11 papers
Patient-specific AI for generation of 3D dosimetry imaging from two 2D-planar measurements
Alejandro Lopez-Montes, Robert Seifert, Astrid Delker +6
In this work we explored the use of patient specific reinforced learning to generate 3D activity maps from two 2D planar images (anterior and posterior). The solution of this probl…
Semi-Supervised Learning for Dose Prediction in Targeted Radionuclide: A Synthetic Data Study
Jing Zhang, Alexandre Bousse, Chi-Hieu Pham +2
Targeted Radionuclide Therapy (TRT) is a modern strategy in radiation oncology that aims to administer a potent radiation dose specifically to cancer cells using cancer-targeting r…
Positronium Imaging: History, Current Status, and Future Perspectives
PaweÅ Moskal, Aleksander Bilewicz, Manish Das +11
Positronium imaging was recently proposed to image the properties of positronium atoms in the patient body. Positronium properties depend on the size of intramolecular voids and ox…
First Positronium Lifetime Imaging with Scandium-44 on a Long Axial Field-of-view PET/CT
Lorenzo Mercolli, William M. Steinberger, Pascal V. Grundler +12
Purpose: 44Sc has been successfully produced, synthesized, labeled and first-in-human studies were conducted some years ago. The decay properties of 44Sc, together with being close…
Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data
Huidong Xie, Weijie Gan, Reimund Bayerlein +24
Reducing scan times, radiation dose, and enhancing image quality for lower-performance scanners, are critical in low-dose PET imaging. Deep learning techniques have been investigat…
Fed-NDIF: A Noise-Embedded Federated Diffusion Model For Low-Count Whole-Body PET Denoising
Yinchi Zhou, Huidong Xie, Menghua Xia +12
Low-count positron emission tomography (LCPET) imaging can reduce patients' exposure to radiation but often suffers from increased image noise and reduced lesion detectability, nec…