Evidence map›Paper›PMID 41570385›Full record

ArticlePhysics in medicine and biology2026

Ideal observer estimation for binary tasks with stochastic object models.

Jingyan Xu, Frederic Noo

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jingyan XuDepartment of Radiology, Johns Hopkins University, Baltimore, MD, United States of America.ORCID 0000-0003-3047-8198
Frederic NooDepartment of Radiology and Imaging Science, University of Utah, Salt Lake City, UT, United States of America.ORCID 0000-0002-5417-3439

Funding

DL-based CT image formation with characterization and control of resolution and noiseR21EB033426 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI XU, JINGYAN · 2023 to 2025
$658k
Stationary spectral encoding for multi-energy CT with energy-integrated detectorsR21EB034337 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI XU, JINGYAN · 2023 to 2024
$461k
Development and validation of diffusion-model enabled computational observers for clinical diagnostic task performance evaluation of deep learning CT algorithmsR21EB037806 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI XU, JINGYAN · 2025 to 2025
$428k
NIBIB NIH HHS R21 EB033426NIBIB NIH HHS R21 EB034337NIBIB NIH HHS R21 EB037806
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Image Processing, Computer-AssistedStochastic Processesarea under the receiver operating characteristic (ROC) curve (AUC)Bayesian inferencedual energy CTideal observersspectral optimizationstochastic object models (SOMs)

Identifiers

PMID41570385
PMCPMC12921438

What Socratic holds

Textmetadata
LicenceCC BY
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.