Next Article in Journal
Non-Destructive Assessment of Chicken Egg Fertility
Next Article in Special Issue
Brachialis Pulse Wave Measurements with Ultra-Wide Band and Continuous Wave Radar, Photoplethysmography and Ultrasonic Doppler Sensors
Previous Article in Journal
Erratum: Borejko, T., et al. NaviSoC: High-Accuracy Low-Power GNSS SoC with an Integrated Application Processor. Sensors 2020, 20, 1069
Previous Article in Special Issue
Time-Domain Investigation of Switchable Filter Wide-Band Antenna for Microwave Breast Imaging
Article

Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection

1
School of Engineering, London South Bank University, London SE1 0AA, UK
2
UBT-Umbria Bioengineering Technologies, Spin off of University of Perugia, 06081 Assisi, Italy
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(19), 5545; https://doi.org/10.3390/s20195545
Received: 27 August 2020 / Revised: 19 September 2020 / Accepted: 25 September 2020 / Published: 28 September 2020
(This article belongs to the Special Issue Ultra Wideband (UWB) Systems in Biomedical Sensing)
In this paper, we present an investigation of different artefact removal methods for ultra-wideband Microwave Imaging (MWI) to evaluate and quantify current methods in a real environment through measurements using an MWI device. The MWI device measures the scattered signals in a multi-bistatic fashion and employs an imaging procedure based on Huygens principle. A simple two-layered phantom mimicking human head tissue is realised, applying a cylindrically shaped inclusion to emulate brain haemorrhage. Detection has been successfully achieved using the superimposition of five transmitter triplet positions, after applying different artefact removal methods, with the inclusion positioned at 0°, 90°, 180°, and 270°. The different artifact removal methods have been proposed for comparison to improve the stroke detection process. To provide a valid comparison between these methods, image quantification metrics are presented. An “ideal/reference” image is used to compare the artefact removal methods. Moreover, the quantification of artefact removal procedures through measurements using MWI device is performed. View Full-Text
Keywords: microwave imaging; brain stroke detection; portable medical devices; UWB imaging; artefact removal methods; Huygens principle microwave imaging; brain stroke detection; portable medical devices; UWB imaging; artefact removal methods; Huygens principle
Show Figures

Figure 1

MDPI and ACS Style

Sohani, B.; Puttock, J.; Khalesi, B.; Ghavami, N.; Ghavami, M.; Dudley, S.; Tiberi, G. Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection. Sensors 2020, 20, 5545. https://doi.org/10.3390/s20195545

AMA Style

Sohani B, Puttock J, Khalesi B, Ghavami N, Ghavami M, Dudley S, Tiberi G. Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection. Sensors. 2020; 20(19):5545. https://doi.org/10.3390/s20195545

Chicago/Turabian Style

Sohani, Behnaz, James Puttock, Banafsheh Khalesi, Navid Ghavami, Mohammad Ghavami, Sandra Dudley, and Gianluigi Tiberi. 2020. "Developing Artefact Removal Algorithms to Process Data from a Microwave Imaging Device for Haemorrhagic Stroke Detection" Sensors 20, no. 19: 5545. https://doi.org/10.3390/s20195545

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop