Control of Multi-Degree-of-Freedom Catheters in Unknown Environments: Exploring the Potential of Deep Learning and Augmented Reality

Cardiovascular disease is currently one of the biggest threats to health. Specific types of cardiovascular disease include, but are not limited to, coronary artery disease, cardiac valve disorders, or peripheral arterial disease. The current gold standard for managing these conditions incorporates the use of catheters and guidewires for...

Classification of Human Activities with Distributed Radar Systems

This thesis introduces the relevance of radar systems in the realm of human activity recognition (HAR) in Chapter 1. The study touches upon the complex understanding of continuous human activities and the existing challenges and gaps in current methodologies, hinting at the innovative technical approaches that are to be detailed in the following...

Wind Power Ramps: Characterisation, Forecasting and Future Projection

Offshore wind energy is a renewable energy source that is anticipated to be significant in the global shift towards clean and green energy in order to reduce the reliance on fossil fuels and mitigate climate change. In recent years, the overall output of offshore wind energy has increased, and as a result, investments in offshore wind power have...

Expensive Optimization with Model-Based Evolutionary Algorithms Applied to Medical Image Segmentation Using Deep Learning

Recently great achievements have been obtained with Artificial Intelligence (AI) methods including human-level performance in such challenging areas as image processing, natural language processing, computational biology, and game playing. Arguably, one of the most societally important application fields of such methods is healthcare. <br/>AI is...

High-frame-rate volumetric ultrasound imaging using dedicated arrays and deep learning

High-frame-rate volumetric ultrasound imaging is highly desired to enable novel clinical ultrasound applications. However, realizing high-quality volumetric ultrasound imaging at a high frame rates (&gt;500 Hz) is challenging. Keeping the cable count and data rate of the transducer device at a realistic level without sacrificing image quality to...

Artificial Intelligence in Radiotherapy: Probabilistic Deep Learning for Dose Prediction and Anatomy Modeling

Accelerating finite element analysis using machine learning

We study the acceleration of the finite element method (FEM) simulations using machine learning (ML) models. Specifically, we replace computationally expensive (parts of) FEM models with efficient ML surrogates. We develop three methods to speed up FEM simulations. The primary difference between these models is their degree of intrusion into the...

Automatic Object Extraction from Airborne Laser Scanning Point Clouds for Digital Base Map Production

A base map provides essential geospatial information for applications such as urban planning, intelligent transportation systems, and disaster management. Buildings and roads are the main ingredients of a base map and are represented by polygons. Unfortunately, manually delineating their boundaries from remote sensing data is time consuming and...