Biology subjects

Kohlheyer, D.

Publications and source records attributed to Kohlheyer, D..

3 recordsLinked to original sources

bioRxiv2022

ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud

SummaryReliable deep learning segmentation for microfluidic live-cell imaging requires comprehensive ground truth data. ObiWan-Microbi is a microservice platform combining the strength of state-of-the-art technologies into a unique integrated workflow for data management and efficient ground truth generation for instance segmentation, empowering collaborative semi-automated image annotation in the cloud. Availability and ImplementationObiWan-Microbi is open-source and available under the MIT license at https://github.com/hip-satomi/ObiWan-Microbi, along documentation and usage examples. Contactk.noeh@fz-juelich.de Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2022

microbeSEG: Accurate Cell Segmentation with OMERO Data Management

In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their development. The key to analyzing acquired data is accurate and automated cell segmentation at the single-cell level. Therefore, we present microbeSEG, a user-friendly Python-based cell segmentation tool with a graphical user interface and OMERO data management. microbeSEG utilizes a state-of-the-art deep learning-based segmentation method and can be used for instance segmentation of a wide range of cell morphologies and imaging techniques, e.g., phase contrast or fluorescence microscopy. The main focus of microbeSEG is a comprehensible, easy, efficient, and complete workflow from the creation of training data to the final application of the trained segmentation model. We demonstrate that accurate cell segmentation results can be obtained within 45 minutes of user time. Utilizing public segmentation datasets or pre-labeling further accelerates the microbeSEG workflow. This opens the door for accurate and efficient data analysis of microbial cultures.

bioinformatics↗

bioRxiv2022

Reliable cell retention of mammalian suspension cells in microfluidic cultivation chambers

We present a new microfluidic trapping concept to retain randomly moving suspension cells inside a cultivation chamber. In comparison to previously published complex multilayer structures, we achieve cell retention by a thin PDMS barrier, which can be easily integrated into various PDMS-based cultivation devices. Cell loss during cultivation is effectively prevented while diffusive media supply is still ensured.

bioengineering↗