使PET

Hao Sun1, Amirhossein Sanaat2, Wenxiang Yi3

  • 1School of Biomedical Engineering, Southern Medical University, 1023 Shatai Road, Guangzhou 510515, China (H.S., W.Y., L.L.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH‑1211 Geneva, Switzerland (H.S., A.S., Y.S., C.E.D., C.I., H.Z.); Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 1023 Shatai Road, Guangzhou 510515, China (H.S., W.Y., L.L.); Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, 1023 Shatai Road, Guangzhou 510515, China (H.S., W.Y., L.L.).

Academic radiology
|August 30, 2025
PubMed
概括

深度学习模型提高了超快扫描中的正电子发射断层扫描 (PET) 图像质量. 这项技术改善了多标志物全身PET成像中的病变检测和图像质量.