PDC-DETR: a Parallel Dilated Convolutional Detection Transformer for preliminary screening of multiple macular degeneration.

Yuhang Wang, Wenhao Wei, Xinghao Pei, Honglei Zhan, Yu Tang, Yahong Li, Jing Bai, Jinshan Li

Abstract read

In one paragraph

Article in BMC medical imaging, 2025. 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

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0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yuhang Wang *The School of Information and Engineering, Dalian Polytechnic University, Dalian, 116034, China.

Wenhao Wei *The School of Information and Engineering, Dalian Polytechnic University, Dalian, 116034, China.

Xinghao PeiThe School of Information and Engineering, Dalian Polytechnic University, Dalian, 116034, China.

Honglei ZhanThe School of Bioengineering, Dalian Polytechnic University, Dalian, 116034, China.

Yu TangThe Department of Ophthalmology, Central Hospital of Dalian University of Technology (Dalian Municipal Central Hospital), Dalian, 116033, China.

Yahong LiThe School of Information and Engineering, Dalian Polytechnic University, Dalian, 116034, China. liyahong@dlpu.edu.cn.ORCID 0000-0003-1222-3095

Jing BaiThe Department of Ophthalmology, Central Hospital of Dalian University of Technology (Dalian Municipal Central Hospital), Dalian, 116033, China. baijingsky@163.com.

Jinshan LiThe School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, China.

Funding

Dalian Science and Technology Bureau,China， 2023ZXYG07

6 · The paper itself

Abstract

Current diagnostic approaches for macular degeneration in optical coherence tomography (OCT) images often lead to misdiagnosis due to their limited ability to capture the disease’s multiscale and irregular features. We present PDC-DETR, a Parallel Dilated Convolutional Detection Transformer, which introduces three major innovations for accurate and efficient macular degeneration analysis. First, a Parallel Feature-Optimized Attention Pyramid Network (PFOAPN) enables simultaneous modeling of global context and local details through multi-scale feature pathways. Second, a novel Wise-MPDIoU loss dynamically adjusts to variations in image quality while improving lesion localization accuracy. Third, the lightweight design ensures real-time clinical applicability, requiring only 38.2 MB parameters and 58.5 GFLOPs, while achieving 94.1% accuracy across five macular degeneration categories at 71 FPS. This study establishes a new benchmark for automated OCT-based retinal disease detection, providing both high diagnostic accuracy and practical clinical deployment potential.

Indexed as

Image Interpretation, Computer-AssistedMacular DegenerationTomography, Optical CoherenceAlgorithmsConvolutional Neural NetworksHumansFeature extractionMacular degenerationOptical coherence tomographyReal-time processingTransformer

Identifiers

PMID41184811

DOI10.1186/s12880-025-01990-w

PMCPMC12581524

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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.