Tongue body positioning and segmentation based on improved TransUNet

Haowei Wang; Tiantian Liang; Yinping Shao

doi:10.1117/12.3033773

13 June 2024 Tongue body positioning and segmentation based on improved TransUNet

Haowei Wang, Tiantian Liang, Yinping Shao

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318021 (2024) https://doi.org/10.1117/12.3033773
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

This paper proposes an improved TransUNet medical image segmentation method for tongue positioning and segmentation to solve the premise of tongue image diagnosis task and the segmentation performance of deep learning network. By introducing efficient multi-scale attention module in the jump connection layer of the network, the image conducts deeper feature extraction and compensate for the spatial information lost by image dimension reduction. At the same time, an improved empty space convolution pooling pyramid is added to the convolutional neural layer of the network to enhance the network perception of the input image while reducing the network training cost. Facing the complex background conditions and a variety of interference problems, the network has excellent performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haowei Wang, Tiantian Liang, and Yinping Shao "Tongue body positioning and segmentation based on improved TransUNet", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318021 (13 June 2024); https://doi.org/10.1117/12.3033773

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KEYWORDS

Image segmentation

Tongue

Feature extraction

Convolutional neural networks

Education and training

Transformers

Data modeling

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