docs: revise *dMRIPrep*'s road-map

Resolves: #116.

Author: oesteban

docs/roadmap.rst

@@ -1,70 +1,127 @@
 .. include:: links.rst
 
---------------------
-Development road map
---------------------
+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 aboout the expectations they should
 have about the current functionality of the software and future developments.
 
-Version 0.3 (Targetted for March 1st, 2020)
--------------------------------------------
-This version should be considered an early alpha of the software, but will
-contain a full pipeline of processing from a raw BIDS dataset to analyzable data.
+If you want to be part of the team developing this road-map, please make sure you
+take a look into our `Contributors Guidelines <https://www.nipreps.org/community/CONTRIBUTING>`__.
+Then, please write one of the developers to be invited to our bi-weekly meetings.
 
-At this point, the processing pipeline will include the following major steps:
+This road-map proposes a :abbr:`RERO (release early, release often)` planning, scheduling
+a monthly release until the first stable 1.0 release is reached.
 
-#. Susceptibility distortion correction.
-    Using `SDCFlows <https://github.com/poldracklab/sdcflows>`__
+.. important::
 
-#. Signal drift estimation
-    Leveraging the :math:`b=0` extraction, rescaling and averaging that was merged in `#50 <https://github.com/nipreps/dmriprep/pull/50>`__
+    Updated: Dec 18, 2020
+    Latest release: `0.3.0 (October 13, 2020) <changes.html#october-13-2020>`__.
 
-Version 0.4 (April 1st, 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
+:math:`B_0` inhomogeneity.
+
+This release will also include Salim's efforts in `#144 <https://github.com/nipreps/dmriprep/pull/144>`__
+to provide with 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)
+---------------------------
+#. Continue with the *SDCFlows 2.0* integration:
+
+    - Cover more complex fieldmap specifications
+    - Automatically set up "*fieldmap-less*" estimations
+
+#. 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
+    <https://neurostars.org/t/head-motion-parameters-different-when-using-fmriprep-and-spm/17386/4>`__,
+    it could be interesting to calculate some sort of average displacement of voxels
+    within the white-matter mask instead.
+
+#. Finalize ongoing PRs about reporting number of shells
+
+    - `#73 <https://github.com/nipreps/dmriprep/pull/73>`__
+    - `#129 <https://github.com/nipreps/dmriprep/pull/129>`__
+
+#. 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)
+----------------------------
 #. 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.
 
-#. Eddy current correction.
+#. :math:`B_1` inhomogeneity correction
 
-    We will explore the possible adaptations of the HMC based on SHOREline above.
-    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.
+    - 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.
 
-#. Framewise-displacement calculation
+#. Initiate Phase I of testing
 
-    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.
+    - Compose our test-bed dataset
+    - Document Phase I testing and reporting protocols
+    - Start execution
 
-Version 0.5 (May 1st, 2020)
-----------------------------
-#. Registration between dMRI and T1w image.
+# 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:
 
 #. Identification of outlier measurements (+ imputation?)
 
-If we get around to doing thesee steps earlier, they can also be included in
-earlier releases.
+#. Implementation of component-based noise identification techniques
 
+#. Gibbs-ringing: investigate whether it should be estimated if other techniques
+   are in place (i.e., component-based above), and ordering of steps.
 
-Version 1.0 (Targetted for September 2020)
-------------------------------------------
-After integrating the above steps, we will spend the time leading to a 1.0
-testing the software on various datasets, evaluating and validating the
-resulting derivatives.
+#. Rician bias modeling.
+
+#. DWI carpet-plot and confounds collation.
 
+#. Testing Phase I execution
+
+#. 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)
+-----------------------
+#. First official presentation at ISMRM 2021 (should the abstract be accepted)
+#. Evaluation Phase II starts.
+
+  - Determine an appropriate dataset
+  - Plan for benchmarking experiments (`#121 <https://github.com/nipreps/dmriprep/issues/121>`__)
+  - Start with addressing issues as the 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:
 
-- Gibbs ringing (using DIPY's image-based implementation).
-- Denoising (e.g., MP-PCA)
-- Rician bias correction
 - Gradient non-linearity correction
-- B1 inhomogeneity field estimation and :abbr:`INU (intensity non-uniformity) correction`
-- Signal drift correction