Cervical cancer is one of the most common cancers in daily life. Early detection and
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …

Cervical cancer remains a significant health concern worldwide, where precise
segmentation of cervical lesions is integral for effective diagnosis and treatment planning …

Integration of whole slide imaging (WSI) and deep learning technology has led to significant
improvements in the screening and diagnosis of cervical cancer. WSI enables the …

Vulvovaginal candidiasis (VVC) is the most prevalent human candidal infection, estimated to
afflict approximately 75% of all women at least once in their lifetime. It will lead to several …

Deep learning has been instrumental in improving the accuracy of cervical cancer screening
using whole-slide images (WSIs) in recent years. Due to the complexity of the computer …

Cervical cancer is a significant health burden worldwide, and computer-aided diagnosis
(CAD) pipelines have the potential to improve diagnosis efficiency and treatment outcomes …

Automated detection of cervical abnormal cells from Thin-prep cytologic test (TCT) images is
crucial for efficient cervical abnormal screening using computer-aided diagnosis systems …

Background and objectives: Graph neural network (GNN) has been extensively used in
histopathology whole slide image (WSI) analysis due to the efficiency and flexibility in …

Cervical cytologic whole slide image (WSI) multiple classificaton (grading) is a challenging
task. Current studies typically ignore the unbalanced data distribution and require multi …

We propose a novel three-stage Transformer-based methodology for entire cytopathological
whole slide image (WSI) classification. The key idea is to leverage Transformer to extract the …