APA (7th ed.) Citation

Huang, B., Yang, Q., Li, X., Wu, Y., Liu, Z., Pan, Z., . . . Zuo, C. (2024). Deep learning–based whole-body characterization of prostate cancer lesions on [68Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence. European Journal of Nuclear Medicine & Molecular Imaging, 51(4), 1173. https://doi.org/10.1007/s00259-023-06551-3

Chicago Style (17th ed.) Citation

Huang, Bingsheng, Qinqin Yang, Xiao Li, Yuxuan Wu, Zhantao Liu, Zhaohong Pan, Shaonan Zhong, Shaoli Song, and Changjing Zuo. "Deep Learning–based Whole-body Characterization of Prostate Cancer Lesions on [68Ga]Ga-PSMA-11 PET/CT in Patients with Post-prostatectomy Recurrence." European Journal of Nuclear Medicine & Molecular Imaging 51, no. 4 (2024): 1173. https://doi.org/10.1007/s00259-023-06551-3.

MLA (9th ed.) Citation

Huang, Bingsheng, et al. "Deep Learning–based Whole-body Characterization of Prostate Cancer Lesions on [68Ga]Ga-PSMA-11 PET/CT in Patients with Post-prostatectomy Recurrence." European Journal of Nuclear Medicine & Molecular Imaging, vol. 51, no. 4, 2024, p. 1173, https://doi.org/10.1007/s00259-023-06551-3.