A lung nodule segmentation model based on the transformer with multiple thresholds and coordinate attention
Abstract Accurate lung nodule segmentation is fundamental for the early detection of lung cancer. With the rapid development of deep learning, lung nodule segmentation models based on the encoder-decoder structure have become the mainstream research approach. However, during the encoding process, mo...
Saved in:
Main Authors: | Tianjiao Hu, Yihua Lan, Yingqi Zhang, Jiashu Xu, Shuai Li, Chih-Cheng Hung |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-12-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-024-82877-8 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improved lung nodule segmentation with a squeeze excitation dilated attention based residual UNet
by: Dhafer Alhajim, et al.
Published: (2025-01-01) -
Squeeze-and-Excitation Vision Transformer for Lung Nodule Classification
by: Xiaozhong Xue, et al.
Published: (2025-01-01) -
Thyroid Nodule Ultrasound Image Segmentation Based on Improved Swin Transformer
by: Yue Wu, et al.
Published: (2025-01-01) -
An ultrasound image segmentation method for thyroid nodules based on dual-path attention mechanism-enhanced UNet++
by: Peizhen Dong, et al.
Published: (2024-12-01) -
LA-ResUNet: An Efficient Linear Attention Mechanism in ResUNet for the Semantic Segmentation of Pulmonary Nodules
by: P. C. Sarah Prithvika, et al.
Published: (2024-01-01)