Evidence map›Paper›PMID 33120903›Full record

ArticleSensors (Basel, Switzerland)2020

CdTe Based Energy Resolving, X-ray Photon Counting Detector Performance Assessment: The Effects of Charge Sharing Correction Algorithm Choice.

Oliver L P Pickford Scienti, Jeffrey C Bamber, Dimitra G Darambara

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. 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. Article
  2. [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
    Review
  3. Article
  4. Article
  5. Review
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

3 authors.

Oliver L P Pickford ScientiJoint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London SM2 5NG, UK.ORCID 0000-0002-5745-8309
Jeffrey C BamberJoint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London SM2 5NG, UK.ORCID 0000-0001-9436-1832
Dimitra G DarambaraJoint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London SM2 5NG, UK.

Funding

Cancer Research UK 16464Cancer Research UK C1060/A16464Cancer Research UK C209/A20926
6 · The paper itself

Abstract

Most modern energy resolving, photon counting detectors employ small (sub 1 mm) pixels for high spatial resolution and low per pixel count rate requirements. These small pixels can suffer from a range of charge sharing effects (CSEs) that degrade both spectral analysis and imaging metrics. A range of charge sharing correction algorithms (CSCAs) have been proposed and validated by different groups to reduce CSEs, however their performance is often compared solely to the same system when no such corrections are made. In this paper, a combination of Monte Carlo and finite element methods are used to compare six different CSCAs with the case where no CSCA is employed, with respect to four different metrics: absolute detection efficiency, photopeak detection efficiency, relative coincidence counts, and binned spectral efficiency. The performance of the various CSCAs is explored when running on systems with pixel pitches ranging from 100 µm to 600µm, in 50 µm increments, and fluxes from 10

Indexed as

CdTecharge sharing correctioncharge sharing effectsenergy resolvingphoton countingspectral imaging

Identifiers

PMID33120903
PMCPMC7663711

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.