Cell segmentation

A workflow combining ImageJ macro and manually using Trainable Weka Segmentation plugin for counting clumped cells.

Segmentation of Golgi.

Sample Images can be found here.

‘’’Squassh’’’ is a tool for 2D and 3D segmentation and quantification of subcellular shapes in fluorescence microscopy images. It provides globally optimal detection and segmentation of objects with constant internal intensity distribution, followed by object-based colocalization analysis. The segmentation computed by Region Competition can optionally correct for the PSF of the microscope, hence providing optimally deconvolved segmentations. Part of the mosaic suite

Image segmentation based on the MOSAIC Discrete region competition algorithm. 

IdentifySecondaryObjects identifies objects (e.g., cells) using objects identified by another module (e.g., nuclei) as a starting point.

Identify objects (as nuclei) within an image without needing the assistance of another cellular feature (as cell). 

NuclearQuant is a QuantCenter module. It is designed for cell nuclei detection and quantification of IHC stained samples. NuclearQuant measures several morphological features besides stain intensity. The cell nuclei classification and the final score are calculated by the intensity score and the proportion score.