University of North Carolina at Chapel Hill

To investigate the difference in gamma passing rate and dose profile of measurement of patient specific quality assurance (PSQA) of SBRT plans using the SNC ArcCHECK in single measurement and high-density diode merge measurement.

To investigate treatment plan quality of head and neck cancers via tumor control and normal tissue complications probability (TCP and NTCP) objectives in the plan optimization process.

To integrate qualitative assessments from experienced treatment planners with quantitative geometric comparisons to evaluate the clinical utility of a deep learning (DL)-based auto-segmentation tool and establish performance criteria grounded in clinical usab...

Halide perovskites, particularly CsPbBr3, present an exciting opportunity to overcome these limitations due to their high atomic number, fast charge transport, and exceptional radiation tolerance. While perovskite detectors have shown promise for low-energy x...

To determine which cardiac substructures are associated with radiation-induced cardiac symptoms following radiotherapy for stage III non-small cell lung cancer (NSCLC), and to estimate the corresponding dose–response relationships using a widely applied norma...

Training nnU-Net models for medical image segmentation with large patient samples is computationally expensive, limiting iteration speed in research and clinical translation. We present an optimized training workflow that significantly accelerates nnU-Net tra...

For craniospinal irradiation (CSI), VMAT offers superior dose conformality and normal tissue sparing compared to traditional 3D techniques. However, generating these plans is cumbersome. It requires multiple isocenters, optimization of a large number of organ...

Accurate multi-organ auto-segmentation is essential for efficient clinical workflows. Although nnU-Net-based models like TotalSegmentator achieve strong baseline performance, residual errors can lead to boundary outliers that require time-consuming manual cor...