Papers
1
Total Citations
8
H-Index
1
About
Wenlong Xia is a researcher specializing in medical physics and radiation therapy optimization, with a particular focus on robotic radiotherapy systems and advanced computational methods for treatment planning. His work sits at the intersection of machine learning frameworks and clinical radiotherapy, applying modern deep learning tools — most notably the PyTorch toolkit — to solve complex optimization challenges in radiation oncology. His most recognized contribution investigates the application of PyTorch to plan optimization for circular cone-based robotic linear accelerators (linacs), addressing a critical clinical bottleneck: the prolonged optimization and treatment delivery times that arise from the non-coplanar treatment space inherent to robotic systems. By leveraging GPU-accelerated computation and automatic differentiation capabilities within PyTorch, Xia's approach aims to streamline hypo-fractionated radiotherapy planning, a rapidly growing treatment modality known for its efficiency and clinical efficacy. With 8 citations accrued since 2022, his work is gaining traction within the medical physics community, reflecting growing interest in integrating modern software engineering tools into clinical treatment planning workflows. His research represents a meaningful step toward making sophisticated robotic radiotherapy more computationally efficient and clinically accessible.
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Top Papers
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