Evidence map›Paper›PMID 38500666›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2024

Super-resolution reconstruction of

Yansong Zhu, Benjamin A Spencer, Zhaoheng Xie, Edwin K Leung, Reimund Bayerlein, Negar Omidvari, Simon R Cherry, Jinyi Qi, Ramsey D Badawi, Guobao Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Yansong ZhuDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, 95817, USA.
Benjamin A SpencerDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, 95817, USA.
Zhaoheng XieDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Edwin K LeungUIH America, Inc., Houston, TX, 77054, USA.
Reimund BayerleinDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, 95817, USA.
Negar OmidvariDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Simon R CherryDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Jinyi QiDepartment of Biomedical Engineering, University of California Davis, Davis, CA, 95616, USA.
Ramsey D BadawiDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, 95817, USA.
Guobao WangDepartment of Radiology, University of California Davis Medical Center, Sacramento, CA, 95817, USA.

Funding

Single-tracer Multiparametric PET ImagingR01EB033435 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI WANG, GUOBAO · 2022 to 2025
$2.4M
PET-enabled Dual-energy CTR21EB027346 · NIBIB · UNIVERSITY OF CALIFORNIA AT DAVIS · PI WANG, GUOBAO · 2019 to 2021
$628k
NIBIB NIH HHS R01 EB033435NIBIB NIH HHS R21 EB027346
6 · The paper itself

Abstract

Dual-energy computed tomography (DECT) enables material decomposition for tissues and produces additional information for PET/CT imaging to potentially improve the characterization of diseases. PET-enabled DECT (PDECT) allows the generation of PET and DECT images simultaneously with a conventional PET/CT scanner without the need for a second x-ray CT scan. In PDECT, high-energy

Indexed as

kernel MLAApatient studyPET-enabled dual-energy CTphantom studysuper-resolution

Identifiers

PMID38500666
PMCPMC10947795

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.