3 citations · 5 across the 10 of their papers we have counts for
11 papers
Task-Based Adaptive Transmit Beamforming for Efficient Ultrasound Quantification
Oisín Nolan, Wessel L. van Nierop, Louis D. van Harten +2
Wireless and wearable ultrasound devices promise to enable continuous ultrasound monitoring, but power consumption and data throughput remain critical challenges. Reducing the numb…
zea: A Toolbox for Cognitive Ultrasound Imaging
Tristan S. W. Stevens, Wessel L. van Nierop, Ben Luijten +7
We present zea (pronounced ze-yah), a Python package for cognitive ultrasound imaging that offers a flexible, modular, and differentiable pipeline for ultrasound data processing. A…
Nuclear Diffusion Models for Low-Rank Background Suppression in Videos
Tristan S. W. Stevens, Oisín Nolan, Jean-Luc Robert +1
Video sequences often contain structured noise and background artifacts that obscure dynamic content, posing challenges for accurate analysis and restoration. Robust principal comp…
Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing
Tristan S. W. Stevens, Oisín Nolan, Ruud J. G. van Sloun
Echocardiography plays a central role in cardiac imaging, offering dynamic views of the heart that are essential for diagnosis and monitoring. However, image quality can be signifi…
Patient-Adaptive Echocardiography using Cognitive Ultrasound
Wessel L. van Nierop, Oisín Nolan, Tristan S. W. Stevens +1
Focused transmits are the most commonly used transmit strategy for echocardiograms, but suffer from relatively low frame rates, and in 3D, even lower volume rates. Fast imaging bas…
High Volume Rate 3D Ultrasound Reconstruction with Diffusion Models
Tristan S. W. Stevens, Oisín Nolan, Oudom Somphone +2
Three-dimensional ultrasound enables real-time volumetric visualization of anatomical structures. Unlike traditional 2D ultrasound, 3D imaging reduces reliance on precise probe ori…
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging
Tristan S. W. Stevens, Jeroen Overdevest, Oisín Nolan +3
Deep generative models have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that u…
Sequential Posterior Sampling with Diffusion Models
Tristan S. W. Stevens, Oisín Nolan, Jean-Luc Robert +1
Diffusion models have quickly risen in popularity for their ability to model complex distributions and perform effective posterior sampling. Unfortunately, the iterative nature of…
Off-Grid Ultrasound Imaging by Stochastic Optimization
Vincent van de Schaft, Oisín Nolan, Ruud J. G. van Sloun
Ultrasound images formed by delay-and-sum beamforming are plagued by artifacts that only clear up after compounding many transmissions. Some prior works pose imaging as an inverse…
Active Diffusion Subsampling
Oisin Nolan, Tristan S. W. Stevens, Wessel L. van Nierop +1
Subsampling is commonly used to mitigate costs associated with data acquisition, such as time or energy requirements, motivating the development of algorithms for estimating the fu…
BaIT: Barometer for Information Trustworthiness
Oisín Nolan, Jeroen van Mourik, Callum Rhys Tilbury
This paper presents a new approach to the FNC-1 fake news classification task which involves employing pre-trained encoder models from similar NLP tasks, namely sentence similarity…