ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2021
Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study.
Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 57 citations in OpenAlex.
- [Nuclear medicine-necessity and opportunities in modern cardiology].Innere Medizin (Heidelberg, Germany) · 2026Review
- Deep learning-based attenuation and scatter correction in myocardial SPECT without using X-ray CT images.Radiological physics and technology · 2026Article
- Approximate CT-free patient specific attenuation correction method for cardiac-dedicated pinhole CZT system: a feasibility phantom study.EJNMMI physics · 2026Article
- On Hallucinations in Artificial Intelligence-Generated Content for Nuclear Medicine Imaging (the DREAM Report).Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026Review
- Towards practical radiopharmaceutical treatment planning: a review of dosimetry simplification techniques.Theranostics · 2026Review
- Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.BMC medical imaging · 2025Article
- Artificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study.PloS one · 2025Article
- The role of deep learning in myocardial perfusion imaging for diagnosis and prognosis: A systematic review.iScience · 2024Review
- 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
- DuDoCFNet: Dual-Domain Coarse-to-Fine Progressive Network for Simultaneous Denoising, Limited-View Reconstruction, and Attenuation Correction of Cardiac SPECT.IEEE transactions on medical imaging · 2024Article
- Deep learning approach using SPECT-to-PET translation for attenuation correction in CT-less myocardial perfusion SPECT imaging.Annals of nuclear medicine · 2024Article
- Artificial Intelligence Empowered Nuclear Medicine and Molecular Imaging in Cardiology: A State-of-the-Art Review.Phenomics (Cham, Switzerland) · 2023Review
- Accurate and efficient rapid acquisition early post-injection stress-first CZT SPECT myocardial perfusion imaging with tetrofosmin and attenuation correction.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- The past, present, and future of attenuation correction for myocardial perfusion imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Transfer learning-based attenuation correction for static and dynamic cardiac PET using a generative adversarial network.European journal of nuclear medicine and molecular imaging · 2023Article
- Deep-learning-based methods of attenuation correction for SPECT and PET.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Deep learning approximation of attenuation maps for myocardial perfusion SPECT with an IQEJNMMI physics · 2023Article
- Synthetic Attenuation Correction Maps for SPECT Imaging Using Deep Learning: A Study on Myocardial Perfusion Imaging.Diagnostics (Basel, Switzerland) · 2023Article
- Applying deep learning attenuation correction in the presence of motion.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quantification with attenuation correction (AC) is challenging and artifacts are routinely encountered in daily clinical practice. In this work, we demonstrated a direct AC technique using deep learning (DL) for myocardial perfusion imaging (MPI).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.