Evidence map›Paper›PMID 33315556›Full record

ArticleIEEE transactions on medical imaging2021

Foveated Model Observers for Visual Search in 3D Medical Images.

Miguel A Lago, Craig K Abbey, Miguel P Eckstein

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

11 citing papers in PubMed, 14 citations in OpenAlex.

  1. Distinct system-level computations underlie perceptual variation across the visual field.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Featural Representation and Internal Noise Underlie the Eccentricity Effect in Contrast Sensitivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  9. Article
  10. Article
  11. Medical image quality metrics for foveated model observers.Journal of medical imaging (Bellingham, Wash.) · 2021
    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

3 authors at 1 institution in 1 country.

Miguel A Lago
Craig K Abbey
Miguel P Eckstein
University of California, Santa Barbara · US

Funding

Visual Search in 3D Medical Imaging ModalitiesR01EB026427 · NIBIB · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI Miguel Patricio Eckstein · 2018 to 2026
$2.5M
Assessment of medical image quality with foveated search modelsR01EB018958 · NIBIB · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI ECKSTEIN, MIGUEL PATRICIO · 2015 to 2018
$1.7M
NIBIB NIH HHS R01 EB018958NIBIB NIH HHS R01 EB026427
6 · The paper itself

Abstract

Model observers have a long history of success in predicting human observer performance in clinically-relevant detection tasks. New 3D image modalities provide more signal information but vastly increase the search space to be scrutinized. Here, we compared standard linear model observers (ideal observers, non-pre-whitening matched filter with eye filter, and various versions of Channelized Hotelling models) to human performance searching in 3D 1/f

Indexed as

Image Processing, Computer-AssistedHumansLinear ModelsObserver Variation

Identifiers

PMID33315556
PMCPMC7994931
OpenAlexW3096846906

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.