Liver Micrometastases area quantification using QuPath and pixel classifier

<strong>Sample</strong>: Mouse (NSG) liver slices with human colorectal cancer cells metastases, stained with Hematoxylin &amp; Eosin. <strong>Image Acquisition</strong>: Images were acquired on an Olympus VS120 Whole Slide Scanner, using a 20x objective (UPLSAPO, N.A. 0.75) and a color camera (Pike F505 Color) with an image pixel size of 0.345 microns. <strong>Image Processing and Analysis</strong>: Obtained images were analyzed using the software QuPath [1] (version 0.3.2) using groovy scripts, making use of a pixel classifier to segment and measure cancer cell clusters. <strong>Files</strong> : <em>Detailed_worflow.pdf</em> : contains a detailed description of how pixel classifier was created <em>images_for_classifier_training.zip</em> : contains all the vsi file obtained from the microscope and used for the training <em>project_for_classifier_training.zip</em> : contains the QuPath project, with Training Image, annotations, classifiers and scripts for analysis <em>PythonCode.txt</em> : code ran to transform output results from QuPath to final results [1] Bankhead, P. et al. <strong>QuPath: Open source software for digital pathology image analysis</strong>. <em>Scientific Reports</em> (2017). https://doi.org/10.1038/s41598-017-17204-5