Evidence map›Paper›PMID 39447603›Full record

ArticlePhysics in medicine and biology2024

Investigation of scatter energy window width and count levels for deep learning-based attenuation map estimation in cardiac SPECT/CT imaging.

Yuan Chen, P Hendrik Pretorius, Yongyi Yang, Michael A King, Clifford Lindsay

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Physics in medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. AI in SPECT Imaging: Opportunities and Challenges.Seminars in nuclear medicine · 2025
    Review
  2. 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

5 authors.

Yuan ChenDepartment of Radiology, University of Massachusetts Medical School, Worcester, MA, United States of America.ORCID 0000-0003-0942-4996
P Hendrik PretoriusDepartment of Radiology, University of Massachusetts Medical School, Worcester, MA, United States of America.
Yongyi YangDepartment of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, United States of America.
Michael A KingDepartment of Radiology, University of Massachusetts Medical School, Worcester, MA, United States of America.
Clifford LindsayDepartment of Radiology, University of Massachusetts Medical School, Worcester, MA, United States of America.

Funding

Optimization of diagnostic accuracy, radiation dose, and patient throughput for cardiac SPECT via advanced and clinically practical cardiac-respiratory motion correction and deep learningR01HL154687 · NHLBI · ILLINOIS INSTITUTE OF TECHNOLOGY · PI KING, MICHAEL A, YANG, YONGYI · 2020 to 2023
$3.1M
NHLBI NIH HHS R01 HL154687
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningHeartImage Processing, Computer-AssistedScattering, RadiationSingle Photon Emission Computed Tomography Computed TomographyHumansattenuation correctioncardiac SPECTdeep learninglow dosescatter window

Identifiers

PMID39447603
PMCPMC11636602

What Socratic 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 Socratic graph.