AIRPET: Virtual Positron Emission Tomography

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Authors: J. Renner, J. J. Gómez-Cadenas, R. Soleti
Cited by: 0

Abstract

Positron Emission Tomography (PET) is a powerful medical imaging technique, but the design and evaluation of new PET scanner technologies present significant challenges. The process is typically divided into three major stages: 1. detector design and simulation, 2. image reconstruction, and 3. image interpretation. Each of these stages requires significant expertise, making it difficult for individuals or small teams to manage all three at once. AIRPET (AI-driven Revolution in Positron Emission Tomography) is a web-based platform designed to address this challenge by integrating all phases of PET design into a single, accessible, and AI-assisted workflow. AIRPET provides an interface to large language models (LLMs) for assisted geometry creation and an interface for basic PET image reconstruction with the potential for further expansion. Here we introduce AIRPET and outline its current functionality and proposed additions.

Fields of Study & Subjects

Medical Imaging Techniques and Applications Radiation Detection and Scintillator Technologies Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
arXiv (Cornell University)
Publication date
29 January 2026
Document type
Preprint