All notable changes to this project will be documented in this file.
- 🆕 model:
inversion_recovery
- Add general equation fitting in addition to Barral's model.
- GUI (JOSS review by @mfroeling)
- Please see changes here.
- Documentation (JOSS review by @grlee77)
- Please see changes here
FilterClas
bug fix.
- Change citation reference to JOSS paper
- Karakuzu A., Boudreau M., Duval T.,Boshkovski T., Leppert I.R., Cabana J.F., Gagnon I., Beliveau P., Pike G.B., Cohen-Adad J., Stikov N. (2020), qMRLab: Quantitative MRI analysis, under one umbrella doi: 10.21105/joss.02343
- 🆕 model:
mp2rage
- Fit MP2RAGE data to create a T1map.
- The original codebase is here.
- Check out qMRLab's MP2RAGE blog post by @mathieuboudreau!
- 🆕 model:
mono_t2
- Fit MESE data to create a T2map.
- 🆕 simulator:
Monte-Carlo Diffusion
- Monte Carlo simulator for 2D diffusion is able to generate synthetic diffusion signal from any 2D axon packing.
- An MRathon project by @Yasuhik, @TomMingasson and @tanguyduval.
- 🆕 Changelog ❤️
- Model:
qsm_sb
- With the new echo combination implementation,
qsm_sb
can now take multi-echo GRE data. - An MRathon project by @jeremie-fouquet.
- With the new echo combination implementation,
- Get rid of redundant buttons in GUI
Protocol
panel.
qMRgenBatch
account for models w/o fixed required inputs (e.g.mp2rage
).- Remove old built packages from
qmrlab/mcrgui
. - Fix
qmrlab/octjn
dependencies.
- 🆕 static member function: getProvenance
- Scrape details and add more (optional) to save sidecar
*.json
files for maps. - See an example use here.
- Scrape details and add more (optional) to save sidecar
- 🆕 Docker image:
qmrlab/minimal
- qMRLab + Octave - Jupyter for qMRFlow pipelines.
- New MATLAB/Octave env:
ISNEXTFLOW
- Deals with the
load_nii
case for symlinked inputs. - Enforces
gzip -d --force
ifISNEXTFLOW
- Commonly used by
qMRWrappers
- Deals with the
- N/A
- N/A
- 🆕 model:
Processing/filtermap
- Apply 2D/3D spatial filtering, primarily intended for fieldmaps.
Polynomial
Gaussian
Median
Spline
- Apply 2D/3D spatial filtering, primarily intended for fieldmaps.
- 🆕 model:
qsm_sb
- Fast quantitative susceptibility mapping:
Split-Bregman
L1 Regularization
L2 Regulatization
No Regularization
SHARP background filtering
- Fast quantitative susceptibility mapping:
- 🆕 model:
mt_ratio
- Semi-quantitative MTR.
- 🆕 GUI 3D toolbox:
- An array of UI tools for the visualization and brief statistical inspection of the data using ROI tools.
- 🆕 functionality
qMRgenJNB
:- Create a Jupyter Notebook for any model.
- Insert Binder Badge to the documentation.
- 🆕 Azure release pipelines and deployment protocols:
- Set self-hosted Azure agent to compile qMRLab and ship in a Docker image
qmrlab/mcrgui
: Use qMRLab GUI in a Docker image.qmrlab/octjn
: Use qMRLab in Octave in Jupyter Env.- See
/Deploy
folder for furhter details. - qMRLab DockerHub page.
- Model:
vfa_t1
:- Bloch simulations are added
- Performance improvement
- Model:
ir_t1
- Parameter descriptions are improved.
- Model:
b1_dam
- Protocol descriptions has been updated.
FitTempResults
:- Is now saved every 5 minutes instead of every 20 voxels.
- GUI fixes.
- N/A