Two-Dimensional Blood Flow Estimation in the Brain with Ultrafast Ultrasound

Detailed imaging of blood flow may improve the understanding of brain functions. The state-of-the-art non-invasive flow imaging of the brain is limited to a one-dimensional Doppler setting. We propose a method to estimate the two-dimensional flow vector in the fine vascular network of the brain by using a speckle tracking technique. The...

Active Semi-Supervised Learning For Diffusions on Graphs

In statistical learning over large data-sets, labeling all points is expensive and time-consuming. Semi-supervised classification allows learning with very few labels. Naturally, selecting a few points to label becomes crucial as the performance relies heavily on the labeled points. The motivation behind active learning is to build an optimal...

Calibration of a Single element ultrasound transducer using an aberration mask

Previous work [1] has demonstrated the possibility of high resolution imaging through the use of a single element and a aberration mask. This thesis will expand on the previous work by examining the proposed method for errors in the creation of the model. The analysis is preformed by examining the various aspects of the measurements setup and...

Improving Ultrafast Doppler Imaging using Subspace Tracking

High frame rate Doppler ultrasound imaging provides a new way to image blood motion at thousands of frames per second. It has gained popularity due to its high spatio-temporal resolution, which is re- quired to distinguish blood motion from clutter signals caused by slow moving tissue. Since the flow of blood inside the brain is coupled to...

An Investigation of the Medical Ultrasound Image Sparse Spaces used for the Model-Based Imaging

In this thesis, we investigate a sparse basis for ultrasound images, so that we can use sparse regularization in imaging. Actually, there are few previous researches explicitly demonstrating that medical ultrasound images can be sparsified for some dictionary. We consider various orthogonal transforms such as wavelet transforms, cosine...

Frequency selection for indoor ranging using compressive sensing

Nowadays, indoor ranging and localization have become necessary in daily life. Due to the multi-path propagation and noise in the indoor environment, phase domain ranging method using multi-frequency has been proposed which achieves accurate estimation of indoor target. However, as the indoor communication is usually carried on Bluetooth Low...

Phase Domain Ranging for Narrowband ISM Radio Bands

In this thesis, we study ranging algorithms in an indoor environment using narrow-band industrial, scientific, and medical (ISM) radio bands at 2.4 GHz. Previously, a phase difference approach implemented for this problem. However, the distance estimation is rather inaccurate for indoor ranging, mainly due to multipath and noise. This thesis...

Multidomain Graph Signal Processing: Learning and Sampling

In this era of data deluge, we are overwhelmed with massive volumes of extremely complex datasets. Data generated today is complex because it lacks a clear geometric structure, comes in great volumes, and it often contains information from multiple domains. In this thesis, we address these issues and propose two theoretical frameworks to handle...

Performance and Complexity of Data Acquisition in Compressive-sensing Radar

Compressive Sensing (CS) provides a new paradigm in data acquisition and signal processing based on the assumption of sparsity and the incoherence of the received signal. Based on that concept, many radar front-end architectures have been studied with the implementation of CS. In these architectures, less data are collected but the radar scene...

Semi-Controllable Compression Schemes for Ultrasound Imaging

The application of Compressive Sampling (CS) in the medical ultrasound has been widely studied in recent years with the growing requirement of reconstructing high-quality images with smaller data size. Most of the current studies with successful CS reconstruction are mainly focusing on the mathematical applications of CS theory in ultrasound...