All conference submissions

Professional

Professional

This study aims to demonstrate the feasibility of a multifocal radioluminescence microscopy (RLM) framework to localize alpha-emitting radionuclide positions at the subcellular level.

While deep learning autosegmentation models are widely integrated into clinical workflows in radiation oncology, a critical gap has emerged: the "static deployment" trap. Once deployed, model performance can deteriorate due to re...

Diagnostic and Interventional Radiology Physics

TH- Brachytherapy

Therapy Physics

Diagnostic and Interventional Radiology Physics

Radiopharmaceuticals, Theranostics, and Nuclear Medicine

Professional

Low-count PET acquisition and inter-radiotracer translation offer effective strategies to reduce radiation dose and mitigate tracer availability constraints. Recent self-supervised learning (SSL) foundation models (e.g., DINOv3)...

To evaluate a Large Language Model (LLM) for automated Volumetric Modulated Arc Therapy (VMAT) planning in cervical cancer, covering both single-target and complex Simultaneous Integrated Boost (SIB) scenarios.

Bone marrow (BM) is an organ-at-risk for 177Lu-PSMA radiopharmaceutical therapy, but estimating the absorbed dose (AD) is challenged by the segmentation of disseminated BM. In this work, we evaluated the impact of two segmentatio...

Diagnostic and Interventional Radiology Physics

Therapy Physics

Therapy Physics

Radiopharmaceuticals, Theranostics, and Nuclear Medicine

Diagnostic and Interventional Radiology Physics

Failure Mode and Effects Analysis (FMEA) is the standard for proactive risk management in radiation therapy under AAPM TG-100 guidelines, yet traditional implementation can exceed 100 hours per process and shows significant inter...

Professional

Artificial intelligence-based denoising has shown much promise in improving signal-to-noise in medical imaging. Our goal was to optimize Y-90 bremsstrahlung SPECT imaging following transarterial radioembolization (TARE) using a d...

To apply a multiparametric model selection strategy within a tensor radiomics paradigm, whereby different flavours of radiomics features are generated from multiple PET-CT image fusion strategies, to identify reliable and general...

Diagnostic and Interventional Radiology Physics

Knowledge-based planning (KBP) improves plan quality and efficiency. However, training institution-specific models requires substantial clinical data and expertise, and publicly available models may not align with local clinical...