Print Email Facebook Twitter Regularized Least Squares Imaging for High Resolution Ultrasound Title Regularized Least Squares Imaging for High Resolution Ultrasound Faculty Electrical Engineering, Mathematics and Computer Science Department Microelectronics Programme Circuits and Systems Date 2016-09-14 Abstract Traditional imaging techniques in medical ultrasound are mostly based on pre-defined geometrical processing of the measurement data. In this thesis however, we focus on finding the image that would best explain the observed measurement in a least squares sense, given an ultrasound model. This enables the use of prior knowledge such as transducer impulse responses and acoustic wave field theory to be fully taken into account, resulting in a spatio-temporal imaging technique. Since performance is dependent on modeling accuracy, this thesis investigates the formulation and verification of a linear ultrasound model that also takes the transducer lens into account. Additionally, a technique to easily estimate the transducer impulse response is proposed. After defining the linear model, several techniques that solve this linear system for the image are considered, namely Tikhonov regularized least squares, Tikhonov regularized non-negative least squares, basis pursuit de-noising. Using a synthetic aperture transmission scheme, these techniques are compared to delay-and-sum beamforming in both a simulation based resolution analysis, as well as in a real experiment using a high-resolution phantom in water. Results show that the proposed imaging techniques perform significantly better than conventional delay-and-sum beamforming. To reference this document use: http://resolver.tudelft.nl/uuid:70d91e29-e24b-4e31-b701-b2357ffc3a8e Embargo date 2017-09-14 Part of collection Student theses Document type master thesis Rights (c) 2016 Meulen, P.Q. van der Files PDF superresolution-PimvdMeul ... s-v1.1.pdf 807.91 KB Close viewer /islandora/object/uuid:70d91e29-e24b-4e31-b701-b2357ffc3a8e/datastream/OBJ/view