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
Reconstruction
Single Shell: DTI, CSA, SFM, SDT, Q-Ball, CSD, ...
Multi-Shell: GQI, DTI, DKI, SHORE, MAPMRI, MSMT-CSD, ...
Registration
Visualization
Announcements
DIPY 1.5.0 released March 11, 2022.
DIPY 1.4.1 released May 6, 2021.
DIPY 1.4.0 released March 13, 2021.
See some of our Past Announcements
Highlights
DIPY 1.5.0 is now available. New features include:
New reconstruction model added: Q-space Trajectory Imaging (QTI).
New reconstruction model added: Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD).
New reconstruction model added: Residual block Deep Neural Network (ResDNN).
Masking management in Affine Registration added.
Multiple Workflows updated (DTIFlow, DKIFlow, ImageRegistrationFlow) and added (MotionCorrectionFlow).
Compatibility with Python 3.10 added.
Migrations from Azure Pipeline to Github Actions.
Large codebase cleaning.
New parallelisation module added.
dipy.io.bvectxtmodule deprecated.New DIPY Horizon features (ROI Visualizer, random colors flag).
Large documentation update.
Closed 129 issues and merged 72 pull requests.
See Older Highlights.
Tweets
Tue Aug 02 |
RT @BramshQ: First in-person conference after God knows how long! #AAIC2022. Come by my poster (P3-220) if you are at #AAIC22 to chat about… |
Mon Aug 01 |
RT @krsitek: Loved flipping the page on my BRAIN Initiative calendar and seeing @BramshQ’s beautiful #sciart! Makes it a little less painfu… |
Fri Jul 15 |
@njahanshad Thank you for taking interest in the challenge! We'll soon send you an email about the details. |
Fri Jul 15 |
Great work 🤩 FiberNeat: Unsupervised White Matter Tract Filtering. No training or atlas required!! 🧠 https://t.co/xWsiooG0wh |
Fri Jul 15 |
RT @PTenigma: If you're at #EMBC22 come see us @ 10:45am in the Forth Room (SEC Armadillo) to talk about manifold embedding (t-SNE, UMAP) t… |
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
