Detecting Multipath Signals using the Hilbert-Huang Transform in Microwave Breast Imaging

This work explores the potential of using the Hilbert-Huang transform (HHT) to detect and investigate multipath signals in microwave breast imaging. Data from simple simulations with inclusions were analyzed to understand the signal shapes and patterns around an inclusion using the HHT. From these scans, mutlipath signals were detectable from their distinct characteristics in the time-frequency domain. Next, the algorithm was applied to data collected from healthy volunteers. The results showed that the time-frequency characteristics of healthy tissue are consistent across multiple scans and there is potential to isolate and understand inclusion characteristics in time and frequency using the HHT. This demonstrates that the HHT can be used as a powerful tool for understanding the characteristics of and isolating multipath signals. This information can be used to improve the permittivity estimates and tumor detection of these imaging systems.