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CUBIC-informatics

Getting Started

Hardware Prerequisites

Software Prerequisites

Tested on Cent OS 7.5 with the following versions of software.

  • Cmake 2.8.12
  • GNU Compiler Collection 4.8.5
  • Python 3.6.4
  • Julia 0.6.3
  • CUDA Toolkit 9.0
  • ANTs 2.1.0

Source Image Prerequisites

  1. Source images should be in binary format. Batch image conversion from TIFF to binary can be performed with script/tiff2bin.py.

  2. Source image files are assumed to be named like:

/path/to/src/YNAME/YNAME_XNAME/ZNAME.bin

  • XNAME,YNAME is the number specifies the origin of the stack
  • ZNAME is the slice number

Conversion rule from these names to physical position should be provided in the HDoG parameter files.

Downloading source codes and reference data

git clone https://github.com/lsb-riken/CUBIC-informatics
cd CUBIC-informatics

Download CUBIC-Atlas reference data from here.

Building C++/CUDA programs

Some programs use helper functions in CUDA Toolkit. Create a symbolic link in the source directory. The path of CUDA Toolkit depends on your system setup.

ln -s /usr/local/cuda/samples/common common

Build programs under build directory. Please change CUDA_NVCC_FLAGS in CMakeLists.txt to match the compute capability of your GPU devices.

mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=. ..
make
make install

Installing python packages

pip install -r requirements.txt

Cell/Nucleus detection

  1. Preparing HDoG parameter files for nuclear staining images

    example: param/param_example_HDoG_FW.json, param/param_example_HDoG_RV.json

  2. Preparing Merge parameter file

    example: param/param_example_mergebrain.json

  3. Preparing Classify parameter file

    example: param/param_example_classify.json

  4. Preparing HDoG and Merge parameter file as well for other channel images

  5. Preparing MultiChannel parameter file

    example: param/param_example_multichannel.json

Tiling check

python script/MergeBrain.py images param/param_example_mergebrain.json

Whole brain image in TIFF format is created.

Cell candidate detection

python script/HDoG_gpu.py param/param_example_HDoG_FW.json
python script/HDoG_gpu.py param/param_example_HDoG_RV.json

Cell candidate detection is performed on GPUs for forward side and reverse side.

python script/MergeBrain.py cells param/param_example_mergebrain.json

Candidate detection results on each side is merged.

Candidate verification

python script/HDoG_classify.py param/param_example_classify.json

Create a classifier with manual decision boundary and plot cell candidates in feature space. By setting use_manual_boundary in the parameter file to be false, you can also perform unsupervised clustering and create classifier automatically.

Multi-channel verification

python script/MultiChannelVerification.py param/param_example_multichannel.json

Alignment and annotation

  1. Preparing Mapping parameter file

    example: param/param_example_mapping.json

Registration

python script/AtlasMapping.py registration param/param_example_mapping.json

Annotation

python script/AtlasMapping.py annotation param/param_example_mapping.json

Intermediate result validation

python script/HDoG_intermediate.py param_param_example_mergebrain.json CB1_on_850-900_148804_249860_1000-1250_750-1000

Second argument of the script defines which part of images to be processed. It is in the following format :

REGIONNAME_FWorRV_ZLOCALstart-ZLOCALend_YNAME_XNAME_YLOCALstart-YLOCALend_XLOCALstart_XLOCALend

  • REGIONNAME is a label for human
  • FWorRV should be either FW, off, RV or on
  • YNAME,XNAME specify which stack to be used.
  • ZLOCALstart,ZLOCALend specify which images in the stack to be used. 0 corresponds to the first image in the stack.
  • YLOCALstart,YLOCAL_end,XLOCALstart,XLOCALend specify which area in images to be used. (0,0) corresponds to the top left pixel.

Advanced Usage

If you want to check how the algorithm works, there is a program to test each step in the algorithm. As a python implementation, we have script/HDoG_cpu.py.

Also we have CUDA programs for each step. To build these programs, run make DoG_test for example and the binary is created under build/test/ directory.