ArticleTomography (Ann Arbor, Mich.)2018
Feasibility of Deep Learning-Based PET/MR Attenuation Correction in the Pelvis Using Only Diagnostic MR Images.
Article in Tomography (Ann Arbor, Mich.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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.
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
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy.Frontiers in radiology · 2024Pooled it
- Artificial Intelligence Across the PET Reconstruction Pipeline: An Update.AJR. American journal of roentgenology · 2026Review
- The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025Review
- An Investigation on Cross-Tracer Generalizability of Deep Learning-based PET Attenuation Correction.IEEE transactions on radiation and plasma medical sciences · 2025Article
- POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation.IEEE transactions on medical imaging · 2025Article
- Context-Aware Transformer GAN for Direct Generation of Attenuation and Scatter Corrected PET Data.IEEE transactions on radiation and plasma medical sciences · 2024Article
- Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis.EJNMMI physics · 2024Article
- Attenuation Correction of Long Axial Field-of-View Positron Emission Tomography Using Synthetic Computed Tomography Derived from the Emission Data: Application to Low-Count Studies and Multiple Tracers.Diagnostics (Basel, Switzerland) · 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
- A review of PET attenuation correction methods for PET-MR.EJNMMI physics · 2023Review
- Pelvic PET/MR attenuation correction in the image space using deep learning.Frontiers in oncology · 2023Article
- Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.European journal of nuclear medicine and molecular imaging · 2022Article
- Data Management and Network Architecture Effect on Performance Variability in Direct Attenuation Correction via Deep Learning for Cardiac SPECT: A Feasibility Study.IEEE transactions on radiation and plasma medical sciences · 2022Article
- A deep learning-based whole-body solution for PET/MRI attenuation correction.EJNMMI physics · 2022Article
- Deep learning-based attenuation correction for whole-body PET - a multi-tracer study withEuropean journal of nuclear medicine and molecular imaging · 2022Article
- Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks.Scientific reports · 2022Article
- Evaluation of Deep Learning-Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022Article
- 2D-to-3D image translation of complex nanoporous volumes using generative networks.Scientific reports · 2021Article
- Artificial Intelligence-Based Data Corrections for Attenuation and Scatter in Position Emission Tomography and Single-Photon Emission Computed Tomography.PET clinics · 2021Review
- Applications of artificial intelligence in nuclear medicine image generation.Quantitative imaging in medicine and surgery · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
This study evaluated the feasibility of using only diagnostically relevant magnetic resonance (MR) images together with deep learning for positron emission tomography (PET)/MR attenuation correction (deepMRAC) in the pelvis. Such an approach could eliminate dedicated MRAC sequences that have limited diagnostic utility but can substantially lengthen acquisition times for multibed position scans. We used axial T2 and T1 LAVA Flex magnetic resonance imaging images that were acquired for diagnostic purposes as inputs to a 3D deep convolutional neural network. The network was trained to produce a discretized (air, water, fat, and bone) substitute computed tomography (CT) (CT
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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.