Title: Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening Show Chinese title

Title: 渐进式注意力引导用于全片外阴阴道念珠菌病筛查

Abstract: 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 symptoms including pruritus, vaginal soreness, and so on. Automatic whole slide image (WSI) classification is highly demanded, for the huge burden of disease control and prevention. However, the WSI-based computer-aided VCC screening method is still vacant due to the scarce labeled data and unique properties of candida. Candida in WSI is challenging to be captured by conventional classification models due to its distinctive elongated shape, the small proportion of their spatial distribution, and the style gap from WSIs. To make the model focus on the candida easier, we propose an attention-guided method, which can obtain a robust diagnosis classification model. Specifically, we first use a pre-trained detection model as prior instruction to initialize the classification model. Then we design a Skip Self-Attention module to refine the attention onto the fined-grained features of candida. 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. Our experimental results demonstrate that our framework achieves state-of-the-art performance. Code and example data are available at https://github.com/cjdbehumble/MICCAI2023-VVC-Screening. Show Chinese abstract

Abstract: 外阴阴道念珠菌病（VVC）是最常见的人类念珠菌感染，估计约有75%的女性在其一生中至少会患一次。 它会导致瘙痒、阴道疼痛等多种症状。 由于疾病控制和预防的巨大负担，对全片图像（WSI）分类的需求非常迫切。 然而，由于标记数据稀缺且念珠菌具有独特属性，基于WSI的计算机辅助VVC筛查方法仍然空白。 由于其独特的细长形状、空间分布比例较小以及与WSI的风格差异，传统的分类模型难以捕捉WSI中的念珠菌。 为了使模型更容易关注念珠菌，我们提出了一种注意力引导的方法，可以得到一个鲁棒的诊断分类模型。 具体来说，我们首先使用预训练的检测模型作为先验指导来初始化分类模型。 然后设计了一个Skip Self-Attention模块，以细化对念珠菌细粒度特征的关注。 最后，我们使用对比学习方法缓解了WSI风格差异引起的过拟合，并抑制了对假阳性区域的关注。 我们的实验结果表明，我们的框架达到了最先进的性能。 代码和示例数据可在https://github.com/cjdbehumble/MICCAI2023-VVC-Screening获取。