SLG-Net: Small-Large-Global Feature-Based Multilevel Feature Extraction Network for Ultrasound Image Segmentation

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成果类型：

期刊论文

作者：

Fan, Xinya;Hu, Jianwen;Hu, Kai

通讯作者：

Hu, JW

作者机构：

[Hu, JW; Hu, Jianwen; Fan, Xinya] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.

[Hu, JW; Hu, Jianwen; Fan, Xinya] Changsha Univ Sci & Technol, State Key Lab Disaster Prevent & Reduct Power Grid, Changsha 410114, Peoples R China.

[Hu, Kai] Cent South Univ, Xiangya Hosp, Dept Neurol, Changsha 410008, Peoples R China.

[Hu, Kai] Cent South Univ, Xiangya Hosp, Natl Clin Res Ctr Geriatr Disorders, Changsha 410008, Peoples R China.

通讯机构：

[Hu, JW ] C

Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410114, Peoples R China.

Changsha Univ Sci & Technol, State Key Lab Disaster Prevent & Reduct Power Grid, Changsha 410114, Peoples R China.

语种：

英文

关键词：

Feature extraction;Image segmentation;Transformers;Kernel;Ultrasonic imaging;Convolutional neural networks;Decoding;Fans;Data mining;Computer vision;Ultrasound image segmentation;transformer;large kernel;attention mechanism;convolutional neural network

期刊：

IEEE ACCESS

ISSN：

2169-3536

年：

2025

卷：

页码：

11720-11733

DOI：

10.1109/ACCESS.2025.3528380

基金类别：

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62271087) 10.13039/501100004735-Natural Science Foundation of Hunan Province (Grant Number: 2024JJ5039 and 2023JJ60141) Scientific Research Fund of Hunan Provincial Education Department (Grant Number: 24A0243) 10.13039/501100005089-Changsha Municipal Natural Science Foundation (Grant Number: kq2208403)

机构署名：

本校为第一且通讯机构

院系归属：

电气与信息工程学院

摘要：

Automatic ultrasound image segmentation improves the efficiency of clinical diagnosis and decreases the workload of doctors. Many ultrasound image segmentation methods only focus on capturing local details and global dependencies, whereas ignoring large-scale context information. However, it is essential to extract large-scale context features for large targets in images. To enhance the capability of feature extraction of the model for targets with various sizes and improve segmentation performance, we propose an effective multilevel feature extraction network (SLG-Net) which can extract featu...

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SLG-Net: Small-Large-Global Feature-Based Multilevel Feature Extraction Network for Ultrasound Image Segmentation

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