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  • ホーム
  • Products
  • 研究・開発
  • 細胞分析
  • Cellular Imaging & Analysis
  • Cellular Imaging Software
  • PhenoLOGIC Machine Learning

PhenoLOGIC Machine Learning

PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC Machine Learning
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC Machine Learning
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC
PhenoLOGIC

PhenoLOGIC™ enables biologists using Harmony to train the software to develop the image analysis algorithms. While other systems may require an image analysis expert to create an algorithm, PhenoLOGIC uses proprietary machine-learning technology to make it easy for you to do it on your own. Using a learn-by-example approach, images can be segmented with just a few clicks of the mouse and then tailored algorithms developed quickly and easily.

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Product variant
Unit Size: 1 each
Part #:
HH12000704
For research use only. Not for use in diagnostic procedures.
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Product information

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Overview

Make creating algorithms easy with PhenoLOGIC

The PhenoLOGIC machine-learning option enables our High Content Analysis software to recognize different cell populations and regions using a simple learn-by-example approach. Just click on a few cells of each class to teach the software what it is looking for, and PhenoLOGIC will do the rest. Image analysis that might have taken hours can be completed in a matter of minutes.

Using advanced proprietary machine-learning technology, PhenoLOGIC sets parameters for optimal image segmentation and cell classification. The software combines the most meaningful parameters, whether it's two, three, four or more, to achieve accurate classification of cells. The result is highly robust and statistically relevant results.

PhenoLOGIC machine learning is available as a software plug-in for the Harmony® High Content Imaging and Analysis Software and the Columbus™ Image Data Management and Analysis System.

Specifications

21CFR Compatible
No
Brand
Phenologic
Unit Size
1 each

Resources

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Deeper insights from your 3D cell model imaging

Researchers are increasingly looking to 3D cell models to bridge the translational gap between 2D cell cultures and in vivo...

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