Deep Learning Algorithms for Medical Image Evaluation

Development of software algorithms for the detection of abnormalities in medical images based on Machine Learning

Aim of the project

The aim of this project is to explore software solutions using deep learning technology to achieve automatic, fast and reliable detection of abnormalities (such as cancer) in medical images. The main advantage of this innovation is the development of a generic algorithm to recognize patterns in images, independent of the type of image (CT, MR, etc) or type of abnormality. This allows to use the same software system to solve a multitude of different clinical problems. The goal is not only to quickly identify healthy individuals, but also to detect abnormalities that are not directly linked to the clinical question (incidental findings). By automatically identifying all abnormalities in the images, missing something crucial will be avoided.

Dieses Projekt wird im Rahmen des INTERREG-Programms von der Europäischen Union und den INTERREG-Partnern finanziell unterstützt.

Dit project wordt in het kader van het INTERREG-programma financieel ondersteund door de Europese Unie en de INTERREG-partners.

This project is financially supported by the European Union and the INTERREG-partners as part of the INTERREG programme.


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