Evidence map›Paper›PMID 30980728›Full record

ArticleMedical physics2019

SparseCT: System concept and design of multislit collimators.

Baiyu Chen, Erich Kobler, Matthew J Muckley, Aaron D Sodickson, Thomas O'Donnell, Thomas Flohr, Bernhard Schmidt, Daniel K Sodickson, Ricardo Otazo

Abstract read
In one paragraph

Article in Medical physics, 2019. 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. Fourier Diffusion for Sparse CT Reconstruction.Proceedings of SPIE--the International Society for Optical Engineering · 2024
    Article
  2. Article
  3. An Investigation of Slot-scanning for Mammography and Breast CT.Proceedings of SPIE--the International Society for Optical Engineering · 2020
    Article
  4. 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

9 authors.

Baiyu ChenDepartment of Radiology, NYU School of Medicine, New York, NY, 10016, USA.
Erich KoblerInstitute of Computer Graphics and Vision, Graz University of Technology, Graz, 8010, Austria.
Matthew J MuckleyDepartment of Radiology, NYU School of Medicine, New York, NY, 10016, USA.
Aaron D SodicksonDepartment of Radiology, Brigham and Women's Hospital, Boston, MA, 02115, USA.
Thomas O'DonnellSiemens Healthineers, Malvern, PA, 19355, USA.
Thomas FlohrSiemens Healthineers, Forchheim, 91301, Germany.
Bernhard SchmidtSiemens Healthineers, Forchheim, 91301, Germany.
Daniel K SodicksonDepartment of Radiology, NYU School of Medicine, New York, NY, 10016, USA.
Ricardo OtazoDepartment of Radiology, NYU School of Medicine, New York, NY, 10016, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Elisa de Stanchina · 1985 to 2026
$347.4M
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Dmitry S Novikov · 2014 to 2026
$19.3M
Critical resources to evaluate CT scan techniques and dose reduction approachesU01EB017185 · NIBIB · MAYO CLINIC ROCHESTER · PI MCCOLLOUGH, CYNTHIA H · 2013 to 2016
$3.6M
SparseCT: Order-of-Magnitude Dose Reduction with Interrupted-Beam AcquisitionU01EB018760 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI OTAZO, RICARDO, SODICKSON, DANIEL K · 2015 to 2018
$2.8M
NCI NIH HHS P30 CA008748NIBIB NIH HHS P41 EB017183NIBIB NIH HHS U01 EB017185NIBIB NIH HHS U01 EB018760
6 · The paper itself

Abstract

purposeSparseCT, an undersampling scheme for compressed sensing (CS) computed tomography (CT), has been proposed to reduce radiation dose by acquiring undersampled projection data from clinical CT scanners (Koesters et al. in, SparseCT: Interrupted-Beam Acquisition and Sparse Reconstruction for Radiation Dose Reduction; 2017). SparseCT partially blocks the x-ray beam with a multislit collimator (MSC) to perform a multidimensional undersampling along the view and detector row dimensions. SparseCT undersamples the projection data within each view and moves the MSC along the z-direction during gantry rotation to change the undersampling pattern. It enables reconstruction of images from undersampled data using CS algorithms. The purpose of this work is to design the spacing and width of the MSC slits and the MSC motion patterns based on beam separation, undersampling efficiency, and image quality. The development and testing of a SparseCT prototype with the designed MSC will be described in a following paper.

methodsWe chose a few initial MSC designs based on the guidance from two metrics: beam separation and undersampling efficiency. Both beam separation and undersampling efficiency were measured from numerically simulated photon distribution with MSC taken into consideration. Beam separation measures the separation between x-ray beams from consecutive slits, taking into account penumbra effects on both sides of each slit. Undersampling efficiency measures the dose-weighted similarity between penumbra undersampling and binary undersampling, in other words, the effective contribution of the incident dose to the signal to noise ratio of the projection data. We then compared the initially chosen MSC designs in terms of their reconstruction image quality. SparseCT projections were simulated from fully sampled patient projection data according to the MSC design and motion pattern, reconstructed iteratively using a sparsity-enforcing penalized weighted least squares cost function with ordered subsets/momentum algorithm, and compared visually and quantitatively.

resultsSimulated photon distributions indicate that the size of the penumbra is dominated by the size of the focal spot. Therefore, a wider MSC slit and a smaller focal spot lead to increased beam separation and undersampling efficiency. For fourfold undersampling with a 1.2 mm focal spot, a minimum MSC slit width of three detector rows (projected to the detector surface) is needed for beam separation; for threefold undersampling, a minimum slit width of four detector rows is needed. Simulations of SparseCT projection and reconstruction indicate that the motion pattern of the MSC does not have a visible impact on image quality. An MSC slit width of three or four detector rows yields similar image quality.

conclusionThe MSC is the key component of the SparseCT method. Simulations of MSC designs incorporating x-ray beam penumbra effects showed that for threefold and fourfold dose reductions, an MSC slit width of four detector rows provided reasonable beam separation, undersampling efficiency, and image quality.

Indexed as

Image Processing, Computer-AssistedModels, TheoreticalPhantoms, ImagingPhotonsTomography, X-Ray Computedcompressed sensingCTmultislit collimator (MSC)penumbraSparseCTUndersampling

Identifiers

PMID30980728
PMCPMC6561820

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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.