Recovering CT score from Ultrasound for Sarcopenia disease

Sarcopenia is a disease involving muscle loss that is currently assesed via CT scan. The ultimate scope of this project is to develop a machine diagnosing Sarcopenia disease with low-cost and non-invasive techniques. To this aim the project required to build ad hoc acquisition machines based on Ultrasounds, in order to get RF data and B-mode imaging.  Both data modalities have been investigated as input for an AI-based algorithm. This algorithm is trained to perform a regression problem predicting the CT score. 

Partner: Flair Bit (Genoa, Italy), Esaote (Genoa, Italy), Akronos (Genoa, Italy), ICS Maugeri (Milan, Italy).  

FESR Liguria