Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning
Phys Med Biol. 2024 Mar 27. doi: 10.1088/1361-6560/ad3880. Online ahead of print.ABSTRACTPredicting the probability of having the plan approved by the physician is important for automatic treatment planning. Driven by the mathematical foundation of deep learning that can use a deep neural network to represent functions accurately and flexibly, we developed a deep-learning framework that learns the probability of plan approval for cervical cancer high-dose-rate brachytherapy (HDRBT).
Approach: The system consisted of a dose prediction network (DPN) and a plan-approval probability network (PPN). DPN predicts OAR D2cc...
Source: Physics in Medicine and Biology - March 27, 2024 Category: Physics Authors: Yin Gao Yesenia Gonzalez Chika Nwachukwu Kevin Albuquerque Xun Jia Source Type: research
B-ultrasound or CT-guided 3D-printing individualized non-coplanar template brachytherapy for the treatment of locally uncontrolled recurrent head and neck squamous cell carcinoma
CONCLUSIONS: Safe and effective interpolation is used to guide the 3D printing of a single non-coplanar template with B-ultrasound or CT in the radiotherapy of local and uncontrolled recurrent head and neck squamous cell carcinoma. According to the guidance of B-ultrasound or CT, the 3D printing individualized non-coplanar template has an obvious healing effect especially in the brachytherapy, and can also protect the functional organs well, with less side effects and fewer complications. Therefore, this method is the most effective for the treatment of locally uncontrolled recurrent head and neck squamous cell carcinoma.P...
Source: Advances in Dermatology and Allergology - March 27, 2024 Category: Dermatology Authors: Pengbing Han Fengju Li Yanping Zhang Liying Gao Guiqiong Zhang Qing Guo Yuxia Zhu Qun Su Source Type: research
Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning
Phys Med Biol. 2024 Mar 27. doi: 10.1088/1361-6560/ad3880. Online ahead of print.ABSTRACTPredicting the probability of having the plan approved by the physician is important for automatic treatment planning. Driven by the mathematical foundation of deep learning that can use a deep neural network to represent functions accurately and flexibly, we developed a deep-learning framework that learns the probability of plan approval for cervical cancer high-dose-rate brachytherapy (HDRBT).
Approach: The system consisted of a dose prediction network (DPN) and a plan-approval probability network (PPN). DPN predicts OAR D2cc...
Source: Physics in Medicine and Biology - March 27, 2024 Category: Physics Authors: Yin Gao Yesenia Gonzalez Chika Nwachukwu Kevin Albuquerque Xun Jia Source Type: research
B-ultrasound or CT-guided 3D-printing individualized non-coplanar template brachytherapy for the treatment of locally uncontrolled recurrent head and neck squamous cell carcinoma
CONCLUSIONS: Safe and effective interpolation is used to guide the 3D printing of a single non-coplanar template with B-ultrasound or CT in the radiotherapy of local and uncontrolled recurrent head and neck squamous cell carcinoma. According to the guidance of B-ultrasound or CT, the 3D printing individualized non-coplanar template has an obvious healing effect especially in the brachytherapy, and can also protect the functional organs well, with less side effects and fewer complications. Therefore, this method is the most effective for the treatment of locally uncontrolled recurrent head and neck squamous cell carcinoma.P...
Source: Advances in Dermatology and Allergology - March 27, 2024 Category: Dermatology Authors: Pengbing Han Fengju Li Yanping Zhang Liying Gao Guiqiong Zhang Qing Guo Yuxia Zhu Qun Su Source Type: research
