Fractal graph convolutional network with MLP-mixer based multi-path feature fusion for classification of histopathological images

作者：

Highlights：

• A novel fractal GCN is proposed for classification of histopathological images.

• FGCN effectively learn multi-level spatial features from histopathological images.

• An MLP-mixer based multi-path feature fusion unit (MMFFU) is developed.

• MMFFU effectively fuses multi-level graph representations in FGCN.

摘要

•A novel fractal GCN is proposed for classification of histopathological images.•FGCN effectively learn multi-level spatial features from histopathological images.•An MLP-mixer based multi-path feature fusion unit (MMFFU) is developed.•MMFFU effectively fuses multi-level graph representations in FGCN.

论文关键词：Histopathological images,Fractal graph convolutional network,Feature fusion,MLP-mixer,Non-local attention

论文评审过程：Received 29 June 2022, Revised 28 August 2022, Accepted 4 September 2022, Available online 10 September 2022, Version of Record 13 September 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118793