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DHR-Net: An Ultra-Lightweight U-Net Based on Efficient Convolutional Attention for Medical Image Segmentation

2025-11-24

Abstract excerpt

Lightweight medical image segmentation models are essential for real-world clinical deployment where computational resources and latency are strictly constrained. However, existing compact architectures often suffer from insufficient feature representation, weak contextual modeling, and performance degradation in complex anatomical structures. To address these limitations, we propose DHR-Net, an ultra-lightweight...

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Radiomics and Machine Learning in Medical Imaging

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Literature Corpus work: f5cdfc13-cb40-587a-a297-ea16fb2c1bcc
DOI: 10.22541/au.176402462.24351269/v1

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