Linux

ImageJ macro script to streamline the original NMJ-morph methodology doi:10.1098/rsob.160240
Also requires Binary Connectivity https://blog.bham.ac.uk/intellimic/g-landini-software/ 

Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use. They excel at object detection, tracking, instance segmentation, image classification, and pose estimation tasks.

SNT is ImageJ’s framework for tracing, visualization, quantitative analyses and modeling of neuronal morphology. For tracing, SNT supports modern multidimensional microscopy data, semi-automated and automated routines, and options for editing traces. For data analysis, SNT features advanced visualization tools, access to all major morphology databases, and support for whole-brain circuitry data.

Big-FISH is a python package for the analysis of smFISH images (2D/3D). It includes various methods to analyze microscopy images, such spot detection and segmentation of cells and nuclei.

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.