Constrained self-supervised method with temporal ensembling for fiber bundle detection on anatomic tracing data

Contents

• citation
• installation
• dependencies
• example
• network architecture
• results

Citation

If you use Fiber Segmentation Tool (FibSeg), please cite the following papers:

• Sundaresan, V., Lehman, J.F., Fitzgibbon, S., Jbabdi, S., Haber, S.N. and Yendiki, A., 2022, September. Constrained self-supervised method with temporal ensembling for fiber bundle detection on anatomic tracing data. In International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis (pp. 115-125). Cham: Springer Nature Switzerland. Preprint: arXiv:2208.03569

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Dependencies

• Main fibseg dependencies:
  • Python > 3.6
  • PyTorch=1.5.0
• Extra dependencies for label extraction:
  • TIRL and Slider (https://git.fmrib.ox.ac.uk/seanf/slider)

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Installation

To install the fibseg tool do the following:

1. Clone the git repository into your local directory.

• If you are not familiar with GitHub then the easiest way is to use the button labelled <> Code (right hand side, just above the file list) on the main truenet page and select the Download ZIP option. After you've done this, move the zip file to where you want to have truenet installed and unzip it.

3. Open up a terminal, go to the directory where you unzipped the file, and then run:

python setup.py install

3. Use the instructions in this document (simple usage is recommended for beginners)
4. For more advanced usage, detailed lists of options for the subcommands are available in the command-line help:

fibseg --help

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Examples

• Run a pretrained model on an histological slice.

mkdir Results/

fibseg evaluate -i Input/directory -m /model_directory/pretrained_model_name.pth -o Results/

Note: The link for teh repository containing the pretrained model weights to be updated soon.

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Network architecture:

Fiber bundle segmentation results: