Gaze-DETR: Using Expert Gaze to Reduce False Positives in Vulvovaginal Candidiasis Screening

1 code implementation • 15 May 2024 • Yan Kong, Sheng Wang, Jiangdong Cai, Zihao Zhao, Zhenrong Shen, Yonghao Li, Manman Fei, Qian Wang

Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse distribution and visually ambiguous characteristics pose significant challenges for accurate identification by pathologists and neural networks alike.

Two-stage Cytopathological Image Synthesis for Augmenting Cervical Abnormality Screening

no code implementations • 22 Feb 2024 • Zhenrong Shen, Manman Fei, Xin Wang, Jiangdong Cai, Sheng Wang, Lichi Zhang, Qian Wang

In the first Global Image Generation stage, a Normal Image Generator is designed to generate cytopathological images full of normal cervical cells.

Cell Detection Data Augmentation +1

Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening

2 code implementations • 6 Sep 2023 • Jiangdong Cai, Honglin Xiong, Maosong Cao, Luyan Liu, Lichi Zhang, Qian Wang

Finally, we use a contrastive learning method to alleviate the overfitting caused by the style gap of WSIs and suppress the attention to false positive regions.

Classification Contrastive Learning