Difference between revisions of "YeaZ"
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| − | [https://www.epfl.ch/labs/lpbs/data-and-software/ | + | [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. |
[[Image:sgdwiki-yeaz-screenshot.png]] | [[Image:sgdwiki-yeaz-screenshot.png]] | ||
| − | The system contains a Python based application with graphical user interface available on [https://github.com/lpbsscientist/YeaZ-GUI | + | 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. | ||
Latest revision as of 10:38, 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.
The system contains a Python based application with graphical user interface available on 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 Dietler 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.
