Description

Signal processing and machine learning techinques are two powerful frameworks for analyzing signals and developing efficient processing and classification algorithms for bimoedical and industrial applications.

The research acitivity of MAS group is focused on signal analysis and processing methods for ultrasonic diagnosis systems. In the last decades, ultrasound diagnosis methods are receiving increasing attention in modern medical and non destructive test (NDT) procedures, thanks to their cheapness, high portability and non-ionizing radiation.

Computer aids for cancer diagnosis, biomedical image restoration methods, advanced time-frequency analysis techinques for NDT of material, and state of the art signal processing implementation techonolgies (DSP, FPGA, GPU computing) are the main research focus.

Current Projects

---

Ultrasound Image Segmentation and Classification

Information Technology has hugely affected medical imaging, making possible the realization of complex vision systems, like ultrasonography. So far the interpretation of bioimages has always been exclusive responsibility of physicians, but recently computerized schemes have been proposed to highlight from images some important aspects of  biological tissues invisible to human eye. >> More Info

 

Time-Frequency Analysis of NDT signals

In the last years time frequency transformation techniques have acquired a leading role in signal processing. However, such transformations have some restrictive properties which make them not suitable in some applications. In particular, the possibility of generalizing and adaptively varying the time frequency plane tiling is a major demand. >> More Info