Evidence map›Paper›PMID 30524041›Full record

ArticlePhysics in medicine and biology2018

Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout.

P Wu, J W Stayman, A Sisniega, W Zbijewski, D Foos, X Wang, N Aygun, R Stevens, J H Siewerdsen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Physics in medicine and biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Gamma radiation detector selection for CT scanner.Zeitschrift fur medizinische Physik · 2025
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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.

P WuDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.
J W StaymanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.
A SisniegaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.
W ZbijewskiDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.
D FoosCarestream Health, Rochester, NY 14608, United States of America.
X WangCarestream Health, Rochester, NY 14608, United States of America.
N AygunDepartment of Radiology, Johns Hopkins University, Baltimore, MD 21205, United States of America.
R StevensDepartment of Anesthesiology and Critical Care Medicine, Johns Hopkins University, Baltimore, MD 21205, United States of America.
J H SiewerdsenDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States of America.

Funding

Intraoperative Imaging for Guidance, Patient Safety, and OR Quality AssuranceR01EB017226 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI SIEWERDSEN, JEFFREY H · 2014 to 2017
$2.1M
NIBIB NIH HHS R01 EB017226
6 · The paper itself

Abstract

Cone-beam CT (CBCT) systems commonly incorporate a flat-panel detector (FPD) with multiple-gain readout capability to reduce electronic noise and extend dynamic range. In this work, we report a penalized weighted least-squares (PWLS) method for CBCT image reconstruction with a system model that includes the electronic noise characteristics of FPDs, including systems with dynamic-gain or dual-gain (DG) readout in which the electronic noise is spatially varying. Statistical weights in PWLS were modified to account for the contribution of the electronic noise (algorithm denoted [Formula: see text]), and the method was combined with a certainty-based approach that improves the homogeneity of spatial resolution (algorithm denoted [Formula: see text]). The methods were tested in phantom studies designed to stress DG readout characteristics and translated to a clinical study for CBCT of patients with head traumas. The [Formula: see text] method demonstrated superior noise-resolution tradeoffs compared to filtered back-projection (FBP) and conventional PWLS. For example, with spatial resolution (edge-spread function width) matched at 0.65 mm, [Formula: see text] reduced variance by 28%-39% and 15%-25% compared to FBP and PWLS, respectively. The [Formula: see text] method achieved more homogeneous spatial resolution than [Formula: see text] while maintaining similar variance reduction. These findings were confirmed in clinical studies, which showed ~20% variance reduction in peripheral regions of the brain, potentially improving visual image quality in detection of epidural and/or subdural intracranial hemorrhage. The results are consistent with the general notion that incorporating a more accurate system model improves performance in optimization-based statistical CBCT reconstruction-in this case, a more accurate model for (spatially varying) electronic noise to improve detectability of low-contrast lesions.

Indexed as

Cone-Beam Computed TomographyPhantoms, ImagingSignal-To-Noise RatioAlgorithmsArtifactsCraniocerebral TraumaElectronicsHumansImage Processing, Computer-AssistedLeast-Squares AnalysisModels, BiologicalModels, StatisticalReproducibility of Results

Identifiers

PMID30524041
PMCPMC13135352

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Registered trials

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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.