Transmission light microscopy

Fiji plugin to segment oocyte and zona pellucida contours from transmitted light images and extract hundreds of morphological features to describe numerically the oocyte. Segmentation is based on trained neural networks (U-Net) that were trained on both mouse and human oocytes (in prophase and meiosis I) acquired in different conditions. They are freely avaialable on the github repository and can be retrained if necessary. Oocytor also have options to extract hundreds of morphological/intensity features to characterize manually the oocyte (eg perimeter, texture...). These features can also be used in machine learning pipeline for automatic phenotyping.

OligoMacro Toolset, is an ImageJ macro-toolset aimed at isolating oligodendrocytes from wide-field images, tracking isolated cells, characterizing processes morphology along time, outputting numerical data and plotting them. It takes benefit of ImageJ built-in functions to process images and extract data, and relies on the R software in order to generate graphs.