TMI published

Minor bug fixing and refactoring/cleaning for TMI publication.

Main changes:

• added docker images with SOTA, published in DockerHub
• split req. py27 and py3 and minimal requirements
• rename data-images, move figures and drop SVG & GIF
• fixed sphinx docs
• fixed notebooks

CIMA experiment

Minor bug fixing and adjustments related to SOTA experimentation on CIMA dataset.

Main changes:

• adding notebooks for CIMA scope and notebook w. scope compare
• adding SOTA results on CIMA dataset
• fix handling too large images, evaluation and figure export
• reverting to absolute imports
• adding STD to evaluations
• update shell experiments

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Borovec, J. (2019). BIRL: Benchmark on Image Registration methods with Landmark validation. arXiv preprint arXiv:1912.13452.

SOA methods & refactoring

Extended update related to Automatic Non-rigid Histological Image Registration (ANHIR) submission, adding SOA methods, package refactoring, updating evaluation. Also, the ANHIR notebook with visual comparisons is updated accordingly.

Added State-of-The-Art methods:

• ANTs & ANTsPy
• DROP2
• Elastix
• RVSS (ImageJ)

Main changes:

• cut-out package tests
• use package relative imports
• add command timeout & fix hist. match
• rename measures TRE, IRE
• update eval. submission
  • eval: jit filter landmarks
  • update compute stats
• minor refacroting:
  • rename some variables & parameters
  • simplify expt. mains - Bm.main
  • move constants/methods to class
  • move Experiments to birl.utilities.experiments
  • rename visualisation and cls_benchmarks
• update ANHIR results in ipynb
• using enlighten progress-bar
• update docs & fix ReadTheDocs
• resize sample images/landmarks

Pre-proc & Docs

Integrate simple image processing like histogram matching and grey-scale images. Adding generated documentation hosted on readthedocs.

Main changes:

• 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

ANHIR update

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.

Main changes:

• 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

Initial release

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.

Main Features:

• 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

Borovec, J., Munoz-Barrutia, A., & Kybic, J. (2018). Benchmarking of image registration methods for differently stained histological slides. In IEEE International Conference on Image Processing (ICIP) (pp. 3368–3372), Athens. DOI: 10.1109/ICIP.2018.8451040