Visualization and co-registration of correlative microscopy data with the ImageJ plug-in Correlia.

Correlative microscopy experiments require the co-registration of the image data acquired by different micro-analytical techniques. Major challenges are the potentially very different fields-of-view and resolutions as well as the multi-modality of the data. To provide microscopists with an easy-to-use software for two-dimensional image co-registration we have developed Correlia, an open source software based on ImageJ/Fiji, which is fully tailored for the registration of multi-modal microscopy data.

Optimization of the Mainzelliste software for fast privacy-preserving record linkage.

Background: Data analysis for biomedical research often requires a record linkage step to identify records from multiple data sources referring to the same person. Due to the lack of unique personal identifiers across these sources, record linkage relies on the similarity of personal data such as first and last names or birth dates. However, the exchange of such identifying data with a third party, as is the case in record linkage, is generally subject to strict privacy requirements.

Correlia: an ImageJ plug-in to co-register and visualise multimodal correlative micrographs.

The correlation of different microscopic imaging techniques alongside with microanalytical methods is crucial to better understand biological processes on a subcellular level. For that, micrographs and chemical maps exhibiting both, very different spatial resolution and field-of-view but also a highly multimodal content has to be co-registered. We developed the ImageJ/Fiji plug-in Correlia that provides an environment for handling multimodal correlative microscopy data.