3DHISTECH Releases QuantCenter™ with Unique Image Analysis Module

QuantCenter™ is 3DHISTECH’s multiple-module image analysis platform designed for whole-slide quantification in histopathology and molecular pathology. Thanks to its wide range of modules, QuantCenter™ provides researchers with maximum flexibility.

QuantCenter™ is 3DHISTECH’s multiple-module image analysis platform designed for whole-slide quantification in histopathology and molecular pathology. Thanks to its wide range of optional modules, QuantCenter™ provides researchers with maximum flexibility in quantitative image analysis, contributing to world-class research results. What’s more, QuantCenter™’s modules can be linked for multi-level analysis.

3DHISTECH is proud to announce the release of QuantCenter™ version 2.3 on June 3, 2021 with the following key new features:

ScriptQuant™: New image analysis module for maximum flexibility

ScriptQuant™ 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.

Its key features include

• 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:

o Storage of quantification results (polygons, objects, regions, measured values)

o Visualization in 3DHISTECH’s SlideViewer™ slide viewing application as an overlay

o Statistics and Data visualization

PatternQuant™ Plus: Image analysis for complex tissue segmentation projects

PatternQuantTM Plus is an improved alternative to the existing PatternQuantTM image analysis module – intended for use on more challenging samples (low visual difference between the staining of tissue types within the sample) and for complex tissue segmentation projects when thorough training using deep learning on multiple slides is needed. PatternQuantTM Plus can analyze both fluorescent and brightfield slides.

Its key features include

• Faster and more accurate tissue segmentation even in case of weak contrast and problematic staining

• Option for training on multiple slides

• Multiple classification features