Multi-center Dose Prediction Using Attention-aware Deep learning Algorithm Based on Transformers for Cervical Cancer Radiotherapy.

Journal: Clinical oncology (Royal College of Radiologists (Great Britain))

PMID: 38631974

Abstract

AIMS: Accurate dose delivery is crucial for cervical cancer volumetric modulated arc therapy (VMAT). We aimed to develop a robust deep-learning (DL) algorithm for fast and accurate dose prediction of cervical cancer VMAT in multicenter datasets and then explore the feasibility of the DL algorithm to endometrial cancer VMAT with different prescriptions.

Authors

Z Wu

School of Data and Computer Science (Z.W.), Sun Yat-sen University, Guangzhou, China.
X Jia
L Lu

Department of Radiotherapy, Tongling People's Hospital, Anhui, PR China.
C Xu

Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA.
Y Pang

Department of Radiotherapy, Zigong First People's Hospital, Sichuan, PR China.
S Peng

Department of Radiotherapy, Zigong First People's Hospital, Sichuan, PR China.
M Liu

School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, 150090, China.
Y Wu

School of Biomedical Informatics, The University of Texas Health Science Center at Houston , Houston, Texas, USA.

Keywords

Adult Aged Algorithms Deep Learning Endometrial Neoplasms Female Humans Middle Aged Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Uterine Cervical Neoplasms

External Resources

View on PubMed Access via DOI PubMed (38631974)

Multi-center Dose Prediction Using Attention-aware Deep learning Algorithm Based on Transformers for Cervical Cancer Radiotherapy.

Abstract

Authors

Keywords

External Resources

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