2 citations · 2 across the 5 of their papers we have counts for
5 papers
Rapid Lung Ultrasound COVID-19 Severity Scoring with Resource-Efficient Deep Feature Extraction
Pierre Raillard, Lorenzo Cristoni, Andrew Walden +6
Artificial intelligence-based analysis of lung ultrasound imaging has been demonstrated as an effective technique for rapid diagnostic decision support throughout the COVID-19 pand…
Meta-Registration: Learning Test-Time Optimization for Single-Pair Image Registration
Zachary MC Baum, Yipeng Hu, Dean C Barratt
Neural networks have been proposed for medical image registration by learning, with a substantial amount of training data, the optimal transformations between image pairs. These tr…
Learning Generalized Non-Rigid Multimodal Biomedical Image Registration from Generic Point Set Data
Zachary MC Baum, Tamas Ungi, Christopher Schlenger +2
Free Point Transformer (FPT) has been proposed as a data-driven, non-rigid point set registration approach using deep neural networks. As FPT does not assume constraints based on p…
Lung Ultrasound Segmentation and Adaptation between COVID-19 and Community-Acquired Pneumonia
Harry Mason, Lorenzo Cristoni, Andrew Walden +6
Lung ultrasound imaging has been shown effective in detecting typical patterns for interstitial pneumonia, as a point-of-care tool for both patients with COVID-19 and other communi…
Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels
Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8
When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…