6 citations · 10 across the 5 of their papers we have counts for
5 papers
CycleULM: A unified label-free deep learning framework for ultrasound localisation microscopy
Su Yan, Clara Rodrigo Gonzalez, Vincent C. H. Leung +11
Super-resolution ultrasound via microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy (ULM), can resolve microvasculature beyond the acoustic…
Adversarial Deep-Unfolding Network for MA-XRF Super-Resolution on Old Master Paintings Using Minimal Training Data
Herman Verinaz-Jadan, Su Yan, Catherine Higgitt +1
High-quality element distribution maps enable precise analysis of the material composition and condition of Old Master paintings. These maps are typically produced from data acquir…
Integrating Deep Unfolding with Direct Diffusion Bridges for Computed Tomography Reconstruction
Herman Verinaz-Jadan, Su Yan
Computed Tomography (CT) is widely used in healthcare for detailed imaging. However, Low-dose CT, despite reducing radiation exposure, often results in images with compromised qual…
Enhancing super-resolution ultrasound localisation through multi-frame deconvolution exploiting spatiotemporal coherence
Su Yan, Clotilde Vié, Marcelo Lerendegui +8
Super-resolution ultrasound imaging through microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy, allows non-invasive sub-diffraction resolu…
A Fast Automatic Method for Deconvoluting Macro X-ray Fluorescence Data Collected from Easel Paintings
Su Yan, Jun-Jie Huang, Herman Verinaz-Jadan +3
Macro X-ray Fluorescence (MA-XRF) scanning is increasingly widely used by researchers in heritage science to analyse easel paintings as one of a suite of non-invasive imaging techn…