tiramisu-brulee 0.1.5

A 2D and 3D PyTorch implementation of the Tiramisu CNN

tiramisù-brûlée

A 2D and 3D PyTorch implementation of the Tiramisu CNN

This package is primarily used for multiple sclerosis (MS) lesion segmentation; specifically, T2 lesions in the brain.

• Free software: Apache Software License 2.0

• Documentation: https://tiramisu-brulee.readthedocs.io.

Install

The easiest way to install the package is with:

pip install tiramisu-brulee

Alternatively, you can download the source and run:

python setup.py install

If you want a CLI to train a 3D lesion segmentation model, install with:

pip install "tiramisu-brulee[lesionseg]"

Basic Usage

Import the 2D or 3D Tiramisu version with:

from tiramisu_brulee.model import Tiramisu2d, Tiramisu3d

References

[1] Jégou, Simon, et al. “The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation.” CVPR. 2017.

[2] Zhang, Huahong, et al. “Multiple sclerosis lesion segmentation with Tiramisu and 2.5D stacked slices.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019.

Why the name?

Why is the name tiramisù-brûlée? Well, tiramisù is named after the neural network [1] whose name is inspired by the dessert; however, tiramisu—by itself—was already taken as a package on PyPI. I added brûlée to get around the existence of that package and because this package is written in PyTorch (torch -> burnt). Plus brûlée in English is often associated with the dessert crème brûlée. Why combine an Italian word (tiramisù) with a French word (brûlée)? Because I didn’t think about it until after I already deployed the package to PyPI.

History

0.1.4 (2021-05-13)

• Add lesion segmentation CLI.

0.1.3 (2021-05-13)

• Fix deployment by fixing repo name in travis.

0.1.2 (2021-05-13)

• Fix supported versions and docs.

0.1.1 (2021-05-13)

• Fix tests and deployment.

0.1.0 (2021-05-13)

• First release on PyPI.