Evidence map›Paper›PMID 33154609›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2020

Model-based Material Decomposition with System Blur Modeling.

Wenying Wang, Matthew Tivnan, Grace J Gang, Yiqun Ma, Qian Cao, Minghui Lu, Josh Star-Lack, Richard E Colbeth, Wojciech Zbijewski, J Webster Stayman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. High-Resolution Model-based Material Decomposition for Multi-Layer Flat-Panel Detectors.Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography · 2020
    Article
  4. Perturbation Response of Model-based Material Decomposition with Edge-Preserving Penalties.Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography · 2020
    Article
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

10 authors.

Wenying WangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
Matthew TivnanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
Grace J GangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
Yiqun MaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
Qian CaoDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
Minghui LuVarex Imaging Corp., 683 River Oaks Pkwy, San Jose, CA 95134.
Josh Star-LackVarex Imaging Corp., 683 River Oaks Pkwy, San Jose, CA 95134.
Richard E ColbethVarex Imaging Corp., 683 River Oaks Pkwy, San Jose, CA 95134.
Wojciech ZbijewskiDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.
J Webster StaymanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205.

Funding

BIOMEDICAL ENGINEERING TRAINING PROGRAMT32GM007057 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI KANOLD, PATRICK O, KARCHIN, RACHEL · 1985 to 2023
$10.4M
Monitoring of fractures with internal fixators using weight-bearing quantitative cone beam CTR01EB025470 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI STAYMAN, JOSEPH WEBSTER, ZBIJEWSKI, WOJCIECH BARTOSZ · 2018 to 2021
$1.5M
NIBIB NIH HHS R01 EB025470NIGMS NIH HHS T32 GM007057
6 · The paper itself

Abstract

In this work, we present a novel model-based material decomposition (MBMD) approach for x-ray CT that includes system blur in the measurement model. Such processing has the potential to extend spatial resolution in material density estimates - particularly in systems where different spectral channels exhibit different spatial resolutions. We illustrate this new approach for a dual-layer detector x-ray CT and compare MBMD algorithms with and without blur in the reconstruction forward model. Both qualitative and quantitative comparisons of performance with and without blur modeling are reported. We find that blur modeling yields images with better recovery of high-resolution structures in an investigation of reconstructed line pairs as well as lower cross-talk bias between material bases that is ordinarily found due to mismatches in spatial resolution between spectral channels. The extended spatial resolution of the material decompositions has potential application in a range of high-resolution clinical tasks and spectral CT systems where spectral channels exhibit different spatial resolutions.

Identifiers

PMID33154609
PMCPMC7641016

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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.