatically generating command line interfaces.
- Faster computation of cross correlation for image registration.

To upgrade, run the following command in your terminal:
<http://dipy.org/release0.10.html>


pip install --upgrade dipy

or

conda install -c conda-forge dipy

This version of DIPY depends on the latest version of nibabel (2.1.0).

For any questions go to http://dipy.org, or send an e-mail to
neuroimag...@python.org

We also have an instant messaging service and chat room available at
https://gitter.im/nipy/dipy

On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

http://dipy.org/developers.html
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: DIPY 1.8.0

[Eleftherios Garyfallidis via Python-list]

Hello all,

We are excited to announce a new release of DIPY: DIPY 1.8.0 ! This release
includes many new features and updates to support the latest Python, Numpy,
Scipy and Cython versions. The Pythonic ecosystem is growing fast. Which is
great. But please report any issues you may find.

DIPY 1.8.0 (Friday, 13 December 2023)

The release 1.8.0 received contributions from 28 developers (the full
release notes are at:
https://docs.dipy.org/stable/release_notes/release1.8.html).

Thank you all for your contributions and feedback!

Please click here
<https://docs.dipy.org/stable/api_changes.html#dipy-1-8-0-changes> to check
1.8.0 API changes.

Highlights of 1.8.0 release include:


   -

   Python 3.12.0 support.
   -

   Cython 3.0.0 compatibility.
   -

   Migrated to Meson build system. Setuptools is no more.
   -

   EVAC+ novel DL-based brain extraction method added.
   -

   Parallel Transport Tractography (PTT) 10X faster.
   -

   Many Horizon updates. Fast overlays of many images.
   -

   New Correlation Tensor Imaging (CTI) method added.
   -

   Improved warnings for optional dependencies.
   -

   Large documentation update. New theme/design integration.
   -

   Closed 197 issues and merged 130 pull requests.

Here is also a reminder of the previous highlights (which was not announced
- due to the large changes in the Pythonic ecosystem).

Highlights of 1.7.0 release include:


   -

   NF: BundleWarp - Streamline-based nonlinear registration method for
   bundles added.
   -

   NF: DKI+ - Diffusion Kurtosis modeling with advanced constraints added.
   -

   NF: Synb0 - Synthetic b0 creation added using deep learning added.
   -

   NF: New Parallel Transport Tractography (PTT) added.
   -

   NF: Fast Streamline Search algorithm added.
   -

   NF: New denoising methods based on 1D CNN added.
   -

   Handle Asymmetric Spherical Functions.
   -

   Large update of DIPY Horizon features.
   -

   Multiple Workflows updated
   -

   Large codebase cleaning.
   -

   Large documentation update. Integration of Sphinx-Gallery.
   -

   Closed 53 issues and merged 34 pull requests.

To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal (works across Mac, Linux, Win):
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.9.0+).

Questions or suggestions?



For any questions go to our new website at https://dipy.org, or send an
e-mail to d...@python.org

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy

Finally, a new discussion forum is available at
https://github.com/dipy/dipy/discussions

Have a wonderful time using this new version and please support us by citing
DIPY in your papers using the following DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>


In addition, registration for the online DIPY workshop 2024 (March 11-15)
is open! The workshop will continue equipping you with the skills and
knowledge needed to master the latest techniques and tools in structural
and diffusion imaging. See the exquisite program and keynote speakers here
<https://dipy.org/workshops/dipy-workshop-2024#Schedule>.

Register now <https://workshop.dipy.org/workshops/dipy-workshop-2024>!


On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

ANN: Happy 2025 with DIPY 1.10.0 💥

[Eleftherios Garyfallidis via Python-list]

Hello and Happy 2025 to all !,

We are excited to announce a new release of DIPY: DIPY 1.10.0 !

DIPY 1.10.0 (Friday, 12 December 2024)

The release 1.10.0 received contributions from 28 developers (the full
release notes are at:
https://docs.dipy.org/stable/release_notes/release1.10.html).

Thank you all for your contributions and feedback!

Please click here
<https://docs.dipy.org/stable/api_changes.html#dipy-1-10-0-changes> to
check 1.10.0 API changes.

Highlights of 1.10.0 release include:

- NF: Patch2Self3 - Memory less denoising for dMRI is now available.

- NF: Fiber density and spread from ODF using Bingham distributions method
added.

- NF: Iteratively reweighted least squares for robust fitting of diffusion
models added.

- NF: NDC - Neighboring DWI Correlation quality metric added.

- NF: DAM - DWI-based tissue classification method added.

- NF: New Parallel Backends (Ray, Joblib, Dask) for fitting reconstruction
methods added.

- RF: Deprecation of Tensorflow support. PyTorch support is now the default.

- Transition to Keyword-only arguments (PEP 3102).

- Zero-warnings policy (CIs, Compilation, doc generation) adopted.

- Adoption of ruff for automatic style enforcement.

- Transition to using f-strings.

- Citation system updated. It is more uniform and robust.

- Multiple Workflows updated.

- Multiple DIPY Horizon features updated.

- Large documentation update.

- Closed 258 issues and merged 187 pull requests.


To upgrade or install <http://dipy.org/release0.10.html> DIPY

Run the following command in your terminal:
<http://dipy.org/release0.10.html>

pip install --upgrade dipy

This version of DIPY depends on nibabel (3.0.0+).

For visualization you need FURY (0.12.0+).

Questions or suggestions?



For any questions go to https://dipy.org, or send an e-mail to
d...@python.org

We also have an instant messaging service and chat room available at
https://gitter.im/dipy/dipy

Finally, a new forum is available at
https://github.com/dipy/dipy/discussions

Have a wonderful time using the new version.

In addition, registration for the online DIPY workshop 2025 (March 17-21)
is open! The workshop will equip you with the skills and knowledge needed
to master the latest techniques and tools in structural and diffusion
imaging. See the exquisite program and keynote speakers here
<https://workshop.dipy.org>. Register today to save a spot!

Please support us by citing DIPY in your papers using the following
DOI: 10.3389/fninf.2014.8
<https://www.ncbi.nlm.nih.gov/pubmed/24600385>


On behalf of the DIPY developers,

Eleftherios Garyfallidis, Ariel Rokem, Serge Koudoro

https://dipy.org/contributors
-- 
https://mail.python.org/mailman/listinfo/python-list

Join us for the 2025 DIPY Workshop! - March 17-21 Online! - Early Bird Ends Jan 3rd!

[Eleftherios Garyfallidis via Python-list]

Dear All,

DIPY is a software that analyzes structural and diffusion MRI images using
Python. We are excited to invite you to our upcoming DIPY workshop, which
will take place from March 17 to March 21, 2025. This year, we promise an
enriching experience as we dive into the world of AI in advanced imaging
and data analytics.

Our distinguished keynote speakers include Prof. Simon Warfield (Harvard
Medical School), Prof. Alexandra Badea (Duke University), Prof. Franco
Pestilli (University of Texas at Austin), Prof. Marco Palombo (Cardiff
University), and Prof. Julien Cohen-Adad (Polytechnique Montreal).

Additionally, Koudoro, Descoteaux, Tang, Rokem, Chandio, Fadnavis,
Henriques, Legarreta, and others will present various techniques in medical
imaging, including (but not limited to) pre-processing, reconstruction,
denoising, microstructure modeling, tractography, and visualization.

This year’s highlights include the overview of our *new ultra-fast tracking*
API by Girard (CPU) and Kruper (GPU) and much more!

The DIPY workshop aims to train the next generation of scientists, doctors,
and engineers who will shape the future of medical imaging. Your
participation will contribute greatly to the success of this event.

As is customary for the DIPY workshop, the following will be available:

   -

   Daily hands-on sessions for guided practice
   -

   Opportunities for attendees to present their work or problems of interest
   -

   Certificates of Attendance

Please visit our website *here*
<https://workshop.dipy.org/workshops/dipy-workshop-2025> to register for
the workshop. We look forward to your participation and to exploring the
exciting work of imaging science together.

DIPY is also offering Early Bird discounts until January 3rd, 2025.
Register soon to take advantage of these offers!

For any concerns, please email *works...@dipy.org *.
On behalf of the DIPY team,
Eleftherios Garyfallidis, PhD
DIPY Founder & Lead
Associate Professor
Intelligent Systems Engineering
Indiana University
Luddy Hall 700 N Woodlawn
Bloomington, IN 47408
GRG <https://grg.luddy.indiana.edu/> | DIPY <http://dipy.org/> | FURY
<https://fury.gl/>
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