ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2022
Cross-vender, cross-tracer, and cross-protocol deep transfer learning for attenuation map generation of cardiac SPECT.
Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
- Transfer learning‑based attenuation correction inEJNMMI physics · 2025Article
- On the Effect of the Patient Table on Attenuation in Myocardial Perfusion Imaging SPECT.EJNMMI physics · 2025Article
- ISIT-GEN: An in silico imaging trial to assess the inter-scanner generalizability of CTLESS for myocardial perfusion SPECT on defect-detection task.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation.Medical image analysis · 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
- Artificial intelligence-based joint attenuation and scatter correction strategies for multi-tracer total-body PET.EJNMMI physics · 2024Article
- Respiratory signal estimation for cardiac perfusion SPECT using deep learning.Medical physics · 2024Article
- Artificial Intelligence Empowered Nuclear Medicine and Molecular Imaging in Cardiology: A State-of-the-Art Review.Phenomics (Cham, Switzerland) · 2023Review
- Deep learning approximation of attenuation maps for myocardial perfusion SPECT with an IQEJNMMI physics · 2023Article
- DuSFE: Dual-Channel Squeeze-Fusion-Excitation co-attention for cross-modality registration of cardiac SPECT and CT.Medical image analysis · 2023Article
- Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies.EJNMMI physics · 2023Review
- Generative adversarial network-based attenuation correction forFrontiers in medicine · 2023Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
It has been proved feasible to generate attenuation maps (μ-maps) from cardiac SPECT using deep learning. However, this assumed that the training and testing datasets were acquired using the same scanner, tracer, and protocol. We investigated a robust generation of CT-derived μ-maps from cardiac SPECT acquired by different scanners, tracers, and protocols from the training data. We first pre-trained a network using 120 studies injected with
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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.