Preliminary experiments involving a 3D phantom filled with brain tissuemimicking liquid confirm the potential of the technology in imaging a spherical target mimicking a stroke of a radius equal to 1.25 cm.Improve Simulation Times on Large Electronic Structures with Tesla GPUs, CST STUDIO SUITE, and Microway It exploits a differential imaging approach and provides 3D images of the stroke. The device is based on a low-complexity architecture which makes use of a minimum number of properly positioned and designed antennas placed on a helmet. In this paper, a novel prototype is presented and characterized. In particular, the open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period. This work focuses on brain stroke imaging via microwave technology.
In addition, we show that the MM can improve the transceivers’ ability to detect useful “weak” signals when incorporated in a headband scanner for brain imaging by increasing the signal difference from a blood-like dielectric target introduced into the brain volume.
We show that the MM can enhance the penetration of the transmitted signals into the human head when placed in contact with skin tissue, acting as an impedance-matching layer. The proposed metasurface is incorporated in different setups, and its interaction with EM waves is studied both experimentally and by using CST Microwave Studio R and is compared to a “no MM” case scenario. We present an approach to enhance microwave brain imaging with an innovative metamaterial (MM) planar design based on a cross-shaped split-ring resonator (SRR-CS). Feasibility Study of Enhancing Microwave Brain Imaging Using MetamaterialsĮ.
Moreover, the prototype can differentiate between haemorrhagic and ischemic strokes based on the estimation of their dielectric properties. Ourresultsdemonstratethatweareabletodetectthestroketargetinscenarios where the initial guess of the inverse problem is only an approximation of the true experimental phantom. 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. 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. 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. Experimental Validation of Microwave Tomography with the DBIM-TwIST Algorithm for Brain Stroke Detection and Classification.The results show the efficiency of our design compared to state-of-the-art implementations on GPUs, many-core CPUs, and other FPGA approaches in terms of resource usage, execution time and power consumption. The flexibility of our design allows us to use it for different FPGA targets, with flexible input data dimensions, and it also lets us easily switch from a more accurate floating-point implementation to a higher speed fixed-point solution. Several HLS optimization strategies are adopted to create an efficient hardware. In order to make the internal PCA computations more efficient, a new block-streaming method is also introduced. In this paper we propose a flexible PCA hardware accelerator in Field-Programmable Gate Arrays (FPGA) that we designed entirely in HLS. Although the hardware design flow can be optimized using High Level Synthesis (HLS) tools, efficient high-performance solutions for complex embedded systems still require careful design. The computational complexity of PCA has made the hardware acceleration of PCA an active research topic in recent years. Principal Component Analysis (PCA) is a technique for dimensionality reduction that is useful in removing redundant information in data for various applications such as Microwave Imaging (MI) and Hyperspectral Imaging (HI). High level design of a flexible PCA hardware accelerator using a new block-streaming method.