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MLSE-Net: Multi-level Semantic Enriched Network for Medical Image Segmentation
Di Gai,Heng Luo,Jing He, Baogang Xie,Pengxiang Su,Zheng Huang,Song Zhang,Zhijun Tu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.9
Medical image segmentation techniques based on convolution neural networks indulge in feature extraction triggering redundancy of parameters and unsatisfactory target localization, which outcomes in less accurate segmentation results to assist doctors in diagnosis. In this paper, we propose a multi-level semantic-rich encoding-decoding network, which consists of a Pooling-Conv-Former (PCFormer) module and a Cbam-Dilated-Transformer (CDT) module. In the PCFormer module, it is used to tackle the issue of parameter explosion in the conservative transformer and to compensate for the feature loss in the down-sampling process. In the CDT module, the Cbam attention module is adopted to highlight the feature regions by blending the intersection of attention mechanisms implicitly, and the Dilated convolution-Concat (DCC) module is designed as a parallel concatenation of multiple atrous convolution blocks to display the expanded perceptual field explicitly. In addition, Multi-Head Attention-DwConv-Transformer (MDTransformer) module is utilized to evidently distinguish the target region from the background region. Extensive experiments on medical image segmentation from Glas, SIIM-ACR, ISIC and LGG demonstrated that our proposed network outperforms existing advanced methods in terms of both objective evaluation and subjective visual performance.
Hui-Xian Yan,Hai-Lian Hong,Lian-Hui Zheng,Heng-Di Su 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.73 No.7
Due to ionic migration and adsorption, an electrical double layer with a thickness scaled by the Debye length is formed at the hydrogel-solution interface. For a thin temperature-pH dual sensitive hydrogel whose chickness is comparable to the Debye length, its mechanical behavior may be affected by the electrical double layer. In this paper, by incorporating electromagnetic field theory into thermodynamic theory, we develop a coupled field theory for a temperature-pH dual sensitive hydrogel, and we take into account the electrical double layer. The proposed model can be used to analyze the in uences of the size effect, ionic concentration, ambient temperature and solution pH value on the swelling of a thin layer of the temperature-pH sensitive hydrogel.