Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

MLA

Holzschuh, Julius C., et al. “Deep Learning Based Automated Delineation of the Intraprostatic Gross Tumour Volume in PSMA-PET for Patients with Primary Prostate Cancer.” Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology, vol. 188, Nov. 2023, p. 109774. EBSCOhost, https://doi.org/10.1016/j.radonc.2023.109774.

APA

Holzschuh, J. C., Mix, M., Ruf, J., Hölscher, T., Kotzerke, J., Vrachimis, A., Doolan, P., Ilhan, H., Marinescu, I. M., Spohn, S. K. B., Fechter, T., Kuhn, D., Bronsert, P., Gratzke, C., Grosu, R., Kamran, S. C., Heidari, P., Ng, T. S. C., Könik, A., … Zamboglou, C. (2023). Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer. Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology, 188, 109774. https://doi.org/10.1016/j.radonc.2023.109774

Chicago

Holzschuh, Julius C, Michael Mix, Juri Ruf, Tobias Hölscher, Jörg Kotzerke, Alexis Vrachimis, Paul Doolan, et al. 2023. “Deep Learning Based Automated Delineation of the Intraprostatic Gross Tumour Volume in PSMA-PET for Patients with Primary Prostate Cancer.” Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology 188 (November): 109774. doi:10.1016/j.radonc.2023.109774.