AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images
Recent MLP-Mixer has a good ability to handle long-range dependencies, however, to have a good performance, one requires huge data and expensive infrastructures for the pre-training process. In this study, we proposed a novel model for nuclei image segmentation namely Axial Convolutional-MLP Mixer,...
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| Format: | Article |
| Language: | English |
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The University of Danang
2024-12-01
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| Series: | Tạp chí Khoa học và Công nghệ |
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| Online Access: | https://jst-ud.vn/jst-ud/article/view/9327 |
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| _version_ | 1850192475534131200 |
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| author | Nguyen Thanh Thu Dinh Binh Duong Tran Thi Thao Pham Van Truong |
| author_facet | Nguyen Thanh Thu Dinh Binh Duong Tran Thi Thao Pham Van Truong |
| author_sort | Nguyen Thanh Thu |
| collection | DOAJ |
| description | Recent MLP-Mixer has a good ability to handle long-range dependencies, however, to have a good performance, one requires huge data and expensive infrastructures for the pre-training process. In this study, we proposed a novel model for nuclei image segmentation namely Axial Convolutional-MLP Mixer, by replacing the token mixer of MLP-Mixer with a new operator, Axial Convolutional Token Mix. Specifically, in the Axial Convolutional Token Mix, we inherited the idea of axial depthwise convolution to create a flexible receptive field. We also proposed a Long-range Attention module that uses dilated convolution to extend the convolutional kernel size, thereby addressing the issue of long-range dependencies. Experiments demonstrate that our model can achieve high results on small medical datasets, with Dice scores of 90.20% on the GlaS dataset, 80.43% on the MoNuSeg dataset, and without pre-training. The code will be available at https://github.com/thanhthu152/AC-MLP. |
| format | Article |
| id | doaj-art-221d48bd385449efb8e9c4e7c18cdfff |
| institution | OA Journals |
| issn | 1859-1531 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | The University of Danang |
| record_format | Article |
| series | Tạp chí Khoa học và Công nghệ |
| spelling | doaj-art-221d48bd385449efb8e9c4e7c18cdfff2025-08-20T02:14:32ZengThe University of DanangTạp chí Khoa học và Công nghệ1859-15312024-12-01646910.31130/ud-jst.2024.332E9321AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological imagesNguyen Thanh Thu0Dinh Binh Duong1Tran Thi Thao2Pham Van Truong3School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, VietnamSchool of Electrical and Electronic Engineering, Hanoi University of Science and Technology, VietnamSchool of Electrical and Electronic Engineering, Hanoi University of Science and Technology, VietnamSchool of Electrical and Electronic Engineering, Hanoi University of Science and Technology, VietnamRecent MLP-Mixer has a good ability to handle long-range dependencies, however, to have a good performance, one requires huge data and expensive infrastructures for the pre-training process. In this study, we proposed a novel model for nuclei image segmentation namely Axial Convolutional-MLP Mixer, by replacing the token mixer of MLP-Mixer with a new operator, Axial Convolutional Token Mix. Specifically, in the Axial Convolutional Token Mix, we inherited the idea of axial depthwise convolution to create a flexible receptive field. We also proposed a Long-range Attention module that uses dilated convolution to extend the convolutional kernel size, thereby addressing the issue of long-range dependencies. Experiments demonstrate that our model can achieve high results on small medical datasets, with Dice scores of 90.20% on the GlaS dataset, 80.43% on the MoNuSeg dataset, and without pre-training. The code will be available at https://github.com/thanhthu152/AC-MLP.https://jst-ud.vn/jst-ud/article/view/9327depthwise convolutionmlp-mixernuclei segmentationtoken mixing |
| spellingShingle | Nguyen Thanh Thu Dinh Binh Duong Tran Thi Thao Pham Van Truong AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images Tạp chí Khoa học và Công nghệ depthwise convolution mlp-mixer nuclei segmentation token mixing |
| title | AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images |
| title_full | AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images |
| title_fullStr | AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images |
| title_full_unstemmed | AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images |
| title_short | AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images |
| title_sort | ac mlp axial convolution mlp mixer for nuclei segmentation in histopathological images |
| topic | depthwise convolution mlp-mixer nuclei segmentation token mixing |
| url | https://jst-ud.vn/jst-ud/article/view/9327 |
| work_keys_str_mv | AT nguyenthanhthu acmlpaxialconvolutionmlpmixerfornucleisegmentationinhistopathologicalimages AT dinhbinhduong acmlpaxialconvolutionmlpmixerfornucleisegmentationinhistopathologicalimages AT tranthithao acmlpaxialconvolutionmlpmixerfornucleisegmentationinhistopathologicalimages AT phamvantruong acmlpaxialconvolutionmlpmixerfornucleisegmentationinhistopathologicalimages |