Deep learning network enhances imaging quality of low-b-value diffusion–weighted imaging and improves lesion detection in prostate cancer
DLR<sub>1500</sub> DWIs were comparable in quality to original 1500 b-value images within both junior and senior radiology doctors. NAFNet based DWI enhancement can significantly improve the image quality of 800 b-value DWI, and therefore promote the accuracy of prostate cancer lesion detection for junior radiology doctors.
Authors
- Fangning Wan (ORCID: https://orcid.org/0000-0001-5258-1626)
- Bo Dai (ORCID: https://orcid.org/0000-0003-1383-3864)
- Dingwei Ye (ORCID: https://orcid.org/0000-0002-6761-5195)
- Zheng Liu (ORCID: https://orcid.org/0000-0002-4168-6702)
- Weijie Gu
- Xiaohang Liu (ORCID: https://orcid.org/0000-0002-7661-2949)
- Yunyi Kong (ORCID: https://orcid.org/0000-0002-4218-7921)
- Zhang-zhe Chen
Institutions
- Shanghai Medical College of Fudan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- Shanghai Cancer Institute (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-05-27
- DOI
- https://doi.org/10.1186/s12885-025-14354-y
- Citations
- 4
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 6.07
Funders
- Shanghai Anti-Cancer Association
- Shanghai Municipal Health Commission
- National Natural Science Foundation of China
- Fudan University