Predicting Region of Interest in Human Visual Search Based on Statistical Texture and Gabor Features.

Hongwei Lin, Diego Andrade, Mini Das, Howard C Gifford

Abstract readPreprint

In one paragraph

Article in ArXiv, 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

4 authors.

Hongwei LinDepartment of Biomedical Engineering, University of Houston, 3517 Cullen Blvd, Houston, TX 77204, USA.

Diego AndradeDepartment of Biomedical Engineering, University of Houston, 3517 Cullen Blvd, Houston, TX 77204, USA.

Mini DasDepartment of Biomedical Engineering, University of Houston, 3517 Cullen Blvd, Houston, TX 77204, USA.

Howard C GiffordDepartment of Biomedical Engineering, University of Houston, 3517 Cullen Blvd, Houston, TX 77204, USA.

Funding

Development of Spectral Phase Contrast Micro-CTR01EB029761 · NIBIB · UNIVERSITY OF HOUSTON · PI Mini Das · 2020 to 2026

$3.2M

A Real-time Multifunctional System for Home TelehealthR43EB003246 · NIBIB · KC SCIENTIFIC AND TECHNOLOGIES, INC. · PI XU, XIAO-LIANG P · 2004 to 2004

$100k

NIBIB NIH HHS R01 EB029761NIBIB NIH HHS R43 EB003246

6 · The paper itself

Abstract

Understanding human visual search behavior is a fundamental problem in vision science and computer vision, with direct implications for modeling how observers allocate attention in location-unknown search tasks. In this study, we investigate the relationship between Gabor-based features and gray-level co-occurrence matrix (GLCM)-based texture features in modeling early-stage visual search behavior. Two feature-combination pipelines are proposed to integrate Gabor and GLCM features for narrowing the region of possible human fixations. The pipelines are evaluated using simulated digital breast tomosynthesis images. Results show qualitative agreement among fixation candidates predicted by the proposed pipelines and a threshold-based model observer. A strong correlation (

Indexed as

Eye-trackingGabor FeaturesModel ObserverTexture FeaturesVisual Search

Identifiers

PMID41647236

PMCPMC12869375

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LicenceCC BY

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Registered trials

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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.