Evidence map›Paper›PMID 28649162›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2016

Scatter estimation and removal of anti-scatter grid-line artifacts from anthropomorphic head phantom images taken with a high resolution image detector.

R Rana, A Jain, A Shankar, D R Bednarek, S Rudin

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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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

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Simultaneous scatter rejection and correction method using 2D antiscatter grids for CBCT.Proceedings of SPIE--the International Society for Optical Engineering · 2020
    Article
  4. Article
  5. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

R RanaToshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214.
A JainToshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214.
A ShankarToshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214.
D R BednarekToshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214.
S RudinToshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214.

Funding

Micro-Radiographic Imager for Neuroovascular InterventionsR01EB002873 · NIBIB · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI RUDIN, STEPHEN · 2003 to 2015
$5.6M
NIBIB NIH HHS R01 EB002873
6 · The paper itself

Abstract

In radiography, one of the best methods to eliminate image-degrading scatter radiation is the use of anti-scatter grids. However, with high-resolution dynamic imaging detectors, stationary anti-scatter grids can leave grid-line shadows and moiré patterns on the image, depending upon the line density of the grid and the sampling frequency of the x-ray detector. Such artifacts degrade the image quality and may mask small but important details such as small vessels and interventional device features. Appearance of these artifacts becomes increasingly severe as the detector spatial resolution is improved. We have previously demonstrated that, to remove these artifacts by dividing out a reference grid image, one must first subtract the residual scatter that penetrates the grid; however, for objects with anatomic structure, scatter varies throughout the FOV and a spatially differing amount of scatter must be subtracted. In this study, a standard stationary Smit-Rontgen X-ray grid (line density - 70 lines/cm, grid ratio - 13:1) was used with a high-resolution CMOS detector, the Dexela 1207 (pixel size - 75 micron) to image anthropomorphic head phantoms. For a 15 × 15cm FOV, scatter profiles of the anthropomorphic head phantoms were estimated then iteratively modified to minimize the structured noise due to the varying grid-line artifacts across the FOV. Images of the anthropomorphic head phantoms taken with the grid, before and after the corrections, were compared demonstrating almost total elimination of the artifact over the full FOV. Hence, with proper computational tools, anti-scatter grid artifacts can be corrected, even during dynamic sequences.

Indexed as

anthropomorphic head phantomanti-scatter gridCMOS detectorgrid artifactshigh resolution detectoriterative artifact removalscatter estimationx-ray imaging

Identifiers

PMID28649162
PMCPMC5482265

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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.