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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
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Real-Time Semantic Segmentation via a Densely Aggregated Bilateral Network.

Shu Yang, Lu Zhang, Shuai Liu

    IEEE Transactions on Neural Networks and Learning Systems
    |November 1, 2023
    PubMed
    Summary

    DAB-Net improves real-time semantic segmentation by enhancing feature extraction in its bilateral streams. This densely aggregated bilateral network (DAB-Net) achieves better accuracy while maintaining high speed for online applications.

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    Area of Science:

    • Computer Vision
    • Deep Learning
    • Image Segmentation

    Background:

    • Real-time semantic segmentation faces a critical speed-accuracy trade-off.
    • Bilateral segmentation networks offer a balance but have limitations in feature extraction.
    • Lightweight backbones and late fusion hinder semantic context and spatial detail aggregation.

    Purpose of the Study:

    • To propose a densely aggregated bilateral network (DAB-Net) for efficient real-time semantic segmentation.
    • To enhance the extraction of semantic context and spatial details in bilateral networks.
    • To improve feature representation for accurate segmentation predictions.

    Main Methods:

    • Introduced a patchwise context enhancement (PCE) module for local semantic context extraction.
    • Designed a context-guided spatial path (CGSP) to encode finer spatial details.
    • Implemented multiple interactions between bilateral branches with a unified decoder for feature fusion.

    Main Results:

    • DAB-Net achieves higher accuracy with minimal speed reduction compared to state-of-the-art methods.
    • The model operates at 31.1 frames per second (FPS) on high-resolution images.
    • Experimental results on three public benchmarks validate the proposed method's effectiveness.

    Conclusions:

    • DAB-Net effectively addresses the limitations of existing bilateral networks for real-time semantic segmentation.
    • The proposed architecture enhances feature representation, leading to improved segmentation performance.
    • DAB-Net offers a promising solution for applications requiring both speed and accuracy.