Skip to content

Liver diseases

Advance discovery

How does Aiforia enable liver research?

Aiforia’s deep learning AI platform has successfully enabled the automation of a versatile, multi-layered range of analyses in a number of areas and sample types such as in primary sclerosing cholangitis (PSC), non-alcoholic steatohepatitis (NASH), nonalcoholic fatty liver disease (NAFLD), and their related inflammation.
With Aiforia you can automate the detection of relevant regions of interest based on morphology, use external ground-truths to find these regions in precise locations, and visualize the feature of interest.
Watch the video to see how Aiforia Create can be used for consistent and fast quantification of fat accumulation in the liver. 

Solutions

Quantification
  • Fat accumulation and fibrosis amount 
Measurement
  • Of spatial and morphological metrics
  • Distance measurements between fat droplets and portal areas
Segmentation
  • Multi-class segmentation
  • In inflammation and steatosis
  • Of fibrotic Collagen I (IHC), CK7 IHC
  • Tissue architecture, for example: portal areas, hepatocytes, parenchyme, capsule, biliary ducts, veins
Regression
  • Regression models predicting continuous values
  • IHC staining of intensity and other end-points
aiforia use case nelli sjöblom

Deep learning AI enables the investigation of prognostic indicators in primary sclerosing cholangitis. Read the use case here.

Sign up for our newsletter