Original Repository | Original Paper | Citation
This is a fork of the Comp2Comp repository. Please refer to the original repository for more information.
This fork is a lightweight version of the original Comp2Comp repository. Some quick and dirty adaptions were made to reduce dependencies, complexity and required writing rights on the host system, making the implementation at HPC-systems simpler.
- predefined pipeline, reduced arguments
- reduction of dependencies (e.g. dosma)
- reduced output
- usage of the original TotalSegmentator instead of the forked Standford version
- download and integration of weights and models prior to execution
- paths moved to parent directory
- files and modules not needed removed
If you use this code, you should cite the following papers:
Blankemeier L., Desai A., Chaves J. M. Z., Wentland A., Yao S., Reis E., Jensen M., Bahl B., Arora K., Patel, B. N. et al. Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography, 2023. URL: https://arxiv.org/abs/2302.06568. arXiv: 2302.06568
Wasserthal J., Meyer M., Breit H., Cyriac J., Yang S., Segeroth M. TotalSegmentator: robust segmentation of 104 anatomical structures in CT images, 2022. URL: https://arxiv.org/abs/2208.05868. arXiv: 2208.05868
Isensee, F., Jaeger, P. F., Kohl, S. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nature methods, 18(2), 203-211.