46 citations · 59 across the 6 of their papers we have counts for
6 papers
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…
Removing Structured Noise with Diffusion Models
Tristan S. W. Stevens, Hans van Gorp, Faik C. Meral +4
Solving ill-posed inverse problems requires careful formulation of prior beliefs over the signals of interest and an accurate description of their manifestation into noisy measurem…
Efficient Out-of-Distribution Detection of Melanoma with Wavelet-based Normalizing Flows
M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun +2
Melanoma is a serious form of skin cancer with high mortality rate at later stages. Fortunately, when detected early, the prognosis of melanoma is promising and malignant melanoma…
SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
Iris A. M. Huijben, Arthur A. Nijdam, Sebastiaan Overeem +2
Continuous monitoring with an ever-increasing number of sensors has become ubiquitous across many application domains. However, acquired time series are typically high-dimensional…
Ultrasound Signal Processing: From Models to Deep Learning
Ben Luijten, Nishith Chennakeshava, Yonina C. Eldar +2
Medical ultrasound imaging relies heavily on high-quality signal processing to provide reliable and interpretable image reconstructions. Conventionally, reconstruction algorithms w…
Deep Proximal Learning for High-Resolution Plane Wave Compounding
Nishith Chennakeshava, Ben Luijten, Massimo Mischi +2
Plane Wave imaging enables many applications that require high frame rates, including localisation microscopy, shear wave elastography, and ultra-sensitive Doppler. To alleviate th…