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20182022
most citedGasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection

239 citations · 760 across the 11 of their papers we have counts for

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Showing 2021Show all

4 papers · 1 filter

cs.CV2021★ 3 cited

GasHisSDB: A New Gastric Histopathology Image Dataset for Computer Aided Diagnosis of Gastric Cancer

Weiming Hu, Chen Li, Xiaoyan Li +9

Background and Objective: Gastric cancer has turned out to be the fifth most common cancer globally, and early detection of gastric cancer is essential to save lives. Histopatholog…

cs.CV2021★ 3 cited

Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers

Wanli Liu, Chen Li, Md Mamunur Rahamana +8

Cervical cancer is a very common and fatal type of cancer in women. Cytopathology images are often used to screen for this cancer. Given that there is a possibility that many error…

cs.CV2021★ 239 cited

GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection

Haoyuan Chen, Chen Li, Ge Wang +9

In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is proposed for Gastric Histopathological Image Detection (GHID), which enables the automatic…

cs.CV2021★ 1 cited

A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification

Yixin Li, Xinran Wu, Chen Li +7

In the Gastric Histopathology Image Classification (GHIC) tasks, which are usually weakly supervised learning missions, there is inevitably redundant information in the images. The…