Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

Journal: Journal of applied clinical medical physics

PMID: 39186746

Abstract

PURPOSE: To develop a non-coplanar cone-beam computed tomography (CBCT) image reconstruction method using projections within a limited angle range for non-coplanar radiotherapy.

Authors

Ran Wei
Zhiyue Song

Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ziqi Pan

College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
Ying Cao
Yongli Song

Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jianrong Dai

National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Keywords

Algorithms Brain Neoplasms Cone-Beam Computed Tomography Humans Image Processing, Computer-Assisted Neural Networks, Computer Organs at Risk Phantoms, Imaging Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Image-Guided Radiotherapy, Intensity-Modulated

External Resources

View on PubMed Access via DOI PubMed (39186746)

Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

Abstract

Authors

Keywords

External Resources

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