Thyroid Nodule Ultrasound Image Segmentation Based on Improved Swin Transformer
To address the issue of inaccurate segmentation caused by blurred edges and strong noise in thyroid nodule ultrasound images, an image segmentation method based on an improved Swin Transformer is proposed. First, depthwise convolutional layers are integrated into the encoder/decoder of the Swin Tran...
Saved in:
Main Authors: | Yue Wu, Lin Huang, Tiejun Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10847842/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving diagnostic precision in thyroid nodule segmentation from ultrasound images with a self-attention mechanism-based Swin U-Net model
by: Changan Yang, et al.
Published: (2025-02-01) -
Enhancing Thyroid Nodule Detection in Ultrasound Images: A Novel YOLOv8 Architecture with a C2fA Module and Optimized Loss Functions
by: Shidan Wang, et al.
Published: (2025-01-01) -
The role of repeat fine needle aspiration in managing indeterminate thyroid nodules
by: Laura Allen, et al.
Published: (2019-03-01) -
SSMM-DS: A semantic segmentation model for mangroves based on Deeplabv3+ with swin transformer
by: Zhenhua Wang, et al.
Published: (2024-10-01) -
Ultrasound Findings Suggestive of Malignancy in Thyroid Nodules Classified as Follicular Lesion of Undetermined Significance or Follicular Neoplasm based on the 2017 Bethesda System for Reporting Thyroid Cytopathology
by: Heui Jin Jung, et al.
Published: (2025-01-01)