All conference submissions

To develop a robust, institution-independent quality assurance model using heterogeneous datasets. By prioritizing generalizability over site-specific tuning, this model aims to predict and assist in the delineation of PTV contou...

To achieve accurate dosimetric modeling of Alpha DaRT sources by accounting for the spatial superposition of dose contributions from multiple implanted sources arranged in a regular lattice geometry.

Photon-counting CT (PCCT) denoising seeks to approximate high-dose image quality from lower-dose acquisitions. A key challenge for patient-specific denoising with precise control of denoising strength is the lack of an available...

Conventional sphere-packing techniques for Gamma Knife treatment plan optimization often produce less conformal dose distributions for non-spherical targets and are inefficient for dose delivery. This work investigates a dose-pai...

To compare the differences among various treatment techniques in the treatment of orbital lymphoma, this study performed a dosimetric comparison among Intensity-Modulated Proton Therapy (IMPT), CyberKnife (CK), and non-coplanar V...

In the microdosimetric kinetic model (MKM), the quadratic coefficient β is commonly assumed to be independent of linear energy transfer (LET). However, experimental data suggest that β decreases at very high LET, likely because t...

To develop an automated CT quality control (QC) query system that retrieves, analyzes, and trends QC data and enables image artifact review across iPhone, iPad, and Computer platforms for 71 GE and Siemens CT scanners spanning nu...

Increasing international collaboration in radiation oncology highlights the need for standardized nomenclature that is consistent across languages. The AAPM Task Group TG‑263U1 established French and Spanish language sub‑groups i...

To characterize the angular dependence of the Elekta Gamma Knife Esprit High Definition Motion Management (HDMM) system and examine the feasibility of non-standard camera angles for the treatment of larger patients.

Deep learning–based three‑dimensional (3D) dose prediction models are increasingly becoming viable for radiotherapy workflows. However, their sensitivity to small variations in input data remains insufficiently characterized. Thi...

To propose a federated learning (FL) framework incorporating a novel deep ensemble strategy for multi-institutional brain metastasis (BM) segmentation, improving performance in limited local datasets while preserving privacy by a...

Evidence from randomized trials demonstrates improved memory, cognition, and quality of life in patients whose hippocampi are spared during radiotherapy (RT) to the brain. We present a RapidPlan (RP) model for high-grade glioma R...

To implement a correction methodology for amorphous silicon Electronic Portal Imaging Device (EPID) dosimetry that resolves systemic discrepancies due to beam hardening, aperture-specific response, and tongue-and-groove (TG) effe...

Spatially fractionated radiation therapy (SFRT) aims to deliver high-dose peaks within tumors while maintaining low-dose valleys. However, commonly used peak-to-valley ratios or D5/D95 and D10/D90 metrics derived from gross tumor...

To develop a slice-specific CT organ dose library using Monte Carlo radiation transport simulations on a set of newborn, infant, and toddler (NIT) computational phantoms containing newly developed age-specific skeletal tissue mod...

Respiratory during lung cancer radiotherapy causes tumor and organ motion, increasing uncertainties of absorbed doses, while current image-guided methods cannot provide real-time volumetric CT during treatment. We proposed a gene...

Current registration tools lack mechanisms for specifying clinical priorities. We developed a system accepting plain-text instructions (e.g., "prioritize tumor alignment for dose accumulation") and evaluated whether text guidance...

In current prostate permanent implant (PPI) low-dose-rate (LDR) brachytherapy planning, algorithm-generated treatment plans are frequently sub-optimal, requiring time-consuming and user-dependent manual adjustments. This work aim...

To evaluate the clinical agreement between surface-guided radiotherapy (SGRT) and cone-beam CT (CBCT) for daily setup verification in pelvic radiotherapy patients.

To develop and validate a novel hybrid framework for five-material decomposition (water, fat, bone, iodine, and lung) using three-energy Photon-Counting CT (PCCT). By integrating multi-energy spectral analysis with density-constr...

Dense lung vasculature landmarking is vital for assessing thoracic registration accuracy in treatment planning. We demonstrate an automated method for identifying vascular bifurcations in free-breathing CT images.

Accurate clinical target volume (CTV) delineation is essential for radiotherapy in esophageal cancer but remains highly subjective and variable due to its reliance on physician experience. Most automated approaches focus on gross...

Proton transmission fields, treating through the target rather than stopping spots in the target, have a substantial but largely unrealized clinical potential, offering inherently robust delivery with minimal range uncertainty an...

This study presents a hybrid framework combining Vision Transformer (ViT) and handcrafted radiomic features for oropharyngeal carcinoma (OPC), to enhance multi-endpoint survival prediction.