Difference between revisions of "YeaZ"

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[https://www.epfl.ch/labs/lpbs/data-and-software/ |YeaZ] is a system for efficiently and accurately segmenting microscopy images of yeast cells. It contains a convolutional neural network, with an underlying training set of high-qual|ty segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system.
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[https://www.epfl.ch/labs/lpbs/data-and-software/ YeaZ] is a system for efficiently and accurately segmenting microscopy images of yeast cells. It contains a convolutional neural network, with an underlying training set of high-qual|ty segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system.
  
 
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[[Image:sgdwiki-yeaz-screenshot.png]]

Revision as of 10:37, 13 November 2020

YeaZ is a system for efficiently and accurately segmenting microscopy images of yeast cells. It contains a convolutional neural network, with an underlying training set of high-qual|ty segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system.

sgdwiki-yeaz-screenshot.png

The system contains a Python based application with graphical user interface available on [1], as well as standalone apps for both Windows and Mac based computers, and training sets. Additional information is available in the accompanying Nature Communications paper by et al., 2020


YeaZ was created at École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland Please contact Sahand Jamal Rahi with questions, or ideas for improvements.