Decoding Techniques and Power Savings for Compressed Sensing Based Portable Ultrasound Imaging System

Jovan Mitrovic

Supervised by Professor Zeljko Ignjatovic

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Medical imaging is going through a period of many innovations and improvements, as new imaging techniques and image algorithms are discovered every day. Still, ultrasound imaging remains the most important non-ionizing medical imaging technique. Although conceptually less demanding than CT or MRI machines, innovations related to ultrasound imaging can bring a lot of hardware overhead, which happens particularly with 2D scanners.

This thesis aims to present a method that allows the ultrasound imaging to be performed with a much smaller hardware footprint, resulting in large power savings (up to 80%), but without the sacrifice to the image quality. This is possible by compressing the data in the analog domain through the implementation of the theory of compressed sensing. A study on the decoding algorithm is provided as well.

Furthermore, a study of the optimal sparse array is provided, which allows an easy design, but powerful performance without large sacrifice to the image quality. This method of sparse array construction can be used by itself or can push the power savings of the compressed sensing-based algorithm even further (up to 90%). The evaluation of the sparse array along with the similar sparse array configurations is provided.