FiCRoN, a deep learning-based algorithm for the automatic determination of intracellularparasite burden from fluorescence microscopy images

The FiCRoN automated method dataset provides fluorescence microscopy images from BMDM macrophages (mouse bone marrow-derived macrophages) infected with <i>Leishmania major</i>. When extracting the FiCRoN.zip file, three main folders appear: <b>Training, Validation and Test.</b> Within the first two main folders there are two secondary folders: <b>O</b><b>riginal_images</b> and another folder with <b>A</b><b>nnotation </b>to detect three cell categories, <b>Amastigotes, Infected Macrophages and Total Macrophages</b> compatible with the FiCRoN method. In the main folder <b>Test</b> there are two secondary folders, <b>O</b><b>riginal_images</b> with MOIs different and another folder with <b>Count</b> generated from the <b>manual counting</b> <b>of three experts</b> and the <b>automatic FiCRoN</b> count.<br>