Warning: This document is for an old version of dmriprep. The main version is master.

Development road-map

This road-map serves as a guide for developers as well as a way for us to communicate to users and other stake-holders about the expectations they should have for the current functionality of the software and future developments.

If you would like to be part of the team developing this road-map, please be sure to read our Contributors Guidelines. Then, you can contact the developers through the Mattermost channel to be invited to our bi-weekly meetings.

This road-map proposes a RERO philosophy, scheduling a monthly release until the first stable 1.0 release is reached.

Important

Updated: Dec 18, 2020 Latest release: 0.3.0 (October 13, 2020).

Version 0.4 (Before end of 2020)

Version 0.4 will condense all the outcomes of our sprint towards ISMRM’s 2021 abstracts deadline. This mostly includes house-keeping work, and most prominently, the integration of the SDCFlows 2.0 alpha releases, which makes dMRIPrep go ahead of fMRIPrep in addressing distortions caused by \(B_0\) inhomogeneity.

This release will also include Salim’s efforts in #144 to provide a temporary implementation of head-motion and eddy-currents correction using FSL’s eddy. This temporary solution will be replaced by our 3dSHORE-based algorithm ported from QSIPREP, and left in place for researchers who prefer this option.

Version 0.5 (January, 2021)

  1. Continue with the SDCFlows 2.0 integration:

    • Cover more complex fieldmap specifications

    • Automatically set up “fieldmap-less” estimations

  2. Framewise-displacement (or equivalent) calculation

    We will identify volumes that are outliers in terms of head-motion, or other severe artifacts that make them likely candidates for exclusion from further analysis. Regarding the or equivalent note above: following with this conversation, it could be interesting to calculate some sort of average displacement of voxels within the white-matter mask instead.

  3. Finalize ongoing PRs about reporting number of shells

  4. First draft of ISBI 2021 tutorial:

    • Accept the design for our ISBI 2021 tutorial and document it on the notebooks repo.

    • First draft

    • Start development

    • Plan for supporting Derek and Ariel in taking the head-motion correction to the finish line.

Version 0.6 (February, 2021)

  1. Head motion correction.

    A SHOREline-based approach, ported from QSIPREP. In cases where the data are “shelled”, 3dSHORE will be used as the diffusion model. If the data are single-shell, we will use SFM as the diffusion model.

  2. \(B_1\) inhomogeneity correction

    • Decide whether it can be brought around from estimation on T1w images

    • Decide whether it should be a default-off option that can be enabled with a flag, or else, generate both conversions always.

  3. Initiate Phase I of testing

    • Compose our test-bed dataset

    • Document Phase I testing and reporting protocols

    • Start execution

# Continue with the development of ISBI 2021 tutorial

Version 0.7 (March, 2021)

The noisy month. This is not a musical event, but a development cycle where we will focus on the implementation of steps addressing noise in DWI:

  1. Identification of outlier measurements (+ imputation?)

  2. Implementation of component-based noise identification techniques

    • Comparison of multiple approaches including MP-PCA, NLMeans, and Patch2Self (#132)

  3. Gibbs-ringing: investigate whether it should be estimated if other techniques are in place (i.e., component-based above), and ordering of steps.

  4. Rician bias modeling.

  5. DWI carpet-plot and confounds collation.

  6. Testing Phase I execution

  7. Final release of the ISBI 2021 tutorial

Version 0.8 (April, 2021)

This release will only address bugfixes conducive to finishing evaluation Phase I, which should conform a pretty solid ensemble ready for premiere in ISMRM 2021.

Version 0.9 (May, 2021)

  1. First official presentation at ISMRM 2021 (should the abstract be accepted)

  2. Evaluation Phase II starts.

  • Determine an appropriate dataset

  • Plan for benchmarking experiments (#121)

  • Start with addressing issues as they are reported

Version 1.0 (Targetted for September 2021)

Wrap-up evaluation Phase II with the first stable release of dMRIPrep.

Long-term plans

In the long run we would like to explore the following processing steps:

  • Gradient non-linearity correction