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Integrate simple image processing like histogram matching and grey-scale images. Adding generated documentation hosted on readthedocs.
- add pre-processing - hist. match & grey-scale
- add SoA experiments - DROP
- add auto api-doc & ipynb examples
- refactor VTK points; rename .txt -> .pts
- update package/experiments/scripts
- refactor parallel proc.
- minor ANHIR refactor (mails)
- update setup & CI
General update related to Automatic Non-rigid Histological Image Registration (ANHIR) challenge participation, handling incomplete datasets and generating rich registration statistic. A notebook with visual comparisons of ANHIR 2019 participants is included.
- fix export images/landmarks
- relativize expteriment paths
- reformat expt. run & returns
- add affine & elastic transform statistic
- include weighted TRE
- redefine (TRE) robustness
- add hist. matching & SIFT for bUnwarpJ
- add RNiftyReg & ANTsPy method
- use YAML configs
BIRL: Benchmark on Image Registration methods with Landmark validation
The project aims at automatic evaluation of state-of-the-art image registration methods based on landmark annotation for given image dataset. In particular, this project is the main evaluation framework for ANHIR challenge.
- automatic execution of image registration on a sequence of image pairs
- integrated evaluation of registration performances
- integrated visualization of performed registration
- running several image registration experiment in parallel
- resuming unfinished sequence of registration benchmark
- handling around dataset and creating own experiments
- rerun evaluation and visualisation for finished experiments