4 accepted papers
Cervical cytologic whole slide image (WSI) multiple classificaton (grading) is a challenging task. Current studies typically ignore the unbalanced data distribution and require multi-class annotations to learn cell features for WSI grading, which largely suffers from label noise. In this paper, we d…
Convolutional Neural Networks (CNNs) have become the de facto approach for medical image classification in recent years. However, the deficiency of convolutional operations in extracting global features has limited the further improvement of this task. Vision Transformers (ViTs) can model long-range…
Breast cancer histopathological image classification has made great progress with the use of Convolutional Neural Networks (CNNs). However, due to the limited receptive field, CNNs have difficulty in learning the global information of breast cancer histopathological images, hindering the further imp…
The automatic and effective cervical cell classification technique is critical for cervical cytology screening and cervical cancer prevention. We notice that cervical cell classification is a fine-grained classification task. The difference between classes is small while the difference within a clas…