Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does improved image quality translate to better resectability assessment?
Although deep learning-based combined noise reduction and contrast enhancement reconstruction significantly improved quantitative and subjective image quality metrics, it did not enhance diagnostic accuracy for predicting R0 resectability in post-neoadjuvant pancreatic cancer patients.
Authors
- Sun Kyung Jeon (ORCID: https://orcid.org/0000-0002-8991-3986)
- Liang Zhu (ORCID: https://orcid.org/0000-0003-3779-7853)
- Junghoan Park (ORCID: https://orcid.org/0000-0002-0636-3756)
- Jeongin Yoo (ORCID: https://orcid.org/0000-0002-3267-2544)
- Jeong Hee Yoon (ORCID: https://orcid.org/0000-0002-9925-9973)
- Hyo‐Jin Kang (ORCID: https://orcid.org/0000-0002-6771-2112)
- Jeong Min Lee (ORCID: https://orcid.org/0000-0003-0561-8777)
- Seok Jin Hong (ORCID: https://orcid.org/0000-0002-5301-6140)
Institutions
- Seoul National University (KR)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- Gyeongsang National University Hospital (KR)
- National University College (PR)
Publication Details
- Journal
- Abdominal Radiology
- Published
- 2025-11-04
- DOI
- https://doi.org/10.1007/s00261-025-05271-6
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00