Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.
- DOI
- 10.1007/s00330-026-12346-5
- Published
- 2026-02-05
- Container
- Eur Radiol
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1007/s00330-026-12346-5,
title = {Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.},
author = {Yang S and Sartoris R and Teyssier Y and Bône A and Ronot M and Decaens T and Glaunès JA and Aubé C.},
year = {2026},
journal = {Eur Radiol},
doi = {10.1007/s00330-026-12346-5},
url = {https://doi.org/10.1007/s00330-026-12346-5}
}RIS
TY - JOUR TI - Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease. AU - Yang S AU - Sartoris R AU - Teyssier Y AU - Bône A AU - Ronot M AU - Decaens T AU - Glaunès JA AU - Aubé C. PY - 2026 JO - Eur Radiol DO - 10.1007/s00330-026-12346-5 UR - https://doi.org/10.1007/s00330-026-12346-5 ER -
APA
S, Y., R, S., Y, T., A, B., M, R., T, D., JA, G., & C., A. (2026). Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.. Eur Radiol. https://doi.org/10.1007/s00330-026-12346-5
Source records
- europe-pmc · retrieved 2026-11-10T11:14:20.508Z
- hal · retrieved 2026-11-10T11:14:20.565Z