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Dipy Development Changelog

Dipy is a diffusion MR imaging library written in Python

'Close gh-' statements refer to GitHub issues that are available at:

http://github.com/nipy/dipy/issues

The full VCS changelog is available here:

http://github.com/nipy/dipy/commits/master

Releases

Dipy

The code found in Dipy was created by the people found in the AUTHOR file.

  • 1.0.0 (Monday, 5 August 2019)
  • Critical :doc:`API changes <api_changes>`
  • Large refactoring of tracking API.
  • New denoising algorithm: MP-PCA.
  • New Gibbs ringing removal.
  • New interpolation module: dipy.core.interpolation.
  • New reconstruction models: MTMS-CSD, Mean Signal DKI.
  • Increased coordinate systems consistency.
  • New object to manage safely tractography data: StatefulTractogram
  • New command line interface for downloading datasets: FetchFlow
  • Horizon updated, medical visualization interface powered by QuickBundlesX.
  • Removed all deprecated functions and parameters.
  • Removed compatibility with Python 2.7.
  • Updated minimum dependencies version (Numpy, Scipy).
  • All tutorials updated to API changes and 3 new added.
  • Large documentation update.
  • Closed 289 issues and merged 98 pull requests.
  • 0.16.0 (Sunday, 10 March 2019)
  • Horizon, medical visualization interface powered by QuickBundlesX.
  • New Tractometry tools: Bundle Analysis / Bundle Profiles.
  • New reconstruction model: IVIM MIX (Variable Projection).
  • New command line interface: Affine and Diffeomorphic Registration.
  • New command line interface: Probabilistic, Deterministic and PFT Tracking.
  • Integration of Cython Guidelines for developers.
  • Replacement of Nose by Pytest.
  • Documentation update.
  • Closed 103 issues and merged 41 pull requests.
  • 0.15 (Wednesday, 12 December 2018)
  • Updated RecoBundles for automatic anatomical bundle segmentation.
  • New Reconstruction Model: qtau-dMRI.
  • New command line interfaces (e.g. dipy_slr).
  • New continuous integration with AppVeyor CI.
  • Nibabel Streamlines API now used almost everywhere for better memory management.
  • Compatibility with Python 3.7.
  • Many tutorials added or updated (5 New).
  • Large documentation update.
  • Moved visualization module to a new library: FURY.
  • Closed 287 issues and merged 93 pull requests.
  • 0.14 (Tuesday, 1 May 2018)
  • RecoBundles: anatomically relevant segmentation of bundles
  • New super fast clustering algorithm: QuickBundlesX
  • New tracking algorithm: Particle Filtering Tracking.
  • New tracking algorithm: Probabilistic Residual Bootstrap Tracking.
  • Integration of the Streamlines API for reading, saving and processing tractograms.
  • Fiber ORientation Estimated using Continuous Axially Symmetric Tensors (Forecast).
  • New command line interfaces.
  • Deprecated fvtk (old visualization framework).
  • A range of new visualization improvements.
  • Large documentation update.
  • 0.13 (Monday, 24 October 2017)
  • Faster local PCA implementation.
  • Fixed different issues with OpenMP and Windows / OSX.
  • Replacement of cvxopt by cvxpy.
  • Replacement of Pytables by h5py.
  • Updated API to support latest numpy version (1.14).
  • New user interfaces for visualization.
  • Large documentation update.
  • 0.12 (Tuesday, 26 June 2017)
  • IVIM Simultaneous modeling of perfusion and diffusion.
  • MAPL, tissue microstructure estimation using Laplacian-regularized MAP-MRI.
  • DKI-based microstructural modelling.
  • Free water diffusion tensor imaging.
  • Denoising using Local PCA.
  • Streamline-based registration (SLR).
  • Fiber to bundle coherence (FBC) measures.
  • Bayesian MRF-based tissue classification.
  • New API for integrated user interfaces.
  • New hdf5 file (.pam5) for saving reconstruction results.
  • Interactive slicing of images, ODFS and peaks.
  • Updated API to support latest numpy versions.
  • New system for automatically generating command line interfaces.
  • Faster computation of Cross Correlation metric for registration.
  • 0.11 (Sunday, 21 February 2016)
  • New framework for contextual enhancement of ODFs.
  • Compatibility with numpy (1.11).
  • Compatibility with VTK 7.0 which supports Python 3.x.
  • Faster PIESNO for noise estimation.
  • Reorient gradient directions according to motion correction parameters.
  • Supporting Python 3.3+ but not 3.2.
  • Reduced memory usage in DTI.
  • DSI now can use datasets with multiple b0s.
  • Fixed different issues with Windows 64bit and Python 3.5.
  • 0.10 (Thursday, 2 December 2015)
  • Compatibility with new versions of scipy (0.16) and numpy (1.10).
  • New cleaner visualization API, including compatibility with VTK 6, and functions to create your own interactive visualizations.
  • Diffusion Kurtosis Imaging(DKI): Google Summer of Code work by Rafael Henriques.
  • Mean Apparent Propagator (MAP) MRI for tissue microstructure estimation.
  • Anisotropic Power Maps from spherical harmonic coefficients.
  • New framework for affine registration of images.
  • 0.9.2 (Wednesday, 18 March 2015)
  • Anatomically Constrained Tissue Classifiers for Tracking
  • Massive speedup of Constrained Spherical Deconvolution (CSD)
  • Recursive calibration of response function for CSD
  • New experimental framework for clustering
  • Improvements and 10X speedup for Quickbundles
  • Improvements in Linear Fascicle Evaluation (LiFE)
  • New implementation of Geodesic Anisotropy
  • New efficient transformation functions for registration
  • Sparse Fascicle Model supports acquisitions with multiple b-values
  • 0.8.0 (Tuesday, 6 Jan 2015)
  • Nonlinear Image-based Registration (SyN)
  • Streamline-based Linear Registration (SLR)
  • Linear Fascicle Evaluation (LiFE)
  • Cross-validation for reconstruction models
  • Sparse Fascicle Model (SFM)
  • Non-local means denoising (NLMEANS)
  • New modular tracking machinery
  • Closed 388 issues and merged 155 pull requests
  • A variety of bug-fixes and speed improvements
  • 0.7.1 (Thursday, 16 Jan 2014)
  • Made installing Dipy easier and more universal
  • Fixed automated seeding problems for tracking
  • Removed default parameter for odf_vertices in EuDX
  • 0.7.0 (Monday, 23 Dec 2013)
  • Constrained Spherical Deconvolution (CSD)
  • Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE)
  • Sharpening Deconvolution Transform (SDT)
  • Signal-to-noise ratio estimation
  • Parallel processing enabled for all reconstruction models using peaks_from_model
  • Simultaneous peak and ODF visualization
  • Streamtube visualization
  • Electrostatic repulsion for sphere generation
  • Connectivity matrices and density maps
  • Streamline filtering through specific ROIs using target
  • Brain extraction and foreground extraction using median_otsu
  • RESTORE fitting for DTI
  • Westin's Tensor maps
  • Access to more publicly available datasets directly through Dipy functions.
  • 3x more tutorials than previous release
  • 0.6.0 (Sunday, 24 Mar 2013)
  • Cython 0.17+ enforced
  • New reconstruction models API
  • Diffusion Spectrum Imaging (DSI)
  • DSI with deconvolution
  • Generalized Q-sampling Imaging 2 (GQI2)
  • Modular fiber tracking * deterministic * probabilistic
  • Fast volume indexing (a faster ndindex)
  • Spherical Harmonic Models * Opdt (Tristan-Vega et. al) * CSA odf (Aganj et. al) * Analytical Q-ball (Descoteaux et. al) * Tuch's Q-ball (Tuch et. al)
  • Visualization of spherical functions
  • Peak finding in odfs
  • Non-linear peak finding
  • Sphere Object
  • Gradients Object
  • 2D sphere plotting
  • MultiTensor and Ball & Sticks voxel simulations
  • Fetch/Download data for examples
  • Software phantom generation
  • Angular similarity for comparisons between multiple peaks
  • SingleVoxelModel to MultiVoxelModel decorator
  • Mrtrix and fibernavigator SH bases
  • More Benchmarks
  • More Tests
  • Color FA and other Tensor metrics added
  • Scripts for the ISBI 2013 competition
  • Fit_tensor script added
  • Radial basis function interpolation on the sphere
  • New examples/tutorials
  • 0.5.0 (Friday, 11 Feb 2011)
    • Initial release.
      • Reconstruction algorithms e.g. GQI, DTI
      • Tractography generation algorithms e.g. EuDX
      • Intelligent downsampling of tracks
      • Ultra fast tractography clustering
      • Resampling datasets with anisotropic voxels to isotropic
      • Visualizing multiple brains simultaneously
      • Finding track correspondence between different brains
      • Reading many different file formats e.g. Trackvis or Nifti
      • Dealing with huge tractographies without memory restrictions
      • Playing with datasets interactively without storing
      • And much more and even more to come in next releases