The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/7b046294-04cf-457f-b143-fde38df7eac0

Cosmi, Valerio; Ghosh, Satyajit; Ramakers, Ruud; Goorden, Marlies C.; Beekman, Freek (2025): Data underlying the publication: "Super-Cluster collimation for ultra-sensitive SPECT-PET: a simulation study". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/7b046294-04cf-457f-b143-fde38df7eac0.v1

Categories

• Artificial Intelligence and Image Processing
• Other Medical and Health Sciences
• Atomic, Molecular, Nuclear, Particle and Plasma Physics
• Physical Sciences
• Information and Computing Sciences
• Medical and Health Sciences

Keywords

collimator high-energy high-sensitivity Monte Carlo simulations PET preclinical SPECT

Licence

CC0

Interoperability

• RO-Crate Metadata

Export as...

RefWorks BibTeX Reference Manager Endnote DataCite NLM DC CFF

by Valerio Cosmi , Satyajit Ghosh , Ruud Ramakers, Marlies C. Goorden , Freek Beekman

This work focused on developing a novel collimator design aimed at achieving high-resolution imaging for preclinical SPECT. The design is particularly relevant for sensitivity-critical applications, as it seeks to maximize system sensitivity while maintaining image quality. The study was conducted through simulations, in which the proposed design was introduced and evaluated. Data generated using simulation software were used to assess the collimator’s performance and reconstruct images of specifically designed phantoms. The data collected include simulation software macros, collimator design scripts, performance analysis scripts and images. All datasets, scripts, and software used in the paper “Super-Cluster Collimation for Ultra-Sensitive SPECT/PET: A Simulation Study” are archived. A user manual detailing how to operate the software tools employed in this work is also included.

History

• 2025-10-16 first online, published, posted

Publisher

4TU.ResearchData

Format

Images in jpeg, jpg or png. Softwares format in .m (Matlab), .py (python), .c (c++). Simulation macros format in .mac (GATE simulation software).

Funding

• QUARAT: Quantitative Universal Radiotracer Tomography (grant code TTW16885) Dutch Research Council (NWO)

Organizations

TU Delft, Faculty of Applied Sciences, Department of Radiation Science and Technology, Biomedical Imaging