Evidence map›Paper›PMID 36719287›Full record

ReviewRadiology2023

Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.

Lennart R Koetzier, Domenico Mastrodicasa, Timothy P Szczykutowicz, Niels R van der Werf, Adam S Wang, Veit Sandfort, Aart J van der Molen, Dominik Fleischmann, Martin J Willemink

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
188citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

188 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  16. Dual energy CT of pediatric genitourinary disorders.Abdominal radiology (New York) · 2026
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128 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Lennart R Koetzier *From the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).
Domenico Mastrodicasa *From the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0001-8227-0757
Timothy P SzczykutowiczFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0002-3008-6568
Niels R van der WerfFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).
Adam S WangFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0001-9234-1264
Veit SandfortFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).
Aart J van der MolenFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0002-2376-9424
Dominik FleischmannFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0003-0715-0952
Martin J WilleminkFrom the Department of Radiology (L.R.K., D.M., A.S.W., V.S., D.F., M.J.W.) and Stanford Cardiovascular Institute (D.M., D.F., M.J.W.), Stanford University School of Medicine, 300 Pasteur Dr, Stanford, CA 94305-5105; Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wis (T.P.S.); Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands (N.R.v.d.W.); Clinical Science Western Europe, Philips Healthcare, Best, the Netherlands (N.R.v.d.W.); and Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.v.d.M.).ORCID 0000-0002-6991-6557

Funding

Multi-Disciplinary Training Program in Cardiovascular Imaging at StanfordT32EB009035 · NIBIB · STANFORD UNIVERSITY · PI Koen Nieman, John M. Pauly · 2008 to 2026
$4.3M
NIBIB NIH HHS T32 EB009035
6 · The paper itself

Abstract

Filtered back projection (FBP) has been the standard CT image reconstruction method for 4 decades. A simple, fast, and reliable technique, FBP has delivered high-quality images in several clinical applications. However, with faster and more advanced CT scanners, FBP has become increasingly obsolete. Higher image noise and more artifacts are especially noticeable in lower-dose CT imaging using FBP. This performance gap was partly addressed by model-based iterative reconstruction (MBIR). Yet, its "plastic" image appearance and long reconstruction times have limited widespread application. Hybrid iterative reconstruction partially addressed these limitations by blending FBP with MBIR and is currently the state-of-the-art reconstruction technique. In the past 5 years, deep learning reconstruction (DLR) techniques have become increasingly popular. DLR uses artificial intelligence to reconstruct high-quality images from lower-dose CT faster than MBIR. However, the performance of DLR algorithms relies on the quality of data used for model training. Higher-quality training data will become available with photon-counting CT scanners. At the same time, spectral data would greatly benefit from the computational abilities of DLR. This review presents an overview of the principles, technical approaches, and clinical applications of DLR, including metal artifact reduction algorithms. In addition, emerging applications and prospects are discussed.

Indexed as

Artificial IntelligenceDeep LearningAlgorithmsHumansImage Processing, Computer-AssistedRadiation DosageRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray Computed

Identifiers

PMID36719287
PMCPMC9968777

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.