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.
Available on many operating systems
Single Shell: DTI, CSA, SFM, SDT, Q-Ball, CSD, ...
Multi-Shell: GQI, DTI, DKI, SHORE, MAPMRI, MSMT-CSD, ...
DIPY 1.3.0 released November 3, 2020.
DIPY 1.2.0 released September 9, 2020.
DIPY 1.1.1 released January 10, 2020.
See some of our Past Announcements
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.
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/… |
Fri Dec 18 |
RT @arokem: New @dipymri with heavy lifting by our collaborators @nvidia: GPU-accelerated brain tractography, https://t.co/CqKJLgRpba. Trac… |
Wed Dec 09 |
RT @dipymri: 🚨Discussion: Patch2Self for #DiffusionMRI data, being presented @NeurIPS_Conf #NeurIPS2020 as a Spotlight Presentation (Thu 10… |
Wed Dec 09 |
Denoise your data in seconds using @dipymri implementation via CLI command: dipy_denoise_patch2self !! For #Python… https://t.co/98xtYkqtTj |
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.