Getting started with DIPY

Introduction to Basic Tracking

Introduction to Basic Tracking

Reslice diffusion datasets

Between-volumes Motion Correction on DWI datasets

Between-volumes Motion Correction on DWI datasets

Noise estimation using PIESNO

Denoise images using Non-Local Means (NLMEANS)

Denoise images using Non-Local Means (NLMEANS)

Brain segmentation with median_otsu

Brain segmentation with median_otsu

Patch2Self: Self-Supervised Denoising via Statistical Independence

Patch2Self: Self-Supervised Denoising via Statistical Independence

Denoise images using Local PCA via empirical thresholds

Denoise images using Local PCA via empirical thresholds

Gradients and Spheres

Denoise images using Adaptive Soft Coefficient Matching (ASCM)

Denoise images using Adaptive Soft Coefficient Matching (ASCM)

SNR estimation for Diffusion-Weighted Images

SNR estimation for Diffusion-Weighted Images

Denoise images using the Marcenko-Pastur PCA algorithm

Denoise images using the Marcenko-Pastur PCA algorithm

Suppress Gibbs oscillations

Below, an overview of all reconstruction models available on DIPY.

Note: Some reconstruction models do not have a tutorial yet

Applying positivity constraints to Q-space Trajectory Imaging (QTI+)

Applying positivity constraints to Q-space Trajectory Imaging (QTI+)

Continuous and analytical diffusion signal modelling with 3D-SHORE

Continuous and analytical diffusion signal modelling with 3D-SHORE

Reconstruct with Diffusion Spectrum Imaging

Reconstruct with Diffusion Spectrum Imaging

DSI Deconvolution vs DSI

Calculate SHORE scalar maps

Reconstruct with Generalized Q-Sampling Imaging

Reconstruct with Generalized Q-Sampling Imaging

Reconstruct with Constant Solid Angle (Q-Ball)

Reconstruct with Constant Solid Angle (Q-Ball)

Reconstruction with the Sparse Fascicle Model

Reconstruction with the Sparse Fascicle Model

Calculate DSI-based scalar maps

Calculate DSI-based scalar maps

Reconstruction of the diffusion signal with the kurtosis tensor model

Reconstruction of the diffusion signal with the kurtosis tensor model

K-fold cross-validation for model comparison

K-fold cross-validation for model comparison

Reconstruct with Q-space Trajectory Imaging (QTI)

Reconstruct with Q-space Trajectory Imaging (QTI)

Reconstruction of the diffusion signal with the Tensor model

Reconstruction of the diffusion signal with the Tensor model

Crossing invariant fiber response function with FORECAST model

Crossing invariant fiber response function with FORECAST model

Using the RESTORE algorithm for robust tensor fitting

Using the RESTORE algorithm for robust tensor fitting

Reconstruction of the diffusion signal with the WMTI model

Reconstruction of the diffusion signal with the WMTI model

Signal Reconstruction Using Spherical Harmonics

Signal Reconstruction Using Spherical Harmonics

Using the free water elimination model to remove DTI free water contamination

Using the free water elimination model to remove DTI free water contamination

Intravoxel incoherent motion

Reconstruction with Constrained Spherical Deconvolution

Reconstruction with Constrained Spherical Deconvolution

Reconstruction with Multi-Shell Multi-Tissue CSD

Reconstruction with Multi-Shell Multi-Tissue CSD

Continuous and analytical diffusion signal modelling with MAP-MRI

Continuous and analytical diffusion signal modelling with MAP-MRI

Mean signal diffusion kurtosis imaging (MSDKI)

Mean signal diffusion kurtosis imaging (MSDKI)

Reconstruction with Robust and Unbiased Model-BAsed Spherical Deconvolution

Reconstruction with Robust and Unbiased Model-BAsed Spherical Deconvolution

Estimating diffusion time dependent q-space indices using qt-dMRI

Estimating diffusion time dependent q-space indices using qt-dMRI

Crossing-preserving contextual enhancement

Crossing-preserving contextual enhancement

Fiber to bundle coherence measures

Fiber to bundle coherence measures

Surface seeding for tractography

Surface seeding for tractography

An introduction to the Deterministic Maximum Direction Getter

An introduction to the Deterministic Maximum Direction Getter

Parallel Transport Tractography

Parallel Transport Tractography

Tracking with Robust Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD)

Tracking with Robust Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD)

Tracking with the Sparse Fascicle Model

Tracking with the Sparse Fascicle Model

Bootstrap and Closest Peak Direction Getters Example

Bootstrap and Closest Peak Direction Getters Example

Introduction to Basic Tracking

Introduction to Basic Tracking

Introduction to Basic Tracking

Introduction to Basic Tracking

An introduction to the Probabilistic Direction Getter

An introduction to the Probabilistic Direction Getter

Particle Filtering Tractography

Particle Filtering Tractography

Linear fascicle evaluation (LiFE)

Linear fascicle evaluation (LiFE)

Using Various Stopping Criterion for Tractography

Using Various Stopping Criterion for Tractography

BUAN Bundle Shape Similarity Score

BUAN Bundle Shape Similarity Score

BUAN Bundle Assignment Maps Creation

BUAN Bundle Assignment Maps Creation

Extracting AFQ tract profiles from segmented bundles

Extracting AFQ tract profiles from segmented bundles

Streamline length and size reduction

Streamline length and size reduction

Calculation of Outliers with Cluster Confidence Index

Calculation of Outliers with Cluster Confidence Index

Calculate Path Length Map

Connectivity Matrices, ROI Intersections and Density Maps

Connectivity Matrices, ROI Intersections and Density Maps

Groupwise Bundle Registration

Direct Bundle Registration

Symmetric Diffeomorphic Registration in 3D

Symmetric Diffeomorphic Registration in 3D

Diffeomorphic Registration with binary and fuzzy images

Diffeomorphic Registration with binary and fuzzy images

Symmetric Diffeomorphic Registration in 2D

Symmetric Diffeomorphic Registration in 2D

Nonrigid Bundle Registration with BundleWarp

Nonrigid Bundle Registration with BundleWarp

Affine Registration with Masks

Affine Registration with Masks

Applying image-based deformations to streamlines

Applying image-based deformations to streamlines

Affine Registration in 3D

Brain segmentation with median_otsu

Brain segmentation with median_otsu

Brain segmentation with median_otsu

Brain segmentation with median_otsu

Tractography Clustering with QuickBundles

Tractography Clustering with QuickBundles

Tissue Classification of a T1-weighted Structural Image

Tissue Classification of a T1-weighted Structural Image

Tractography Clustering - Available Metrics

Tractography Clustering - Available Metrics

Fast Streamline Search

Enhancing QuickBundles with different metrics and features

Enhancing QuickBundles with different metrics and features

Tractography Clustering - Available Features

Tractography Clustering - Available Features

Automatic Fiber Bundle Extraction with RecoBundles

Automatic Fiber Bundle Extraction with RecoBundles

DSI Deconvolution vs DSI

DSI Deconvolution vs DSI

DKI MultiTensor Simulation

MultiTensor Simulation

Parallel reconstruction using Q-Ball

Parallel reconstruction using Q-Ball

Parallel reconstruction using CSD

Parallel reconstruction using CSD

Read/Write streamline files

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

Advanced interactive visualization

Advanced interactive visualization

Creating a new workflow.

Creating a new combined workflow

Creating a new combined workflow