SMART SENSING insights

AACR 2023 @ Orlando

With over 20.000 in-person registrants from 87 countries, the AACR 2023 annual meeting in Orlando, Florida, was THE PLACE TO BE when it comes to cancer research. For the first time, we exhibited MIKAIA.

Christian Münzenmayer, Julia Hetzel, and Volker Bruns at AACR 2023

Julia Hetzel, Christian Münzenmayer, and I gave many demos and collected lots and lots of positive feedback. Our booth at AACR 2023 was visited by

  • academics,
  • CROs,
  • pharmacologists, and
  • instrument vendors.
impressions from the Fraunhofer IIS booth at AACR 2023

On high demand was the analysis of multiplex immunofluorescence (mIF) slides, including high-plex proteomics scans. The ability to segment cells, classify, and quantify them based on their marker expression, create interactive density heat maps, and even derive statistics on cellular neighborhoods and cell-cell interactions seemed to be exactly what many researchers were looking for. And they were stunned, when we showed them the small laptop that we brought to run MIKAIA.

A close 2nd and 3rd place were the batch analysis of IHC-slides as well as the new AI Authoring App that lets biologists easily and interactively adapt an AI on their own data. They especially appreciated that the AI, which is based on “Few Shot Learning”, only requires a handful of training annotations.

download MIKAIA for free from www.mikaia.ai

Avatar photo

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.

Add comment

Get started now

Download MIKAIA for free from www.mikaia.ai

Don’t miss any news

Sign up now for the MIKAIA newsletter

Get in touch with us

Questions, remarks, feature
requests, project inquiries, …
email us: mikaia@iis.fraunhofer.de

Dr. Volker Bruns
Group Manager
Medical Image Analysis (MIA)
Digital Health and Analytics | Fraunhofer IIS