融合全局推理和MLP架构的甲状腺结节分割模型

doi:10.16451/j.cnki.issn1003-6059.202207007

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Abstract To address the problems of large noise interference in ultrasound images and variable nodule size and high computational complexity of the existing thyroid nodule segmentation methods, a segmentation model combining global reasoning and multi-layer perception(MLP) architecture is proposed. The model is based on the axial shift MLP module, and hence the interaction between different spatial location features is realized with less computational complexity. The end-to-end global reasoning unit is integrated into the encoder and the global information interaction is conducted based on graph convolutional networks to alleviate the interference of image noise. The pyramid feature layer is introduced into the decoder and multi-scale feature interaction is performed to deal with the problem of variable nodule size. Experimental results on DDIT datasets show that the proposed model yields better performance, and it can be applied to other medical image segmentation task, such as breast nodule segmentation and retinal vessel segmentation.

Key words： Medical Image Segmentation Global Reasoning Multi-layer Perception(MLP) Architecture Pyramid Feature Thyroid Nodule

Received: 18 November 2021

ZTFLH:

TP 391

Fund:Supported by Natural Science Foundation of Shanxi Province(No.201901D111091)

Corresponding Authors: XIE Jun, Ph.D., associate professor. Her research interests include image semantic segmentation and intelligent information processing.

About author:: About Author:LI Binrong, master student. Her research interests include computer vision and medical image processing. LI Gang, Ph.D., associate professor. His research interests include artificial intelligence and visual information processing. XU Xinying, Ph.D., professor. His research interests include computer vision and intelligent control. LAN Zijun, master student. His research interests include deep learning and medical image processing.

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	LI Binrong
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Cite this article:

LI Binrong,XIE Jun,LI Gang等. Thyroid Nodule Segmentation Model Integrating Global Reasoning and MLP Architecture[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(7): 649-660.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202207007 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I7/649

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