Author profile
Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine
While optically stimulated luminescence dosimeters (OSLD) offer advantages in reusability and efficiency, they overestimate the surface dose due to thick effective point of measurement. The aim of this study is to investigate the detector-specific correction...
Cone-beam CT (CBCT) acquired on the linear accelerator is being increasingly used beyond image guidance to support simulation and treatment planning workflows. This work reports the clinical implementation, challenges, and solutions associated with CBCT-based...
This study aims to develop a deep learning (DL) model capable of predicting Monte Carlo (MC)-level carbon-ion dose distributions from Pencil Beam Algorithm (PBA) calculations. The objective is to achieve the high accuracy of MC simulations while maintaining t...
Magnetic resonance (MR)–only radiotherapy planning requires accurate synthetic CT (sCT) generation from images acquired using standard clinical MRI simulation protocols. However, MRI acquisition protocols vary substantially across anatomical sites, and many e...
To mitigate the loss of spatial information inherent to DVH-based and coarse categorical descriptors used for breast cancer–related lymphedema prediction, we present a multi-modal cross-attention predictive model with self-attention refinement using patient-s...
In carbon ion radiotherapy (CIRT), treatment-day position verification is typically performed using two-dimensional (2D) X-ray images acquired at non-orthogonal angles. While effective for bone-based alignment, this approach provides limited three-dimensional...
While Denoising Diffusion Probabilistic Models (DDPMs) have set new benchmarks for synthetic CT (sCT) image quality, their prohibitive inference times hinder integration into online adaptive radiation therapy (ART) workflows. This study introduces HQ-PatchNet...