Development of an algorithm for the pulse polarity detection of an ultrasound probe and of an algorithm for the Air-bubbles detection on the surface of an ultrasound probe during an acoustic measurement

Abstract

This thesis presents the development and evaluation of two novel algorithms aimed at enhancing ultrasound imaging: the Pulse Polarity Detection Algorithm and the Air Bubble Detection Methodology. The Pulse Polarity Detection Algorithm is designed to accurately identify the polarity of ultrasound waveforms. This is crucial for ensuring the integrity and quality of imaging data, which can significantly impact diagnostic outcomes. The algorithm was rigorously tested and demonstrated an impressive sensitivity of 100% and specificity of 100%. These results underline the algorithm’s robustness and reliability in various ultrasound imaging scenarios. The Air Bubble Detection Methodology comprises two distinct approaches for identifying air bubbles on the surface of ultrasound probes: Method 1 (Reflection Method) and Method 2 (Data Points Method). Accurate detection of air bubbles is essential for maintaining the efficacy of ultrasound procedures, as air bubbles can cause significant image artifacts and degrade image quality. Method 1 involves the reflection and comparison of cross-sectional profiles to detect asymmetries indicative of air bubbles. Method 2 directly compares data points across profiles to identify deviations. Both methods exhibited high accuracy, with Method 1 achieving 95.05% and Method 2 achieving 96.04%. The high sensitivity and specificity of these methods demonstrate their effectiveness in minimizing false positives and negatives, ensuring reliable detection of air bubbles. These advancements in pulse polarity detection and air bubble detection represent significant contributions to the field of ultrasound imaging. Future research will focus on ref ining these algorithms and exploring complementary techniques to further enhance their performance and applicability in diverse laboratory and clinical settings. The algorithms were implemented and simulated using MATLAB, with initial data and acoustic output measurements provided by GE Healthcare. The experimental acoustic measurements performed by a hydrophone in a water tank.

Datum der Bewilligung	Juni 2024
Originalsprache	Englisch
Betreuer/-in	Andreas Schrempf (Betreuer*in)