Your browser doesn't support javascript.
loading
Rapid unpaired CBCT-based synthetic CT for CBCT-guided adaptive radiotherapy.
Wynne, Jacob F; Lei, Yang; Pan, Shaoyan; Wang, Tonghe; Pasha, Mosa; Luca, Kirk; Roper, Justin; Patel, Pretesh; Patel, Sagar A; Godette, Karen; Jani, Ashesh B; Yang, Xiaofeng.
Affiliation
  • Wynne JF; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Lei Y; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Pan S; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Wang T; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
  • Pasha M; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Luca K; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Roper J; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Patel P; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Patel SA; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Godette K; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Jani AB; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
  • Yang X; Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.
J Appl Clin Med Phys ; 24(10): e14064, 2023 Oct.
Article in En | MEDLINE | ID: mdl-37345557
ABSTRACT
In this work, we demonstrate a method for rapid synthesis of high-quality CT images from unpaired, low-quality CBCT images, permitting CBCT-based adaptive radiotherapy. We adapt contrastive unpaired translation (CUT) to be used with medical images and evaluate the results on an institutional pelvic CT dataset. We compare the method against cycleGAN using mean absolute error, structural similarity index, root mean squared error, and Frèchet Inception Distance and show that CUT significantly outperforms cycleGAN while requiring less time and fewer resources. The investigated method improves the feasibility of online adaptive radiotherapy over the present state-of-the-art.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spiral Cone-Beam Computed Tomography Limits: Humans Language: En Journal: J Appl Clin Med Phys Journal subject: BIOFISICA Year: 2023 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spiral Cone-Beam Computed Tomography Limits: Humans Language: En Journal: J Appl Clin Med Phys Journal subject: BIOFISICA Year: 2023 Document type: Article Affiliation country: United States