CellProfiler Activator Full Version

Those who are involved into studying biological processes and use light / fluorescence microscopes for imaging cells and other biological samples could benefit from a tool for analyzing such images. CellProfiler was created in order to provide users with a way of collecting information about the imaged samples. It provides the means for extracting valuable biological data from images in a fast-paced environment, therefore increasing users’ workflow efficiency.

The application comes packed with a clean interface that provides several modules where users can organize their workflow efficiently. One will be able to follow an intuitive analysis sequence, which provides an effective analysis flow: images, metadata, names / types and groups.

Download CellProfiler Crack

Software company
Rank 4
825 4
Crack size ~ 500KB
Downloads total 6488
Systems Win XP 64 bit, Win Vista 64 bit, Win 7 64 bit, Win 8 64 bit

After loading the images that need to be analyzed, people will be able to analyze them, update their information and extract details from their corresponding metadata. In order to improve the work efficiency and flexibility, the application allows users to add several predefined modules for creating their required workflow.

Users will be able to access an impressive array of predefined modules that offer tools for processing the loaded images, classifying objects, creating batch files or measuring correlations and overlaps. After adding the preferred modules, users can easily switch between them by using the dedicated commands.

Advanced users might be happy to know that CellProfiler Keygen also provides a plate viewer and features for visualizing the corresponding histogram, density plots or statistics. Novices are advised to refer to the in-depth documentation that can be accessed on the developer’s website, as this application will require advanced knowledge of biological phenology.

This application addresses those who require a reliable tool for quantifying data from biological images, with the help of a modular and flexible approach. It will deploy several algorithms that are able to accurately identify the cell distribution in images and it will offer people access to an extensive library of predefined image analysis modules.


  • Many bug fixes
  • Improvements to the code behind the input modules to address issues with color image stacks
  • Adding a caching layer to image file handling which should improve performance for image stacks
  • Improving the compositing of overlays on images


Piero, 09 December 2016

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