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About CellTypeAnalyzer...

Quantitative Image Analysis Unit - CNB edited this page Apr 26, 2021 · 4 revisions

This ImageJ or Fiji tool offers automated analysis for fluorescence images of stained cells with two different markers in an objective, reliable, fast and reproducible manner considerably more accurate than with qualitative strategies. Therefore, Cell Type Analyze serves as a powerful tool easily adaptable to solve specific challenges through user-defined parameters for analysis of single 2D bio-images as well as large data sets in batch-mode. For the last few years, researchers can choose from a wide range of open source bio-image packages however, on numerous occasions, researchers do not have these computational proficiency so that Cell Type Analyzer allows automation to analyze specific cell biological processes in a defined region of interest within the image that not need to be a square, but also could be any closed shape. Besides the above-mentioned, a key functionality is that the researcher is going to be guided through a user-friendly wizard-like GUI allowing through each step of the process, setting algorithms for auto-threshold, detection, delineating shapes, quantification or filtering and moreover, visualizing instantaneously, going backwards to re-calibrate initial settings in case of inadequate outputs. Once parameters are adjusted and visually confirmed for single analysis, this methodology is ready to be applied to a large batch providing a robust performance. The user may apply filters based on shape circularity as post-processing actions after detection step for all binary objects whose probability, in this case, is equal for the whole image.In short,Cell Type Analyzer offers a formidable set of tools to manipulate and process multiple image formats currently supported through Bio-Formats providing a solution for quantitative measurements and statistics in sub-cellular structures in fluorescence microscopy images even at challenging situations as very low fluorescence intensities variable signal-to-noise ratio (SNR) or uneven background.

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