Improvement of 3D ultrasound computer tomography images by signal pre-processing

Abstract

Ultrasound computer tomography using synthetic aperture focusing technique is sensitive to phase aberration errors. We propose a signal preprocessing method for coherent imaging, which can take the system specific phase aberration into account. The method detects local maxima in the envelope of a matched filtered signal and convolutes the result with a truncated difference of sinc-functions, where the main lobe is scaled to represent the phase aberration. For our system we could show that reflectivity images reconstructed such pre-processed signals are approximately within a factor two of the ideal resolution, while increasing the contrast by a factor of 30.

First results of a clinical study with 3D ultrasound computer tomography

“…The A-scans were preprocessed using a matched filter, followed by envelope transformation, detection of the local maxima and convolution with an optimal pulse [7]. The main lobe of the optimal pulse was set to 2 µs, which corresponds to a Full Width Half Maximum (FWHM) of the point spread function of approx.…”

GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB

“…The matched filter also can cope with phase deviations. So the outcome is an improved contrast for the reconstructed image [12].…”

Comparison of processing performance and architectural efficiency metrics for FPGAs and GPUs in 3D Ultrasound Computer Tomography

“…In this work, we focus on signal processing, which directly operates on the acquired raw data, and on the core element of the actual image reconstruction. The signal processing sequence, called Adapted Matched Filtering (AMF) [21] is applied in order to improve the contrast in the reconstructed images. The Synthetic Aperture Focusing Technique (SAFT) [22] reconstruction algorithm then exploits the pressure over time information in the A-Scans in order to create reflectivity images.…”