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...
This MIKAIA® University app note demonstrates how to quickly and interactively train your own AI using just a few training annotations, all in a matter of minutes. In the app center, select the Segmentation AI Author App, click “+” to...
This MIKAIA® University app note illustrates how to interactively train a new H&E segmentation AI with serial sections, without having to annotate tumor regions. Instead, an IHC epithelial marker (pan-cytokeratin AE1/AE3) is thresholded through...
Common category to topics from Digital Pathology, Computational Pathology, Spatial Biology as well as applications and technologies left and right.
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...
This MIKAIA® University app note demonstrates how to quickly and interactively train your own AI using just a few training annotations, all in a matter of minutes. In the app center, select the Segmentation AI Author...
This MIKAIA® University app note illustrates how to interactively train a new H&E segmentation AI with serial sections, without having to annotate tumor regions. Instead, an IHC epithelial marker (pan-cytokeratin...
With the upcoming MIKAIA® 3 release (scheduled for Q1 2026), MIKAIA® will receive a new multi-omics slide alignment module, “MIKAIA® Slide Align“. Based on a 3-phase registration process, the last one being...
Spatial Proteomics was named the Nature Method of the Year 2024. One predominant method is Cyclic Immunofluorescence (CycIF). Here, a tissue sample is stained and scanned during a first cycle. Next, the stain is...
With 1,150 participants from over 60 countries, the first edition of the ESMO AI & Digital Oncology meeting was an inspiring kick-off for knowledge sharing and building connection building at the intersection of...
The “Divide by ROIs” feature in MIKAIA’s analysis apps enables users to compile statistics and enhance their understanding of variations in cell populations. This functionality allows for comparisons between user...
The IHC Cell Detection App features a universal subcellular IHC cell AI that is compatible with a wide range of markers, tissues, and cell types. Our 23-minute video tutorial guides MIKAIA® step by step through the app...
This gallery highlights MIKAIA's mIF Cell Segmentation in the FL Cell Analysis App, featuring various examples and an overview of the AI's three segmentation modes and various cell typing options.
New to MIKAIA®? This blog post is here to help you get started on your first steps.
© Fraunhofer IIS · 2026
Volker Bruns
Michaela Benz
Grit Nickel