Detection of haemorrhagic stroke in simulation and realistic 3-D human head phantom using microwave imaging. (August 2020)

• Record Type: Journal Article
• Authors: Sohani, Behnaz; Khalesi, Banafsheh; Ghavami, Navid; Ghavami, Mohammad; Dudley, Sandra; Rahmani, Amir; Tiberi, Gianluigi
• Is Part Of: Biomedical signal processing and control. Volume 61(2020)
• Publication Date: 2020-08
• Subjects: Microwave imaging -- Brain stroke detection -- Haemorrhagic stroke detection -- Huygens principle; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2020.102001
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A low complexity microwave imaging procedure for brain imaging. A portable detection system for diagnosis of various emergency circumstances. Distinguishing between different tissues for medical imaging applications. Signal processing techniques applicable to several strokes and cancer detection. Detection of the stroke is demonstrated through simulation and measurements. Abstract: This research presents the use and validation of a low complexity microwave imaging procedure for brain imaging, where antennas operate in free-space. In particular, we employ only two microstrip antennas, operating between 1 and 2 GHz for successful detection of the haemorrhagic stroke. Detection is demonstrated through simulation and measurements. Simulations have been performed using an anthropomorphic human head model where a haemorrhagic stroke has been inserted. In addition, multi-bistatic frequency-domain measurements have been performed to collect the transfer function (S21) between the two antennas inside an anechoic chamber using a multi-layered phantom mimicking a human head. Images have been obtained through Huygens principle. To reconstruct the image, subtraction artefact removal method between the data of a healthy head and the data of a head with stroke has been initially employed in simulations. Next, the rotation subtraction artefact removal method has been used both in simulation and in measurements. It has been verified that both artefact removal procedures allow detection.