Data for: Detection of cervical cancer cells based on strong feature CNN-SVM network

1. Due to the large number of pictures, we just selected some of them for display.
2. Original negative sample and Original positive sample are raw data collected from our cooperative unit. We used 100 cervical liquid based cell slides in total, for the sake of simplicity, we have selected a positive and a negative sample for publication, so that you can see the appearance of our raw data which has not been processed.
3. Processed training material are the images which have been processed after binarization, image segmentation and image classification. This folder contains 400 epithelial cells , they are the images of single cells after a series of processes. epithelial cells has been divided into two categories including 200 cancerous epithelial cells and 200 normal epithelial cells, as the names you can see, these are the typical samples we used in the paper.

鉴于图片数量庞大，我们仅从中选取部分进行展示。
原始的负样本与原始的正样本系从我们的合作单位收集的原始数据。总计使用了100张基于宫颈液体的细胞涂片，为简化起见，我们选定了正负样本进行发布，以便您能够观察到未经处理的原始数据的外观。处理过的训练材料是经过二值化、图像分割和图像分类处理后的图像。该文件夹包含400个上皮细胞图像，它们是经过一系列处理后的单个细胞图像。上皮细胞已被划分为两类，包括200个癌细胞上皮细胞和200个正常上皮细胞，正如其名所示，这些是我们论文中使用的典型样本。