Genfit

Median Technologies

Elton Rexhepaj

John Brozek

Benoit Huet

Pierre Baudot

Jean-Christophe Brisset

Nathalie Degallaix

Nozha Boujemaa

Corinne Ramos

Sébastien Poullot

Benjamin Renoust

A method for performing classification of the severity of at least one liver disease from non-invasive radiographic images is disclosed. The method includes: providing radiographic images of slices of the abdomen of a patient; pre-processing the radiographic images by: segmenting liver and spleen, thus achieving a spleen binary mask and a liver binary mask per slice, and normalizing the images with each other, thus achieving normalized radiographic images per slice; for each slice, from the liver binary mask and the normalized radiographic images, extracting a liver parameter; from at least one spleen binary mask, extracting a spleen parameter; and classifying, in function of both parameters and by help of a trained Machine Learning model, the severity of liver disease between one among a group of liver disease at early stage and a group of liver disease at advanced stage.

Automated pattern recognition and scoring method of fibrosis from non invasive radiology imaging

The present invention relates to a novel automated pattern recognition and scoring method of histological images.

Automated pattern recognition and scoring method of histological images

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Antibes, France

Elton Rexhepaj