Select Publications

Efficiency Through Automation and Artificial Intelligence

  1. Ni R, Chuk E, Han K, .. Haibe-Kains B, Rink A. Geometrically focused training and evaluation of organs-at risk segmentation via deep learning. Med Phys 2025 Jul;52(7):e17840. doi: 10.1002/mp.17840

  2. Song WY, Roumeliotis M, Lee J, et al. Roadmap: medical physics technologies in brachytherapy. Phys Med Biol 2025 Jul 16;70(14). doi: 10.1088/1361-6560/ade21f

  3. Ni R, Han K, Haibe-Kains B, Rink A. Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy. Radiother Oncol 2024 Aug:197:110332. doi: 10.1016/j.radonc.2024.110332

  4. Zhao JZL, Ni R, Chow R, Rink A, Weersink R, Croke J, Srinivas R. Artificial Intelligence applications in brachytherapy: A literature review. Brachytherapy 023 Jul-Aug;22(4):429-445. doi: 10.1016/j.brachy.2023.04.003

Efficacy in Brachytherapy

  1. Maina J, Liu ZA, Milosevic M, et al. MRI-guided Brachytherapy for vaginal recurrence of endometrial cancer. Brachytherapy. 2025 Nov 21:S1538-4721(25)00347-2. doi: 10.1016/j.brachy.2025.10.007

  2. Chuk E Conway J, Hanuschak J, et al. Patient-reported sexual health outcomes of cervical cancer patients treated with definitive chemoradiation and MRI-guided brachytherapy. Gynecol Oncol 2024 Nov:190:153-159. doi: 10.1016/j.ygyno.2024.08.022

  3. Scott AA, Weersink M, Liu ZA, et al. Comparing dosimetry of locally advanced cervical cancer patients treated with 3 versus 4 fractions of MRI-guided brachytherapy. Brachytherapy 2023 Mar-Apr;22(2):146-156. doi: 10.1016/j.brachy.2022.11.005