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Site Navigation

    • Overview
    • Tutorials
    • Recipes
    • CLI / Workflows
    • API
    • CLI API

    • Upcoming

    • DIPY Workshop 2026

    • Past

    • DIPY Workshop 2025
    • DIPY Workshop 2024
    • DIPY Workshop 2023
    • DIPY Workshop 2022
    • DIPY Workshop 2021
    • DIPY Workshop 2020
    • DIPY Workshop 2019

    • News

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    • Help

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Section Navigation

  • Quick Start
    • Getting started with DIPY
    • Introduction to Basic Tracking
  • Preprocessing
    • Reslice diffusion datasets
    • Between-volumes Motion Correction on DWI datasets
    • Noise estimation using PIESNO
    • Denoise images using Non-Local Means (NLMEANS)
    • Patch2Self: Self-Supervised Denoising via Statistical Independence
    • Brain segmentation with median_otsu
    • Denoise images using Local PCA via empirical thresholds
    • Gradients and Spheres
    • Denoise images using Adaptive Soft Coefficient Matching (ASCM)
    • SNR estimation for Diffusion-Weighted Images
    • Denoise images using the Marcenko-Pastur PCA algorithm
    • Suppress Gibbs oscillations
    • Bias Field Correction for Diffusion MRI: a Practical Guide
  • Reconstruction
    • Applying positivity constraints to Q-space Trajectory Imaging (QTI+)
    • Reconstruct with Diffusion Spectrum Imaging (DSI)
    • Reconstruction of the diffusion signal with the correlation tensor model (CTI)
    • DSI Deconvolution (DSID) vs DSI
    • Calculate SHORE scalar maps
    • Reconstruct with Generalized Q-Sampling Imaging
    • Continuous and analytical diffusion signal modelling with 3D-SHORE
    • Reconstruct with Constant Solid Angle (Q-Ball)
    • Reconstruction with the Sparse Fascicle Model (SFM)
    • Calculate DSI-based scalar maps
    • Reconstruct with Q-space Trajectory Imaging (QTI)
    • Crossing invariant fiber response function with FORECAST model
    • K-fold cross-validation for model comparison
    • Reconstruction of the diffusion signal with DTI (single tensor) model
    • Local reconstruction using the Histological ResDNN
    • Reconstruction of the diffusion signal with the WMTI model (DKI-MICRO)
    • Using the RESTORE algorithm for robust tensor fitting
    • Using the free water elimination model to remove DTI free water contamination
    • Reconstruction of the diffusion signal with the kurtosis tensor model (DKI)
    • Reconstruction with FORCE (FORward modeling for Complex microstructure Estimation)
    • Signal Reconstruction Using Spherical Harmonics
    • Reconstruction with Multi-Shell Multi-Tissue CSD
    • Continuous and analytical diffusion signal modelling with MAP-MRI
    • Reconstruction with Constrained Spherical Deconvolution model (CSD)
    • Intravoxel incoherent motion (IVIM)
    • Reconstruction of Bingham Functions from ODFs
    • Robust fitting with iteratively reweighted least squares.
    • Mean signal diffusion kurtosis imaging (MSDKI)
    • Reconstruction with Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA)
    • Estimating diffusion time dependent q-space indices using qt-dMRI
  • Contextual Enhancement
    • Crossing-preserving contextual enhancement
    • Fiber to bundle coherence measures
  • Fiber Tracking
    • Surface seeding for tractography
    • Parallel Transport Tractography
    • An introduction to the Deterministic Tractography
    • Bootstrap and Closest Peak Tracker Example
    • Tracking with Robust Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD)
    • Tracking with the Sparse Fascicle Model
    • Introduction to Basic Tracking
    • Particle Filtering Tractography
    • An introduction to the Probabilistic Tractography
    • Linear fascicle evaluation (LiFE)
    • Using Various Stopping Criterion for Tractography
  • Streamlines Analysis and Connectivity
    • BUAN Bundle Shape Similarity Score
    • BUAN Bundle Assignment Maps Creation
    • BUAN bundle profiles
    • Extracting AFQ tract profiles from segmented bundles
    • Streamline length and size reduction
    • Calculation of Outliers with Cluster Confidence Index
    • Calculate Path Length Map
    • Connectivity Matrices, ROI Intersections and Density Maps
  • Registration
    • Groupwise Bundle Registration
    • Direct Bundle Registration
    • Diffeomorphic Registration with binary and fuzzy images
    • Symmetric Diffeomorphic Registration in 3D
    • Nonrigid Bundle Registration with BundleWarp
    • Symmetric Diffeomorphic Registration in 2D
    • Applying image-based deformations to streamlines
    • Affine Registration with Masks
    • Affine Registration in 3D
  • Segmentation
    • Tissue Classification using Diffusion MRI with DAM
    • Brain segmentation with median_otsu
    • Tractography Clustering with QuickBundles
    • Tissue Classification of a T1-weighted Structural Image
    • Tractography Clustering - Available Metrics
    • Saving and Loading QuickBundles Clustering Results
    • Fast Streamline Search
    • Enhancing QuickBundles with different metrics and features
    • Tractography Clustering - Available Features
    • Automatic Fiber Bundle Extraction with RecoBundles
  • Simulation
    • DSI Deconvolution (DSID) vs DSI
    • DKI MultiTensor Simulation
    • MultiTensor Simulation
  • Multiprocessing
    • Parallel reconstruction using CSD
    • Parallel reconstruction using Q-Ball
    • Tractography on the DiSCo Phantom
  • File Formats
    • Understanding the PAM5 File Format
    • Read/Write streamline files
  • Visualization
    • Visualization of ROI Surface Rendered with Streamlines
    • Visualize bundles and metrics on bundles
    • Simple volume slicing
    • Advanced interactive visualization
    • Interactive Visualization with DIPY Horizon (Python)
  • Workflows
    • Creating a new workflow.
    • Creating a new combined workflow
  • Examples
  • Visualization

Visualization#

Visualization of ROI Surface Rendered with Streamlines

Visualization of ROI Surface Rendered with Streamlines

Visualize bundles and metrics on bundles

Visualize bundles and metrics on bundles

Simple volume slicing

Simple volume slicing

Advanced interactive visualization

Advanced interactive visualization

Interactive Visualization with DIPY Horizon (Python)

Interactive Visualization with DIPY Horizon (Python)

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Read/Write streamline files

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Visualization of ROI Surface Rendered with Streamlines

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  • Google supported DIPY through the Google Summer of Code Program (2015-2024)
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