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

Command-Line Interfaces

All Agorithms available via CLI

Create your Own

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Statistical Analysis

BUAN

AFQ

K-Fold cross validation

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Reconstruction

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

Multi-Shell: GQI, DTI, DKI, SHORE, MAPMRI, MSMT-CSD, ...

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Registration

Affine Registration

Diffeomorphic 2D/3D Registration

Streamlines based Registration

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Tractography

Probabilistic Tracking

Deterministic Tracking

PFT Tracking

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Datasets

HCP Tractogram

CFIN Datasets

High resolution DWI

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Denoising

Patch2self

Gibbs Unringing

LPCA - MPPCA

Non Local Means

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Visualization

ODFs visualization

interactive tractogram visualization

Advanced UI and Shaders

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Pre-Processing

Brain extraction

SNR estimation

Reslice Datasets

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Announcements


See some of our Past Announcements

Highlights


DIPY 1.3.0 is now available. New features 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 for data downloading) dependency added.

  • Large documentation update.

  • Bundle section highlight from BUAN added in Horizon.

  • Closed 134 issues and merged 49 pull requests.

See Older Highlights.

Tweets

Tue Mar 02

RT @ShreyasSF: 💥Patch2Self is now available for use in QSIPrep via @dipymri ! Huge shoutout to @CieslakMatt and @sattertt for building the…

Fri Feb 26

RT @ShreyasSF: Very excited to share that the work on🌟Denoising Diffusion MRI, Patch2Self🌟 with @thebasepoint and @garyfallidis has been ac…

Wed Feb 10

RT @BramshQ: @dipymri is participating in Google Summer of Code 2021 under the @INCForg umbrella. Check out these exciting projects and app…

Mon Jan 18

RT @msandstr: I just added another 10 projects to the @INCForg #GSoC Ideas list. Excited to have @dipymri, @hebbianloop, @R3RT0, @katjaQhe…

Mon Jan 04

RT @arokem: A milestone for @dipymri, as the paper describing the software reached 500 citations, according to Google Scholar https://t.co/…

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