MLU-Net: A Multi-Level Lightweight U-Net for Medical Image Segmentation Integrating Frequency Representation and MLP-Based Methods

MLU-Net: A Multi-Level Lightweight U-Net for Medical Image Segmentation Integrating Frequency Representation and MLP-Based Methods

Medical image segmentation is a challenging and popular task in the field of medical image processing in recent decades. Most of the current mainstream segmentation networks are based on convolutional neural networks (CNNs) methods. Among them, encoding and decoding structures based on U-Net archite...

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Bibliographic Details
Main Authors: Liping Feng, Kepeng Wu, Ziyi Pei, Tengfei Weng, Qi Han, Lun Meng, Xin Qian, Hongxiang Xu, Zicheng Qiu, Zhong Li, Yuan Tian, Guanzhong Liang, Yaojun Hao
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Medical image segmentation
convolution neural networks
frequency representation
MLP-based
brain tumor segmentation
computer-aided diagnosis
Online Access:https://ieeexplore.ieee.org/document/10423278/

Internet

https://ieeexplore.ieee.org/document/10423278/

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