Image analysis software module QuantCenter
for digital microscopesvirtual microscopyvisualization

Image analysis software module - QuantCenter - 3DHISTECH Ltd. - for digital microscopes / virtual microscopy / visualization
Image analysis software module - QuantCenter - 3DHISTECH Ltd. - for digital microscopes / virtual microscopy / visualization
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Characteristics

Applications
virtual microscopy, for digital microscopes
Function
image analysis, visualization, AI

Description

QuantCenter is a multiple-module image analysis platform designed for whole-slide quantification in histopathology and molecular pathology. Thanks to its wide range of linkable modules and the ability to create their own image analysis algorithm, QuantCenter provides researchers with maximum flexibility in quantitative image analysis, contributing to world-class research results. The latest available version of QuantCenter is 2.3. Please get in touch with us if you are interested! QuantCenter is intended for use in tissue classification, IHC quantification and molecular pathology. It consists of ten individual modules that can be freely combined for world-class research results: ScriptQuant: A unique tool for maximum flexibility ScriptQuant is a brand-new image analysis module for QuantCenter. It provides a shell for user-created image analysis scripts in Python for maximum flexibility for the research user, enabling them to run their own image analysis algorithms within the QuantCenter framework. Key Features Arbitrary script editor (VS Code by Microsoft is recommended) The user-created script can be saved into a scenario and handled like one Fast visual feedback: write your code and see the results immediately! ScriptQuant can be extended with external libraries (e.g. OpenCV, TensorFlow…) Well-documented API and use case examples ScriptQuant may provide a gateway for 3rd party AI developers Quantification results can be fed back into the 3DHISTECH infrastructure: Storage of quantification results (polygons, objects, regions, measured values) Visualization in SlideViewer as an overlay Statistics and Data visualization
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