Current and emerging knowledge in COVID-19
COVID-19 has emerged as a pandemic leading to a global public health crisis of
unprecedented morbidity. A comprehensive insight into the imaging of COVID-19 has …
unprecedented morbidity. A comprehensive insight into the imaging of COVID-19 has …
Medlsam: Localize and segment anything model for 3d medical images
The Segment Anything Model (SAM) has recently emerged as a groundbreaking model in
the field of image segmentation. Nevertheless, both the original SAM and its medical …
the field of image segmentation. Nevertheless, both the original SAM and its medical …
Geometric visual similarity learning in 3d medical image self-supervised pre-training
Learning inter-image similarity is crucial for 3D medical images self-supervised pre-training,
due to their sharing of numerous same semantic regions. However, the lack of the semantic …
due to their sharing of numerous same semantic regions. However, the lack of the semantic …
Pleuropulmonary manifestations of vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome
Background The vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS)
syndrome is a newly identified autoinflammatory disorder related to somatic UBA1 …
syndrome is a newly identified autoinflammatory disorder related to somatic UBA1 …
[HTML][HTML] Covid-19: Early Cases and Disease Spread
J Reis, A Le Faou, A Buguet, G Sandner… - Annals of Global …, 2022 - ncbi.nlm.nih.gov
The emergence and global spread of the Severe Acute Respiratory Syndrome Coronavirus-
2 (SARS-CoV-2) is critical to understanding how to prevent or control a future viral …
2 (SARS-CoV-2) is critical to understanding how to prevent or control a future viral …
Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19
Objectives COVID-19 pandemic seems to be under control. However, despite the vaccines,
5 to 10% of the patients with mild disease develop moderate to critical forms with potential …
5 to 10% of the patients with mild disease develop moderate to critical forms with potential …
COVID detection and severity prediction with 3D-ConvNeXt and custom pretrainings
Since COVID strongly affects the respiratory system, lung CT-scans can be used for the
analysis of a patients health. We introduce a neural network for the prediction of the severity …
analysis of a patients health. We introduce a neural network for the prediction of the severity …
Human Observer Net: a platform tool for human observer studies of image data
U Genske, P Jahnke - Radiology, 2022 - pubs.rsna.org
Background Current software applications for human observer studies of images lack
flexibility in study design, platform independence, multicenter use, and assessment methods …
flexibility in study design, platform independence, multicenter use, and assessment methods …
ECONet: Efficient convolutional online likelihood network for scribble-based interactive segmentation
Automatic segmentation of lung lesions associated with COVID-19 in CT images requires
large amount of annotated volumes. Annotations mandate expert knowledge and are time …
large amount of annotated volumes. Annotations mandate expert knowledge and are time …
High-confidence pseudo-labels for domain adaptation in COVID-19 detection
R Turnbull, S Mutch - arXiv preprint arXiv:2403.13509, 2024 - arxiv.org
This paper outlines our submission for the 4th COV19D competition as part of theDomain
adaptation, Explainability, Fairness in AI for Medical Image Analysis'(DEF-AI-MIA) workshop …
adaptation, Explainability, Fairness in AI for Medical Image Analysis'(DEF-AI-MIA) workshop …