Evidence map›Paper›PMID 27694700›Full record

ArticlePhysics in medicine and biology2016

Optimization-based image reconstruction with artifact reduction in C-arm CBCT.

Dan Xia, David A Langan, Stephen B Solomon, Zheng Zhang, Buxin Chen, Hao Lai, Emil Y Sidky, Xiaochuan Pan

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A balanced total-variation-Chambolle-Pock algorithm for EPR imaging.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2021
    Article
  5. Article
  6. Non-convex primal-dual algorithm for image reconstruction in spectral CT.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2021
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

8 authors.

Dan XiaDepartment of Radiology, The University of Chicago, Chicago, IL, USA.
David A LanganGE Global Research, Niskayuna, NY, USA.
Stephen B SolomonMemorial Sloan Kettering Cancer Center, New York, NY, USA.
Zheng ZhangDepartment of Radiology, The University of Chicago, Chicago, IL, USA.
Buxin ChenDepartment of Radiology, The University of Chicago, Chicago, IL, USA.
Hao LaiGE Global Research, Niskayuna, NY, USA.
Emil Y SidkyDepartment of Radiology, The University of Chicago, Chicago, IL, USA.
Xiaochuan PanDepartment of Radiology, The University of Chicago, Chicago, IL, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Digital Specimen Tomosynthesis for Volumetric Imaging of Lumpectomy SpecimensR01EB018102 · NIBIB · UNIVERSITY OF CHICAGO · PI PAN, XIAOCHUAN · 2014 to 2017
$2.0M
Development of Advanced C-arm Cone-Beam CT for the Treatment of Liver CancerR01CA182264 · NCI · UNIVERSITY OF CHICAGO · PI PAN, XIAOCHUAN · 2014 to 2017
$1.8M
Limited Angle Image ReconstructionR01CA158446 · NCI · UNIVERSITY OF CHICAGO · PI SIDKY, EMIL Y · 2012 to 2015
$1.2M
NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA158446NCI NIH HHS R01 CA182264NIBIB NIH HHS R01 EB018102
6 · The paper itself

Abstract

We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g. data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility.

Indexed as

ArtifactsAlgorithmsAnimalsCone-Beam Computed TomographyHumansImage Processing, Computer-AssistedLiver DiseasesPhantoms, ImagingSwine

Identifiers

PMID27694700
PMCPMC5109550

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.