Evidence map›Paper›PMID 35419500›Full record

ArticleIEEE transactions on radiation and plasma medical sciences2021

Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment.

Adam S Wang, Norbert J Pelc

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in IEEE transactions on radiation and plasma medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.3field-weighted citation impact, top 22% of its field
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

23 citing papers in PubMed, 40 citations in OpenAlex.

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  18. [A comprehensive review on photon-counting computed tomography: Principles, technical hurdles and analysis of clinical applications].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023
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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

2 authors at 1 institution in 1 country.

Adam S WangDepartments of Radiology and, by courtesy, Electrical Engineering, Stanford University, Stanford, CA 94305 USA.
Norbert J PelcDepartment of Radiology, Stanford University, Stanford, CA 94305 USA.
Stanford University · US

Funding

High dose efficiency CT SystemU01EB017140 · NIBIB · STANFORD UNIVERSITY · PI EDIC, PETER, PELC, NORBERT J. · 2014 to 2018
$5.4M
Software tool for routine, rapid, patient-specific CT organ dose estimationU01EB023822 · NIBIB · MARQUETTE UNIVERSITY · PI SCHMIDT, TALY GILAT, VAN HETEREN, JOHN · 2017 to 2020
$2.1M
NIBIB NIH HHS U01 EB017140NIBIB NIH HHS U01 EB023822
6 · The paper itself

Abstract

Photon counting x-ray detectors (PCDs) with spectral capabilities have the potential to revolutionize computed tomography (CT) for medical imaging. The ideal PCD provides accurate energy information for each incident x-ray, and at high spatial resolution. This information enables material-specific imaging, enhanced radiation dose efficiency, and improved spatial resolution in CT images. In practice, PCDs are affected by non-idealities, including limited energy resolution, pulse pileup, and cross talk due to charge sharing, K-fluorescence, and Compton scattering. In order to maximize their performance, PCDs must be carefully designed to reduce these effects and then later account for them during correction and post-acquisition steps. This review article examines algorithms for using PCDs in spectral CT applications, including how non-idealities impact image quality. Performance assessment metrics that account for spatial resolution and noise such as the detective quantum efficiency (DQE) can be used to compare different PCD designs, as well as compare PCDs with conventional energy integrating detectors (EIDs). These methods play an important role in enhancing spectral CT images and assessing the overall performance of PCDs.

Indexed as

cross talkimage noisematerial decompositionPhoton countingpulse pileupspectral CT

Identifiers

PMID35419500
PMCPMC9000208
OpenAlexW3041804771

What OpenQuestion holds

Textmetadata
LicenceTDM
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.