Artificial intelligence-based models for quantification of intra-pancreatic fat deposition and their clinical relevance: a systematic review of imaging studies

Tej Joshi, John Virostko, Maxim S. Petrov

Open source

DOI
10.1007/s00330-025-11808-6
Published
2025-07-19
Container
European Radiology
Publisher
Springer Science and Business Media LLC
Open access
unknown

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BibTeX

@article{allodium:10.1007/s00330-025-11808-6,
  title = {Artificial intelligence-based models for quantification of intra-pancreatic fat deposition and their clinical relevance: a systematic review of imaging studies},
  author = {Tej Joshi and John Virostko and Maxim S. Petrov},
  year = {2025},
  journal = {European Radiology},
  doi = {10.1007/s00330-025-11808-6},
  url = {https://doi.org/10.1007/s00330-025-11808-6}
}

RIS

TY  - JOUR
TI  - Artificial intelligence-based models for quantification of intra-pancreatic fat deposition and their clinical relevance: a systematic review of imaging studies
AU  - Tej Joshi
AU  - John Virostko
AU  - Maxim S. Petrov
PY  - 2025
JO  - European Radiology
DO  - 10.1007/s00330-025-11808-6
UR  - https://doi.org/10.1007/s00330-025-11808-6
ER  - 

APA

Joshi, T., Virostko, J., & Petrov, M. S. (2025). Artificial intelligence-based models for quantification of intra-pancreatic fat deposition and their clinical relevance: a systematic review of imaging studies. European Radiology. https://doi.org/10.1007/s00330-025-11808-6

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