You Zhang, PhD

T1-weighted (T1w) and T2-weighted (T2w) FLAIR MRI provide complementary image contrast for delineating gross tumor volume (GTV) and clinical target volume (CTV) in brain tumor radiotherapy (RT) planning during both MRI simulation (MR-Sim) and MRI-guided RT (M...

Implicit neural representations (INRs) enable continuous, resolution-agnostic modeling of complex anatomical motion and have shown remarkable promise for deformation-driven, instance-specific real-time volumetric MRI estimation from a prior MRI. However, trai...

To clinically validate an implicit neural representation (INR)-based fitting approach for intravoxel incoherent motion (IVIM) diffusion MRI parameter estimation against conventional non-linear least squares (NLLS), and to evaluate a robustness metric (R-index...

Diffusion-weighted MRI (DWI) and its derived parameters, including apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) metrics, are valuable for assessing tumor response to radiotherapy. However, DWI processing workflows are complex,...

Proton arc therapy (PAT) holds promise for enhancing plan conformity while minimizing dose sparing. However, PAT faces practical barriers related to delivery inefficiency, and its effectiveness can be compromised by beam range and radiobiological uncertaintie...

Dynamic myocardial perfusion CT (MPCT) serves as a critical tool for functional assessment of multiple diseases, including coronary stenosis and myocardial ischemia. However, the continuous acquisition required to track contrast kinetics incurs substantial ra...

The HyperSight 6-second rapid scan has been used clinically for internal-target-volume(ITV) definition. However, limited temporal sampling may lead to ITV underestimation, particularly for irregular motion. Using a joint dynamic reconstruction and motion-esti...

Timely dose verification is essential for quality assurance (QA) in modern radiotherapy (RT), particularly in online adaptive RT, where measurement-based QA is often impractical. Current approaches are limited by machine/energy-specific designs, hindering sca...

Time-resolved volumetric MRI reconstructed from minimal k-space samples is critical for motion-adaptive radiotherapy to capture real-time deformable motion. We propose a Gaussian representation-based one-shot learning framework that models patient anatomy and...

Standard Cone-Beam CT (CBCT) enables cost-effective Dual-Energy CT (DECT) via a one-kVp-switching protocol(switching energy once in the middle of a full scan), but inherently suffers from geometry-inconsistent data acquisition and unknown spectral characteris...

Accurate lesion segmentation is fundamental to medical image analysis, yet most methods are tailored to specific anatomical sites or modalities, limiting their generalizability in diverse clinical settings. While recent vision-language foundation models enabl...

Accurate evaluation of multi-modality deformable image registration remains a critical challenge in radiotherapy. Traditional metrics such as Normalized Mutual Information (NMI), Mean Absolute Error (MAE), and Normalized Cross-Correlation (NCC) are based on i...

Therapy Physics

Existing adaptive radiotherapy (ART) only accounts for inter-fraction variations in anatomy. Adapted plans can become suboptimal immediately due to anatomical changes during online planning and treatment delivery, degrading treatment quality and efficacy. To...

Treatment planning for MR-guided adaptive radiotherapy (MRgART) requires extensive time and effort in both preplanning and online adaptation processes. It is a major bottleneck hindering the efficiency and quality of MRgART. Specifically, extended preplanning...

Existing volumetric MRI techniques are constrained by the trade-off between acquisition time and image quality, limiting accuracy in motion-impacted sites such as the liver. To enable fast and high-quality volumetric imaging with sufficient spatiotemporal res...

Positron emission tomography (PET) is essential for image-guided radiotherapy by enabling accurate tumor localization and delineation. For sites affected by respiration, time-resolved PET is needed to resolve motion but challenged by very low counts per timef...

Real-time liver motion tracking is essential in image-guided radiotherapy to enable precise tumor targeting. We developed a conditional latent point cloud diffusion model (Latent-Liver) for real-time deformable liver motion tracking and tumor localization usi...

Accurate tumor segmentation is essential for adaptive radiation therapy (ART) but remains time-consuming, labor-intensive, and subject to considerable inter-user variations. Recent advances in foundation models, such as Segment Anything Model 2 (SAM2), show s...