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Medical Physics
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October 20, 2023
Single patient learning for adaptive radiotherapy dose prediction
Austen Maniscalco, Xiao Liang, Mu-Han Lin, et al.
Medical Physics
|
July 17, 2023
Intentional deep overfit learning for patient-specific dose predictions in adaptive radiotherapy
Austen Maniscalco, Xiao Liang, Mu-Han Lin, et al.
Machine Learning: Science and Technology
|
October 14, 2024
Quality assurance for online adaptive radiotherapy: a secondary dose verification model with geometry-encoded U-Net
Shunyu Yan, Austen Maniscalco, Biling Wang, et al.
Medical Physics
|
December 31, 2025
MedicalDataHandler, a research-oriented graphical user interface for DICOM data management
Austen Maniscalco, Yang Kyun Park, Andrew Godley, et al.
Machine Learning. Health
|
January 1, 2026
Geometry-encoded deep learning (GeoDL) framework for real-time 3D dose verification for online adaptive radiotherapy
Shunyu Yan, Austen Maniscalco, Biling Wang, et al.
Machine Learning. Health
|
September 8, 2025
Adaptive radiotherapy dose prediction on head and neck cancer patients with a 3D multi-headed U-Net deep learning architecture
Hui-Ju Wang, Austen Maniscalco, David Sher, et al.
Journal of Applied Clinical Medical Physics
|
March 15, 2025
Enhanced dose prediction for head and neck cancer artificial intelligence-driven radiotherapy based on transfer learning with limited training data
Hui-Ju Wang, Austen Maniscalco, David Sher, et al.
Journal of Applied Clinical Medical Physics
|
March 20, 2025
Closing the gap in plan quality: Leveraging deep-learning dose prediction for adaptive radiotherapy
Sean J Domal, Austen Maniscalco, Justin Visak, et al.
Medical Physics
|
May 6, 2024
Multimodal radiotherapy dose prediction using a multi-task deep learning model
Austen Maniscalco, Ezek Mathew, David Parsons, et al.
Journal of Applied Clinical Medical Physics
|
December 3, 2024
Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy
Justin Visak, Chien-Yi Liao, Xinran Zhong, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
Medical Physics
|
October 20, 2023
Single patient learning for adaptive radiotherapy dose prediction
Austen Maniscalco, Xiao Liang, Mu-Han Lin, et al.
Medical Physics
|
July 17, 2023
Intentional deep overfit learning for patient-specific dose predictions in adaptive radiotherapy
Austen Maniscalco, Xiao Liang, Mu-Han Lin, et al.
Machine Learning: Science and Technology
|
October 14, 2024
Quality assurance for online adaptive radiotherapy: a secondary dose verification model with geometry-encoded U-Net
Shunyu Yan, Austen Maniscalco, Biling Wang, et al.
Medical Physics
|
December 31, 2025
MedicalDataHandler, a research-oriented graphical user interface for DICOM data management
Austen Maniscalco, Yang Kyun Park, Andrew Godley, et al.
Machine Learning. Health
|
January 1, 2026
Geometry-encoded deep learning (GeoDL) framework for real-time 3D dose verification for online adaptive radiotherapy
Shunyu Yan, Austen Maniscalco, Biling Wang, et al.
Machine Learning. Health
|
September 8, 2025
Adaptive radiotherapy dose prediction on head and neck cancer patients with a 3D multi-headed U-Net deep learning architecture
Hui-Ju Wang, Austen Maniscalco, David Sher, et al.
Journal of Applied Clinical Medical Physics
|
March 15, 2025
Enhanced dose prediction for head and neck cancer artificial intelligence-driven radiotherapy based on transfer learning with limited training data
Hui-Ju Wang, Austen Maniscalco, David Sher, et al.
Journal of Applied Clinical Medical Physics
|
March 20, 2025
Closing the gap in plan quality: Leveraging deep-learning dose prediction for adaptive radiotherapy
Sean J Domal, Austen Maniscalco, Justin Visak, et al.
Medical Physics
|
May 6, 2024
Multimodal radiotherapy dose prediction using a multi-task deep learning model
Austen Maniscalco, Ezek Mathew, David Parsons, et al.
Journal of Applied Clinical Medical Physics
|
December 3, 2024
Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy
Justin Visak, Chien-Yi Liao, Xinran Zhong, et al.
Page
of 1