Deconvolution approach to ultrasound medical imaging.

The aim of this work is to derive new algorithms for improving the spatial resolution of medical ultrasonic images and suppressing the speckle pattern. The project was oriented at 1-D and 2-D deconvolution using Wiener filter. An essential part of the task was to estimate the Point Spread Function (PSF) of the imaging process in the raw radio-frequency (RF) signal domain. RF data was first obtained from an advanced ultrasound scanner SONIX RP. The characteristics of ultrasound speckles can be analyzed and studied using MATLAB. Subsequently, signal processing was done to transform the RF data from the spatial-domain into cepstrum-domain whereby the tissue function and PSF are separable. The author then proposed a low-pass filter to extract an estimation of the PSF which is required for the deconvolution step that follows after that. The performances of the proposed method were assessed by using visual comparison with other images. The proposed method was shown to possess superior speckle reduction ability while retaining important image details. As the major focus of the project is to address the low quality problem of medical ultrasound images due to speckles, this method serves as an invaluable way to enhance the analysis and physical investigation of ultrasound scanning for application explorations. This report will first briefly describe the background of ultrasound signal, medical ultrasound image formation and some relevant characteristic of speckles. The rest of the report will contain detailed descriptions of concepts, methods and results of the proposed method that are implemented on the RF signal.Bachelor of Engineering (Chemical and Biomolecular Engineering