Abstract
SAND2020-14119 O A Tensorflow and Keras-backed framework for learned segmentation methods of 3D CT scan volumes. Supported functionality includes training models, running inference and quantifying uncertainty. The main underlying model architecture is V-Net. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
- Developers:
-
Ganter, Tyler [1][2][3] ; Martinez, Carianne [1][2][3] ; Potter, Kevin [1][2][3] ; LaBonte, Tyler [1][2][3]
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Release Date:
- 2021-01-20
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Python
- Version:
- .1
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:NA0003525
- Code ID:
- 78111
- Site Accession Number:
- SCR #2589
- Research Org.:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Country of Origin:
- United States
Citation Formats
Ganter, Tyler, Martinez, Carianne, Potter, Kevin, and LaBonte, Tyler.
Keras CT Segmentation v.1.
Computer Software.
https://github.com/sandialabs/mcdn-3d-seg.
USDOE.
20 Jan. 2021.
Web.
doi:10.11578/dc.20220802.3.
Ganter, Tyler, Martinez, Carianne, Potter, Kevin, & LaBonte, Tyler.
(2021, January 20).
Keras CT Segmentation v.1.
[Computer software].
https://github.com/sandialabs/mcdn-3d-seg.
https://doi.org/10.11578/dc.20220802.3.
Ganter, Tyler, Martinez, Carianne, Potter, Kevin, and LaBonte, Tyler.
"Keras CT Segmentation v.1." Computer software.
January 20, 2021.
https://github.com/sandialabs/mcdn-3d-seg.
https://doi.org/10.11578/dc.20220802.3.
@misc{
doecode_78111,
title = {Keras CT Segmentation v.1},
author = {Ganter, Tyler and Martinez, Carianne and Potter, Kevin and LaBonte, Tyler},
abstractNote = {SAND2020-14119 O A Tensorflow and Keras-backed framework for learned segmentation methods of 3D CT scan volumes. Supported functionality includes training models, running inference and quantifying uncertainty. The main underlying model architecture is V-Net. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20220802.3},
url = {https://doi.org/10.11578/dc.20220802.3},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20220802.3}},
year = {2021},
month = {jan}
}