AI-based Image Analysis with MICAIA® 

Digital pathology image analysis software for researchers

 

ParasiteWeb® - Virtual proficiency tests for parasitology

ParasiteWeb® is a web platform for performing virtual EQA (External Quality Assessment) and IQC (Internal Quality Control) for the microscopic detection of parasites in clinical samples.

 

We are your development
partner for medical image
analysis – please contact us.

 

We have a long history in the quantitative evaluation of microscopic images. The first step, though, is to digitize the samples into a Whole Slide Image (WSI). iSTIX® is our low-budget solution for manual Whole-Slide-Imaging. It upgrades your microscope into a scanner.  

Methods

For the analysis we employ

  • “classical” algorithms
  • and increasingly more often AI-based Deep Learning methods.


Workflow

Usually we cooperate with clinical partners.

  1. We jointly view sample images and let our partners explain to us the biological backgrounds as well as the research questions
  2. We then translate the research question into an image analysis problem and design a first algorithm
  3. We jointly discuss and fine-tune the solution, often in multiple iterations


Infrastructure

During the process, we can leverage our high end infrastructure:

  • On-Site Deep Learning Cluster with 72x NVIDIA P100 and 16x P40 GPUs
  • On-Site CPU Cluster with 864 Cores
  • ZEISS Axio Scan.Z1 Slide Scanner for Brightfield and Fluorescence
  • ZEISS Axio Imager 2 Mikroscope for Brightfield and Fluorescence
  • PreciPoint M8 microscope
  • Our SCube® Scanning Platform with support for z-Stacks and high resolution immersion microscopy

Virtual microscopy

 

Press Release

The web platform that makes parasite ­microscopy easier – ParasiteWeb® goes live

 

Fluorescence Microscopy

Analysis of Fluorescence Microscopy Images for Life Science Research

 

Hematology

Optical analysis of blood samples

QSP

Quality Slide Program

It allows the laboratory to assess the ability of prospective examiners to correctly identify individual WBC populations and other identifiable elements.

News

MICAIA® Newsletter

 

Register now for more insights in Digital Pathology.

Live Event Recording

Computational
Pathology Research in
GI Histopathology

PreciPOINT, Fraunhofer IIS

Interview

Volker Bruns with ChatGPT on Digital Pathology

Recording of the BVM workshop 2021

Robust Slide
Cartography in Colon Cancer Histology

Evaluation on a Multi-scanner Database

ParasiteWeb - Demo platform

The online tool for training and quality control of parasite microscopy

 

Online Magazine: #WeKnowHow

Sorting cells

How to recognize the right cells among thousands in a matter of seconds.