Example testing images for PFU detection neural network

This is the example testing images used for the paper of "Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning". The data has been compressed into eight zip files from .001 to .008. To access the data, please follow these steps: 1) Download all eight zipped files. 2) Once the download is complete, click on any one of the zipped files to start the extraction process. 3) The extracted files will automatically be organized into one folder.

After extraction, there are three subfolders inside it: 1) Network input: it contained 4 holographic phase images (.mat files) at 12h, 13h, 14h and 15h of incubation for an example postive well and an example negative well. 2) Network output: It contains the network output image (PFU probability map) fot the example postive well and the example negative well. 3) Detection result: It contains the final binary detection result images after thresholding fot the example postive well and the example negative well.

本数据集为论文《无染色式快速定量病毒噬斑：基于无透镜全息术与深度学习》所用的测试示例图像。该数据已被压缩为8个编号从.001至.008的ZIP压缩包。获取数据请遵循以下步骤：1）下载全部8个压缩包；2）下载完成后，点击任意一个压缩包即可启动解压流程；3）解压后的文件将自动整合为一个文件夹。

解压完成后，该文件夹内包含3个子文件夹：
1）网络输入（Network input）：内含1个阳性对照孔与1个阴性对照孔在培养12h、13h、14h、15h时的4幅全息相位图像（.mat格式文件）。
2）网络输出（Network output）：内含1个阳性对照孔与1个阴性对照孔的网络输出图像——噬斑形成单位（Plaque Forming Unit, PFU）概率图。
3）检测结果（Detection result）：内含针对上述阳性对照孔与阴性对照孔，经阈值处理后得到的最终二值化检测结果图像。