Difference between revisions of "YeaZ"
| Line 1: | Line 1: | ||
| − | 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-quality segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system. | + | [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-quality segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system. |
[[Image:sgdwiki-yeaz-screenshot.png]] | [[Image:sgdwiki-yeaz-screenshot.png]] | ||
| − | The system contains a Python based application with graphical user interface available on | + | The system contains a Python based application with graphical user interface available on [https://github.com/lpbsscientist/YeaZ-GUI|GitHub], 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 [https://www.nature.com/articles/s41467-020-19557-4|Dietler et al., 2020] |
YeaZ was created at École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland | YeaZ was created at École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland | ||
Please contact [https://www.epfl.ch/labs/lpbs/professor-rahi/ Sahand Jamal Rahi] with questions, or ideas for improvements. | Please contact [https://www.epfl.ch/labs/lpbs/professor-rahi/ Sahand Jamal Rahi] with questions, or ideas for improvements. | ||
Revision as of 11:36, 13 November 2020
[1] 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-quality segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system.
The system contains a Python based application with graphical user interface available on [2], 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.
