Measuring physiological data outside the lab often requires a compromise: either researchers retain full access to live data and device settings, or participants gain the freedom to move naturally in real-world environments. Seamless Mode Switching...
The collaboration aims to show how researchers can use VisiOmics image data within MIKAIA® workflows for cell segmentation, phenotyping, and spatial analysis. This work supports greater flexibility in downstream analysis, helping laboratories...
Are we already at a point where AI is beginning to understand and shape the physical world? Researchers exploring Embodied AI – aka “intelligence with a body” – are starting to push exactly in that direction. We talked to Thomas Wittenberg, Chief...
The MIKAIA® Cell x Gene App can be used to analyze FISH (or similar, e.g., RNAscope), CISH, or spatial transcriptomics scans, including Xenium by 10x Genomics. For Xenium data in particular, this app is the right choice, supporting three types of...
Chromogenic in situ hybridization (CISH) is used to detect specific DNA or RNA sequences in tissue samples. It uses enzyme-based staining rather than fluorescence (FISH), allowing for high-resolution imaging, quantification, and analysis under...
Welcome to our MIKAIA FAQs. We know that navigating a flexible digital pathology & spatial biology image analysis software like MIKAIA® can raise a lot of questions, and we’re here to help. Whether...
Parkinson’s disease is the second most common neurodegenerative disease after Alzheimer’s, characterized by the progressive loss of nerve cells. As the disease progresses, both motor and non-motor symptoms...
What if your sensor nodes can’t agree on the time? Having all wireless sensor nodes developed and ready for use is an important milestone toward conducting multimodal experiments – but it’s only the beginning. To...
Collecting high-quality physiological data is fundamental to applied research and the broader field of personalized healthcare. Quality data – such as ECG, pulse, EEG, and EMG – is also essential for training AI...
© Fraunhofer IIS · 2026
Markus Jechow
Grit Nickel
Volker Bruns
Yvonne Neß