Abstract:
Tissue sensitive adaptive radar (TSAR) is a non-ionizing, near-field radar imaging technique proposed for the long-term monitoring of breast cancer. Microwave techniques ...Show MoreMetadata
Abstract:
Tissue sensitive adaptive radar (TSAR) is a non-ionizing, near-field radar imaging technique proposed for the long-term monitoring of breast cancer. Microwave techniques inherently have a lower resolution than MRI or X-ray making it important that the TSAR image reconstruction algorithm does not unintentionally introduce further resolution loss. The 3D TSAR image is reconstructed by summing the intensity and voxel-location information encoded in the multiple 1D round-trip time-delay signals reflected from breast features. Decoding requires knowledge of system and patient properties. We have identified differences in the highest intensity voxel location present in TSAR images after summing all decoded antenna time-domain data streams compared to summing a few localized data streams. This potentially can lead to image resolution loss. We propose approaches to determine whether these differences must be accepted as a limit of the current technology and software or whether they can be systematically removed by making minor, but experimentally relevant, empirical changes in system or patient properties. We identified that the consistency improvements in simulated and patient data identified in the empirical study could mainly be accounted for by calculating the transit time between the antenna aperture and feed using AR modeling rather than the current DFT based techniques.
Published in: 2021 32nd Irish Signals and Systems Conference (ISSC)
Date of Conference: 10-11 June 2021
Date Added to IEEE Xplore: 01 July 2021
ISBN Information: