activity
20242026
collaborators

7 papers

physics.med-ph2026

Novel Asymmetrical High-Resolution and High-Sensitivity Brain Dedicated PET system: Design optimization and performance evaluation

Yuemeng Feng, Lisa Blackberg, Arkadiusz Sitek +1

Objective. This study investigates the best achievable performance of a brain-dedicated PET system with high resolution and sensitivity by evaluating different detector configurati…

physics.med-ph2026

Maximum-Likelihood--Based Position Decoding of Laser Processed Converging Pixel CsI: Tl Detectors for High-Resolution SPECT

Xi Zhang, Arkadiusz Sitek, Lisa Blackberg +3

This study demonstrates the feasibility of a novel fabrication technique for high spatial resolution CsI: Tl scintillation detectors tailored for single photon emission computed to…

physics.med-ph2025

Towards Integrated Clinical-Computational Nuclear Medicine

Faraz Farhadi, Shadi A. Esfahani, Fereshteh Yousefirizi +7

The field of Clinical-Computational Nuclear Medicine is rapidly advancing, fueled by AI, tracer kinetic modeling, radiomics, and integrated informatics. These technologies improve…

physics.med-ph2025

Collimator-less SPECT System Design for Dynamic Whole-body Imaging

Yuemeng Feng, Arkadiusz Sitek, Shadi Abdar Esfahani +1

In this study, we introduce a Compton SPECT system for whole-body imaging of Actinium-225 (225Ac), one of the trending radionuclides for targeted alpha therapy (TAT). The Compton S…

eess.IV2025

A novel perspective on denoising using quantum localization with application to medical imaging

Amirreza Hashemi, Sayantan Dutta, Bertrand Georgeot +2

Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodol…

eess.IV2025

Application of Spherical Convolutional Neural Networks to Image Reconstruction and Denoising in Nuclear Medicine

Amirreza Hashemi, Yuemeng Feng, Arman Rahmim +1

This work investigates use of equivariant neural networks as efficient and high-performance frameworks for image reconstruction and denoising in nuclear medicine. Our work aims to…