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Artificial intelligence in nuclear medicine: Historical milestones and core principles


Authors: M. Bejtic 1,2;  V. Kamírová 1;  O. Lang 1;  M. Lang 1;  M. Darsa 2
Authors‘ workplace: Prague Medical Care Department, s. r. o., Praha 1;  Fakulta biomedicínského inženýrství, České vysoké učení technické v Praze, Kladno, ČR 2
Published in: NuklMed 2025;14:60-64
Category: Review Article

Overview

Artificial intelligence (AI) represents a rapidly evolving technology with a significant impact on modern medicine, including nuclear medicine, where it offers new possibilities for improving diagnostics, quantitative assessment, and prognostic evaluation. This article provides a comprehensive overview of the historical development of AI –⁠ from its theoretical foundations in the 1950s, through the emergence of machine learning and deep neural networks, to contemporary architectures based on convolutional networks, generative adversarial models, and large language models.

The text highlights the first practical and clinically relevant applications of AI in nuclear medicine, particularly in cardiology, neurology, and oncology. These include automated interpretation of myocardial perfusion SPECT, PET brain analysis in neurodegenerative diseases, and quantitative evaluation of bone metastases. Special attention is given to models that have undergone independent validation and demonstrated real clinical benefit, such as automated bone scan index calculation and algorithms for detecting Alzheimer’s disease from FDG PET.

In conclusion, the article summarizes the key technological developments that have shaped today’s AI capabilities in nuclear medicine and illustrates how the progression from simple algorithms to advanced deep and generative models has influenced current clinical practice.

Keywords:

artificial intelligence; nuclear medicine; history; machine learning; deep learning; convolutional network


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Labels
Nuclear medicine Radiodiagnostics Radiotherapy
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