![]() Cell profiler is cost effective software which is beneficial to identify and measure neurons of fundus striati. Results of the present study can be extrapolated to correlate with pathological conditions associated with emotional and behavioral disorders involving fundus striati. Mean Intensity units of neurons of fundus striati as measured by intensity module of Cell profiler was 17.916 pixel units. Using specific modules, neurons and branching points of their neurites in images of fundus striati were measured in pixel units. Neuronal nuclei were identified as primary objects and cytoplasm was identified by the software as secondary objects. Freely downloadable Cell Profiler software was installed, specific pipeline for neuronal assay was drawn, and modules were used to analyze images. A qualitative cross sectional study was done using eighty one images of histological sections of hematoxylin and eosin stained 8µ thick tissue sections of fundus striati. The present study was undertaken to study and analyze images of fundus striati using cell profiler as an automated image analysis technique. A versatile technique to measure neurons of fundus striati is the use of Cell profiler software. One such part of human brain which has been explored in recent years is fundus striati, a part of basal ganglia bridging caudate nucleus and putamen. Strengths: Cells, Neurons, C.Analysis of volumetric and morphological neuronal data has been of keen interest to neurologists and neuroscientists because of its implications in pathological conditions such as schizophrenia, autism, obsessive compulsive disorder etc. CellProfiler is extensible through plugins written in Python or for ImageJ. CellProfiler is structured so that the most general and successful methods and strategies are the ones that are automatically suggested, but the user can override these defaults and pull from many of the basic algorithms and techniques of image analysis to solve harder problems. The researcher creates an analysis pipeline from modules that find cells and cell compartments, measure features of those cells to form a rich, quantitative dataset that characterizes the imaged site in all of its heterogeneity. The percentage of positive nuclei vs total number of nuclei can then be computed using the CalculateMath Module.ĬellProfiler is free, open-source software for quantitative analysis of biological images.ĬellProfiler is designed to enable biologists without training in computer vision or programming to quantitatively measure cell or whole-organism phenotypes from thousands of images automatically. If needed, nuclei can be expanded in order to include touching object rather than object inside only. Nuclei are then filtered according to the property of having histone (positive) or not having histone (negtiveobject) related to them. Then objects (nuclei) are related to the second object (Histone), to create a parent child-relation ship: where nuclei can have histone has child. In a few words, it used the IdentifyPrimaryObject module of CellProfiler to detect nuclei from a channel (e.g DAPI), then again the same module on another channel to detect another probe (e.g some particular histone). This pipeline shows how to do both of these tasks, and demonstrates how various modules may be used to accomplish the same result. CP is commonly used to count cells or other objects as well as percent-positives, by measuring the per-cell staining intensity. This one example workflow from the Cell Profiler(CP) Examples.
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