What is DIPY?

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

DIPY is easy to install:

Available on many operating systems

Pre-Processing

Denoising : NLmeans, Local PCA
Brain extraction

SNR estimation / Reslice Datasets

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Registration

Streamlines based Registration

Affine Registration

Diffeomorphic 2D/3D Registration

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Reconstruction

Single Shell: DTI, CSD, SDT, SFM, Q-Ball CSA...

Multi Shell: GQI, DTI, DKI, SHORE and MAPMRI...

More than 20 Models...

Tractography

Tissue Classification

Many tracking algorithms

Apply different operations on streamlines

Simplify large datasets via streamlines clustering.

Calculate distances/correspondences between streamlines.

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Visualization

Simple interactive visualization of ODFs

Streamlines interactive visualization

Advanced widget

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Command Line Interfaces

Many algorithms available via command line

Create your owns command line!

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Announcements


See some of our Past Announcements

Highlights


DIPY 1.2.0 is now available. New features 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 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.

See Older Highlights.

Tweets

Tue Oct 13

Bundle Analytics aka BUAN, is a computational framework for investigating the shapes and profiles of brain pathways… https://t.co/IkjSSNQ12s

Wed Oct 07

RT @johancarlin: 23-24 November we end the series with Rafel Neto Henriques' @RafaelNetoHenr1 workshop on diffusion MRI analysis with @dipy…

Fri Oct 02

RT @openneurosci: @dipymri offers methods for spatial normalization, sig. processing, ML, statistical analysis & visualization of medical…

Sat Sep 26

RT @dipymri: DIPY 1.2.0 is out! Thanks to all 110 contributors! New command-line interfaces for group analysis: BUAN. Added b-tensor encodi…

Thu Sep 24

DIPY 1.2.0 is out! Thanks to all 110 contributors! New command-line interfaces for group analysis: BUAN. Added b-te… https://t.co/7JZnyzofDz

Cite Us !


Garyfallidis E, Brett M, Amirbekian B, Rokem A, van der Walt S, Descoteaux M, Nimmo-Smith I and Dipy Contributors (2014). DIPY, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, vol.8, no.8.

Sponsors


DIPY - NIH / NIBIB
DIPY - Indiana university
DIPY - GSOC
IU
DIPY - EWU