ArticleDiagnostics (Basel, Switzerland)2023
Synthetic Attenuation Correction Maps for SPECT Imaging Using Deep Learning: A Study on Myocardial Perfusion Imaging.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- AI-based synthetic CT attenuation correction enables reliable quantitative SPECT in unilateral condylar hyperplasia.EJNMMI physics · 2026Article
- Instrumentation Digital Twins in PET and SPECT Imaging: Current Status, Challenges, and Future Directions.Computational and structural biotechnology journal · 2026Review
- Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.BMC medical imaging · 2025Article
- CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.IEEE transactions on medical imaging · 2024Article
- Investigation of scatter energy window width and count levels for deep learning-based attenuation map estimation in cardiac SPECT/CT imaging.Physics in medicine and biology · 2024Article
- Activity quantification and dosimetry in radiopharmaceutical therapy with reference toFrontiers in nuclear medicine · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
(1) Background: The CT-based attenuation correction of SPECT images is essential for obtaining accurate quantitative images in cardiovascular imaging. However, there are still many SPECT cameras without associated CT scanners throughout the world, especially in developing countries. Performing additional CT scans implies troublesome planning logistics and larger radiation doses for patients, making it a suboptimal solution. Deep learning (DL) offers a revolutionary way to generate complementary images for individual patients at a large scale. Hence, we aimed to generate linear attenuation coefficient maps from SPECT emission images reconstructed without attenuation correction using deep learning. (2) Methods: A total of 384 SPECT myocardial perfusion studies that used
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