Evidence map›Paper›PMID 40356674›Full record

Article... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics2024

RBAD: A Dataset and Benchmark for Retinal Vessels Branching Angle Detection.

Hao Wang, Wenhui Zhu, Jiayou Qin, Xin Li, Oana Dumitrascu, Xiwen Chen, Peijie Qiu, Abolfazl Razi, Yalin Wang

Abstract read
In one paragraph

Article in ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 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

9 authors.

Hao WangSchool of Computing, Clemson University.
Wenhui ZhuSchool of Computing and Augmented Intelligence, Arizona State University.
Jiayou QinDepartment of Electrical and Computer Engineering, Stevens Institute of Technology.
Xin LiSchool of Computing and Augmented Intelligence, Arizona State University.
Oana DumitrascuMayo Clinic.
Xiwen ChenSchool of Computing, Clemson University.
Peijie QiuMcKeley School of Engineering, Washington University in St.Louis.
Abolfazl RaziSchool of Computing, Clemson University.
Yalin WangSchool of Computing and Augmented Intelligence, Arizona State University.

Funding

Hierarchical Bayesian Analysis of Retinotopic Maps of the Human Visual Cortex with Conformal GeometryR01EY032125 · NEI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI LU, ZHONG-LIN, WANG, YALIN · 2021 to 2024
$1.2M
NEI NIH HHS R01 EY032125
6 · The paper itself

Abstract

Detecting retinal image analysis, particularly the geometrical features of branching points, plays an essential role in diagnosing eye diseases. However, existing methods used for this purpose often are coarse-level and lack fine-grained analysis for efficient annotation. To mitigate these issues, this paper proposes a novel method for detecting retinal branching angles using a self-configured image processing technique. Additionally, we offer an open-source annotation tool and a benchmark dataset comprising 40 images annotated with retinal branching angles. Our methodology for retinal branching angle detection and calculation is detailed, followed by a benchmark analysis comparing our method with previous approaches. The results indicate that our method is robust under various conditions with high accuracy and efficiency, which offers a valuable instrument for ophthalmic research and clinical applications. The dataset and source codes are available at https://github.com/Retinal-Research/RBAD.

Indexed as

Image ProcessingMedical DatasetMedical ImagingRetinal Analysis

Identifiers

PMID40356674
PMCPMC12068685

What OpenQuestion holds

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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.