mlsanityData to 14 Oct 2026

Boundary Guided Semantic Learning for Real-time COVID-19 Lung Infection Segmentation System

arXiv 2209.02934 ↗First posted 7 Sep 2022eess.IV cs.CVcited by 11

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Abstract (arXiv)

The coronavirus disease 2019 (COVID-19) continues to have a negative impact on healthcare systems around the world, though the vaccines have been developed and national vaccination coverage rate is steadily increasing. At the current stage, automatically segmenting the lung infection area from CT images is essential for the diagnosis and treatment of COVID-19. Thanks to the development of deep learning technology, some deep learning solutions for lung infection segmentation have been proposed. However, due to the scattered distribution, complex background interference and blurred boundaries, the accuracy and completeness of the existing models are still unsatisfactory. To this end, we propose a boundary guided semantic learning network (BSNet) in this paper. On the one hand, the dual-branch semantic enhancement module that combines the top-level semantic preservation and progressive semantic integration is designed to model the complementary relationship between different high-level features, thereby promoting the generation of more complete segmentation results. On the other hand, the mirror-symmetric boundary guidance module is proposed to accurately detect the boundaries of the lesion regions in a mirror-symmetric way. Experiments on the publicly available dataset demonstrate that our BSNet outperforms the existing state-of-the-art competitors and achieves a real-time inference speed of 44 FPS.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 45 of its 86 references that are in the map. First posted on arXiv 7 Sep 2022.

Builds on

45 of 86 references.

References · 45

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33 more
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Built on by

Cited by year

Citing papers per year: 2022: 4; 2023: 3; 2024: 4.

11 papers.

  1. 2023PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminatorscited by 49
  2. 2022CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detectioncited by 38
  3. 2023Frequency Perception Network for Camouflaged Object Detectioncited by 37
  4. 2024Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attentioncited by 26
  5. 2024Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learningcited by 17
  6. 2022PSNet: Parallel Symmetric Network for Video Salient Object Detectioncited by 12
  7. 2024Query-guided Prototype Evolution Network for Few-Shot Segmentationcited by 12
  8. 2024EAFormer: Scene Text Segmentation with Edge-Aware Transformerscited by 4
  9. 2022Feedback Chain Network For Hippocampus Segmentationcited by 1
  10. 2022Collective Intelligent Strategy for Improved Segmentation of COVID-19 from CTcited by 1
  11. 2023BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer's Diseasecited by 0