Researching | Efficient Multi-Scale Attention Decoding Method for Thyroid Nodule Segmentation Based on SwinTransCAD

Laser & Optoelectronics Progress, Volume. 62, Issue 12, 1237004(2025)

Efficient Multi-Scale Attention Decoding Method for Thyroid Nodule Segmentation Based on SwinTransCAD

Yunpeng Wang¹, Jincao Yao^2,3、***, Dong Xu^2,3、**, and Xiang Hao^1、*

Author Affiliations

¹College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang , China

²Department of Ultrasound, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang , China

³Hangzhou Institute of Medicine, Chinese Academy of Sciences, Hangzhou 310000, Zhejiang , China

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References(16)

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[3] Ahmed M N, Yamany S M, Mohamed N et al. A modified fuzzy C-means algorithm for bias field estimation and segmentation of MRI data[J]. IEEE Transactions on Medical Imaging, 21, 193-199(2002).

[4] Ma J L, Wu F, Zhu J et al. A pre-trained convolutional neural network based method for thyroid nodule diagnosis[J]. Ultrasonics, 73, 221-230(2017).

[5] Mubashar M, Ali H, Grönlund C et al. R2U++: a multiscale recurrent residual U-Net with dense skip connections for medical image segmentation[J]. Neural Computing & Applications, 34, 17723-17739(2022).

[6] Wei C, Ren S H, Guo K T et al. High-resolution swin transformer for automatic medical image segmentation[J]. Sensors, 23, 3420(2023).

[7] Wen X B, Zhao B, Yuan M F et al. Application of multi-scale fusion attention U-Net to segment the thyroid gland on localized computed tomography images for radiotherapy[J]. Frontiers in Oncology, 12, 844052(2022).

[8] Rahman M M, Munir M, Marculescu R. EMCAD: efficient multi-scale convolutional attention decoding for medical image segmentation[C], 11769-11779(2024).

[9] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Computer vision-ECCV 2018, 11211, 3-19(2018).

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[11] Liu Z, Lin Y T, Cao Y et al. Swin Transformer: hierarchical vision transformer using shifted windows[C], 9992-10002(2021).

[12] Cao H, Wang Y Y, Chen J et al. Swin-UNet: U-Net-like pure transformer for medical image segmentation[M]. Computer vision- ECCV 2022 workshops, 13803, 205-218(2023).

[13] Chen L C, Zhu Y K, Papandreou G et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[M]. Computer vision-ECCV 2018, 11211, 833-851(2018).

[14] Chang Z Y, Xu M Y, Wei Y W et al. UNeXt: an efficient network for the semantic segmentation of high-resolution remote sensing images[J]. Sensors, 24, 6655(2024).

[15] Gong H F, Chen J X, Chen G Q et al. Thyroid region prior guided attention for ultrasound segmentation of thyroid nodules[J]. Computers in Biology and Medicine, 155, 106389(2023).

[16] Ding J R, Huang Z C, Shi M D et al. Automatic thyroid ultrasound image segmentation based on U-shaped network[C](2019).

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Yunpeng Wang, Jincao Yao, Dong Xu, Xiang Hao. Efficient Multi-Scale Attention Decoding Method for Thyroid Nodule Segmentation Based on SwinTransCAD[J]. Laser & Optoelectronics Progress, 2025, 62(12): 1237004

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Paper Information

Category: Digital Image Processing

Received: Nov. 11, 2024

Accepted: Dec. 12, 2024

Published Online: Jun. 10, 2025

The Author Email: Jincao Yao (yaojc@zjcc.org.cn), Dong Xu (xudong@zjcc.org.cn), Xiang Hao (haox@zju.edu.cn)

DOI:10.3788/LOP242250

CSTR:32186.14.LOP242250

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology