Evidence map›Paper›PMID 39687383›Full record

ArticleData in brief2024

Dataset for identifying paracentral acute middle maculopathy lesions in spectral-domain optical coherence tomography images.

Tianqiao Zhang, Mengjiao Zhang, Dexun Zhang, Wenjing Meng, Zhenzhen Li, Zhengwei Zhang

Abstract read
In one paragraph

Article in Data in brief, 2024. 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

6 authors.

Tianqiao ZhangSchool of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Mengjiao ZhangSchool of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Dexun ZhangSchool of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Wenjing MengDepartment of Library Services, Guilin University of Electronic Technology, Guilin, China.
Zhenzhen LiSchool of Information Engineering, Nanchang Institute of Technology, Nanchang, China.
Zhengwei ZhangDepartment of Ophthalmology, Jiangnan University Medical Center, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper introduces a comprehensive dataset of spectral-domain optical coherence tomography (SD-OCT) images of human eyes affected by paracentral acute middle maculopathy (PAMM). Acquired with an SD-OCT device (Optovue, Fremont, California, USA), the dataset includes 133 OCT images of lesions. Each image is paired with a corresponding YOLO label in TXT format, representing manually annotated lesion regions of PAMM, created with the assistance of ophthalmologists. This dataset is invaluable for developing and evaluating automatic algorithms for diagnosing PAMM lesions. By providing detailed annotations and high-quality images, it facilitates advancements in understanding the morphology, progression, and potential treatments of PAMM. Furthermore, it supports the improvement of diagnostic accuracy and the development of targeted therapeutic interventions for retinal diseases. This resource addresses a significant gap in the availability of public datasets focused on PAMM lesions, promoting further research in automated intelligent analysis systems for retinal OCT images.

Indexed as

Anomaly detectionBounding box annotationOphthalmologyRetinal disease

Identifiers

PMID39687383
PMCPMC11647149

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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.