PCA-based artifact removal algorithm for stroke detection using UWB radar imaging

• Published in: Medical & biological engineering & computing Vol. 55; no. 6; pp. 909 - 921
• Main Authors: Ricci, Elisa, di Domenico, Simone, Cianca, Ernestina, Rossi, Tommaso, Diomedi, Marina
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2017; Springer Nature B.V
• Subjects: Algorithms; Ambulances; Backscattering; Beamforming; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Brain; Computational neuroscience; Computer Applications; Data processing; Diagnostic Imaging - methods; Diagnostic systems; Human Physiology; Humans; Imaging; Medical imaging; Microwaves; Neuroimaging; Original Article; Radar - instrumentation; Radar detection; Radar imaging; Radiology; Signal processing; Signal Processing, Computer-Assisted; Stroke; Stroke - diagnosis; Ultrawideband radar; Artifact removal; Brain stroke detection; Microwave UWB radar; PCA
• ISSN: 0140-0118; 1741-0444; 1741-0444
• DOI: 10.1007/s11517-016-1568-8

Stroke patients should be dispatched at the highest level of care available in the shortest time. In this context, a transportable system in specialized ambulances, able to evaluate the presence of an acute brain lesion in a short time interval (i.e., few minutes), could shorten delay of treatment. UWB radar imaging is an emerging diagnostic branch that has great potential for the implementation of a transportable and low-cost device. Transportability, low cost and short response time pose challenges to the signal processing algorithms of the backscattered signals as they should guarantee good performance with a reasonably low number of antennas and low computational complexity, tightly related to the response time of the device. The paper shows that a PCA-based preprocessing algorithm can: (1) achieve good performance already with a computationally simple beamforming algorithm; (2) outperform state-of-the-art preprocessing algorithms; (3) enable a further improvement in the performance (and/or decrease in the number of antennas) by using a multistatic approach with just a modest increase in computational complexity. This is an important result toward the implementation of such a diagnostic device that could play an important role in emergency scenario.