SMART SENSING insights
Just like Stuttgart Public Library, MIKAIA University is a hub for learning.

MIKAIA University

the central MIKAIA® learning portal

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(note: in February 2024 MICAIA was renamed to MIKAIA®)

MIKAIA University is the central MIKAIA® learning portal. Here you can find various app notes and video tutorials that describe typical MIKAIA® workflows either from a technical or medical perspective. The underlying AI technologies are described in our scientific publications. The latest software changes are documented in the MIKAIA® Changelog.

As we are continuously adding more content, please check back frequently or subscribe to the MIKAIA® newsletter, where we announce newly released app notes.

Apps & AIs

MIKAIA® 2.4 (released Sep 2025) includes 20 apps, 10 of which work for both brightfield and fluorescent scans.
The AI Author App and Plug-in your own AI App can be used to develop additional user-specific apps.

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More details, including a description of each app, are available here.
MIKAIA® is for Research Use Only (RUO).

MIKAIA FAQs with Logo printed on a colorful background

Frequently Asked Questions

Navigating a flexible digital pathology and spatial biology image analysis software like MIKAIA® can bring up many questions — perhaps even before you get started. If our FAQs don’t answer your question, don’t hesitate to drop us a line.

First Steps

If you just installed MIKAIA® and want to get started, this blog post will guide you through the essentials: MIKAIA® Introduction & First Steps

MIKAIA First steps visualized by foot prints on the MIKAIA gradient

MIKAIA University App Notes & Concepts

MIKAIA University App Notes are blog articles, where we describe a particular MIKAIA® app or a medical use case in a step-by-step fashion. They illustrate how MIKAIA® can be used to make discoveries or automate quantitative analysis in Digital Pathology & Spatial Biology. Our app notes typically describe what the expected input images look like and what quantitative outputs can be generated. They contain many screenshots and explain the concepts or in some cases even the technical background of the image analysis apps.

We are frequently releasing new app notes. Here are the most recent additions:

mIF cell segmentation
AI gallery

mIF / FL cell segmentation examples

IHC cell quantification
AI gallery

IHC cell analysis examples for various IHC markers and organs.

Overview of spatial analysis capabilities

Videos on all spatial biology analysis apps

MIKAIA® Editions

Don’t worry about selecting which apps you want to purchase. You do not need to select each individual app. Currently, three feature sets are available:

  1. MIKAIA® lite (free)
  2. MIKAIA® studio
  3. MIKAIA® studio + AI App Bundle

If you’d like to try out the MIKAIA® apps on a temporary basis or request a quote, please feel free to email us at mikaia@iis.fraunhofer.de.

Overwiew of MIKAIA apps and their respective edition

User Manual

Download the detailed 100+ pages user manual:

It is also included in the free MIKAIA® installer (download here) and available from within MIKAIA® by clicking “User Manual” in the main “Help” menu.

MIKAIA University Video Tutorials

These and further videos are available in the MIKAIA® YouTube playlist.

Workflow: How to creat a new AI with the AI Author App and then batch-analyze an entire dataset.

Workflow of 3 apps: Detect tumor in colon section. Then classify cells in tumor area. Then compute cell-cell connections and highlight tumor-infiltrating lymphocytes (TILs).
Example workflow of 3 Apps: Train AI to detect mucosa. Then run Crypt AI only in mucosa mask. Then detect cells and group by intra-crypt vs. inter-crypt. View app note.
IHC analysis of murine lung tissue (FoxP3): DAB+ cells are detected and then grouped by inside metastasis vs outside metasis vs in invasive margin. View app note.

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Volker Bruns

Volker is a digital pathology and spatial biology enthusiast with a computer science background. Volker and his team develop commercial image analysis software for digital pathology and offer contract development, as well as image analysis as a service in the life sciences.

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