PNS-Cyst

<p>Data collected by the PheNeSens (Phenotyping of Nematodes with Sensors) project. The images recorded&nbsp;cysts of sugar beet nematode, together with organic debris from the soil sample, left after the soil processing.</p> <p>All cysts are&nbsp;manually outlined by experts and saved as indexed-PNG images. We used the annotations to train deep neural networks for automatic cyst segmentation in the PheNeSens project.</p> <p>For details of the data collection and deep learning model training, refer to our paper:</p> <p>Chen L, Daub M, Luigs H-G, Jansen M, Strauch M and Merhof D (2022) High-throughput phenotyping of nematode cysts. Front. Plant Sci. 13:965254. doi: 10.3389/fpls.2022.965254 [<a href="https://www.frontiersin.org/articles/10.3389/fpls.2022.965254/full?&amp;utm_source=Email_to_authors_&amp;utm_medium=Email&amp;utm_content=T1_11.5e1_author&amp;utm_campaign=Email_publication&amp;field=&amp;journalName=Frontiers_in_Plant_Science&amp;id=965254">link</a>]</p>