Liquid based cytology pap smear images for multi-class diagnosis of cervical cancer

While a publicly available benchmark dataset provides a base for the development of new algorithms and comparison of results, hospital-based data collected from the real-world clinical setup is also very important in automated AI-based medical research likewise in disease diagnosis or categorization of predicted disease for tissue level staging or any class identification as per standard protocol so that the developed algorithm works with as much accuracy as possible in the regional context. The repository supports research work related to image segmentation and final classification for a complete decision support system. Liquid based cytology is one of the cervical screening tests. The repository consists of total 963 images sub-divided into four sets of images representing the four classes of pre-cancerous and cancerous lesions of cervical cancer as per standards under The Bethesda System. The pap smear images were captured in 40x magnification using Leica ICC50 HD microscope which is collected and prepared using the liquid-based cytology technique from 460 patients. Microscopic investigation of abnormal changes in cell-level enables detection of malignancy or pre-malignant characteristics. This procedure is time-consuming and subject to inter or intra-observer variability which is why computer-assisted diagnosis can improve the overall disease diagnosis time period to proceed with rapid treatment and therapy which can limit late diagnosis of cervical cancer.

尽管公开基准数据集可为新算法研发与结果比对提供基础支撑，但从真实临床场景采集的院内临床数据，在基于人工智能的自动化医学研究中同样不可或缺：无论是疾病诊断、基于组织分期的预测疾病分类，还是依照标准流程的类别识别，均需依托此类数据，方能让研发的算法在对应区域场景中实现尽可能高的准确率。本数据集仓库面向完整决策支持系统的相关研究，支持图像分割与最终分类方向的科研工作。液基细胞学（Liquid Based Cytology）是宫颈癌筛查的常用手段之一。本仓库共计收录963张图像，依照《贝塞斯达系统》（The Bethesda System）的分类标准，被划分为4组，分别对应宫颈癌的癌前病变与癌性病灶的4个类别。本次采集的巴氏涂片（Pap Smear）图像由徕卡ICC50 HD显微镜以40倍放大倍率拍摄，样本源自460名患者，均采用液基细胞学技术制备。通过显微镜观察细胞水平的异常变化，可检测出恶性或癌前病变特征，但该人工镜检流程耗时较长，且易受观察者间与观察者内部差异的影响，因此计算机辅助诊断能够优化整体疾病诊断流程，缩短诊疗周期，助力快速开展治疗干预，从而降低宫颈癌晚期诊断的概率。