The increasing prevalence of brain tumors necessitates the development of advanced diagnostic techniques to enhance detection and characterization. This paper presents innovative methodologies for designing and optimi...
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Microwave imaging systems for medical applications have been widely investigated in recent years due to their potential to provide portable diagnostic tools that are safe, low cost, and nonionizing. Among many medical...
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Microwave imaging systems for medical applications have been widely investigated in recent years due to their potential to provide portable diagnostic tools that are safe, low cost, and nonionizing. Among many medical applications, brain stroke detection and classification using microwave techniques has been attracting an increasing interest due to the need for a portable onsite, real-time stroke diagnosis that can be used by paramedics. A complete microwave imaging system includes hardware components and software algorithms. The processing and imaging techniques, which are the topic of this thesis, use the collected microwave signals via the antenna array to generate the images of the brain. Numerous microwave imaging techniques applied on bio-medical applications have been researched during recent years. Those proposed techniques exhibited great potential, however, they suffer from several serious drawbacks that need to be solved. This thesis aims to solve four main problems (including a large number of antenna elements, a large number of frequency samples, sensitivity to initial guess of the effective dielectric properties of the image domain and sparsity of the imaged domain), in current microwave imaging techniques and in doing so makes four main research contributions. The first contribution is the development of a novel algorithm based on compressive sensing (CS). The main target is to develop CS-based imagingalgorithm to reduce the number of antennas used in the array. A CS model is constructed based on confocal imaging algorithm, and a convex optimization problem is solved in order to reconstruct the reflection coefficients of the imaging domain. The proposed algorithm is successfully tested on a head model. Followed by that, another CS-based algorithm is proposed to reduce the number of stepped frequencies used in the microwave transceiver system. A CS model is constructed based on the sparse time domain signal received by the antenna array. The algorithm
CMOS equivalent-time sampling circuits for impulse-radio ultra-wideband (IR-UWB) breast cancer detection system was developed. The minimum phase resolution of 9.77 ps and the sampling rate of 102.4 GS/s were achieved ...
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ISBN:
(纸本)9781479932825
CMOS equivalent-time sampling circuits for impulse-radio ultra-wideband (IR-UWB) breast cancer detection system was developed. The minimum phase resolution of 9.77 ps and the sampling rate of 102.4 GS/s were achieved for Gaussian monocycle pulses (GMP) with the pulse width of 210 ps. The input analog GMP was converted to digital data by use of a 4-bit analog-to-digital circuit. Target phantom images were reconstructed by confocal imaging algorithm.
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