42 citations · 67 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
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…
Dehazing Ultrasound using Diffusion Models
Tristan S. W. Stevens, Faik C. Meral, Jason Yu +3
Echocardiography has been a prominent tool for the diagnosis of cardiac disease. However, these diagnoses can be heavily impeded by poor image quality. Acoustic clutter emerges due…
Accelerated Intravascular Ultrasound Imaging using Deep Reinforcement Learning
Tristan S. W. Stevens, Nishith Chennakeshava, Frederik J. de Bruijn +2
Intravascular ultrasound (IVUS) offers a unique perspective in the treatment of vascular diseases by creating a sequence of ultrasound-slices acquired from within the vessel. Howev…
Automated Gain Control Through Deep Reinforcement Learning for Downstream Radar Object Detection
Tristan S. W. Stevens, R. Firat Tigrek, Eric S. Tammam +1
Cognitive radars are systems that rely on learning through interactions of the radar with the surrounding environment. To realize this, radar transmit parameters can be adapted suc…