Journal
SENSORS
Volume 20, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/s20030840
Keywords
microwave tomography; stroke detection; DBIM
Funding
- EMERALD project - European Union's Horizon 2020 research and innovation programme under the Marie Skodowska-Curie [764479]
- Innovate UK [103920]
- Engineering and Physical Sciences Research Council [EP/R013918/1]
- EPSRC [EP/R013918/1] Funding Source: UKRI
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We present an initial experimental validation of a microwave tomography (MWT) prototype for brain stroke detection and classification using the distorted Born iterative method, two-step iterative shrinkage thresholding (DBIM-TwIST) algorithm. The validation study consists of first preparing and characterizing gel phantoms which mimic the structure and the dielectric properties of a simplified brain model with a haemorrhagic or ischemic stroke target. Then, we measure the S-parameters of the phantoms in our experimental prototype and process the scattered signals from 0.5 to 2.5 GHz using the DBIM-TwIST algorithm to estimate the dielectric properties of the reconstruction domain. Our results demonstrate that we are able to detect the stroke target in scenarios where the initial guess of the inverse problem is only an approximation of the true experimental phantom. Moreover, the prototype can differentiate between haemorrhagic and ischemic strokes based on the estimation of their dielectric properties.
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