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| author | Daniil Kazantsev <dkazanc3@googlemail.com> | 2018-04-09 15:17:24 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-04-09 15:17:24 +0100 |
| commit | 62635199f4e5a464a267ffce070ecec68bfdcfe8 (patch) | |
| tree | cdc7c4469e210a52cb416b2747ca2d954da073cc /Readme.md | |
| parent | a5b5872b76bf00023a7e7cee97e028003ccbc45e (diff) | |
| parent | b9fafd363d1d181a4a8b42ea4038924097207913 (diff) | |
| download | regularization-62635199f4e5a464a267ffce070ecec68bfdcfe8.tar.gz regularization-62635199f4e5a464a267ffce070ecec68bfdcfe8.tar.bz2 regularization-62635199f4e5a464a267ffce070ecec68bfdcfe8.tar.xz regularization-62635199f4e5a464a267ffce070ecec68bfdcfe8.zip | |
Merge pull request #47 from vais-ral/add3Dtests
major renaming and new 3D demos for Matlab
Diffstat (limited to 'Readme.md')
| -rw-r--r-- | Readme.md | 14 |
1 files changed, 7 insertions, 7 deletions
@@ -1,7 +1,7 @@ -# CCPi-Regularization Toolkit (CCPi-RGL) +# CCPi-Regularisation Toolkit (CCPi-RGL) -**Iterative image reconstruction (IIR) methods normally require regularization to stabilize the convergence and make the reconstruction problem more well-posed. -CCPi-RGL software consist of 2D/3D regularization modules for single-channel and multi-channel reconstruction problems. The modules especially suited for IIR, however, +**Iterative image reconstruction (IIR) methods normally require regularisation to stabilise the convergence and make the reconstruction problem more well-posed. +CCPi-RGL software consist of 2D/3D regularisation modules for single-channel and multi-channel reconstruction problems. The modules especially suited for IIR, however, can also be used as image denoising iterative filters. The core modules are written in C-OMP and CUDA languages and wrappers for Matlab and Python are provided.** ## Prerequisites: @@ -24,13 +24,13 @@ can also be used as image denoising iterative filters. The core modules are writ ### Python (conda-build) ``` export CIL_VERSION=0.9.2 - conda build recipes/regularizers --numpy 1.12 --python 3.5 - conda install cil_regularizer=0.9.2 --use-local --force + conda build recipes/regularisers --numpy 1.12 --python 3.5 + conda install cil_regulariser=0.9.2 --use-local --force cd Wrappers/Python conda build conda-recipe --numpy 1.12 --python 3.5 - conda install ccpi-regularizer=0.9.2 --use-local --force + conda install ccpi-regulariser=0.9.2 --use-local --force cd test/ - python test_cpu_vs_gpu_regularizers.py + python test_cpu_vs_gpu_regularisers.py ``` ### Matlab ``` |