5 papers
FedMAP: Personalised Federated Learning for Real Large-Scale Healthcare Systems
Fan Zhang, Daniel Kreuter, Carlos Esteve-Yagüe +11
Federated learning (FL) promises to enable collaborative machine learning across healthcare sites whilst preserving data privacy. Practical deployment remains limited by statistica…
SurvSurf: a partially monotonic neural network for first-hitting time prediction of intermittently observed discrete and continuous sequential events
Yichen Kelly Chen, Sören Dittmer, Kinga Bernatowicz +7
We propose a neural-network based survival model (SurvSurf) specifically designed for direct and simultaneous probabilistic prediction of the first hitting time of sequential event…
A study of why we need to reassess full reference image quality assessment with medical images
Anna Breger, Ander Biguri, Malena Sabaté Landman +11
Image quality assessment (IQA) is indispensable in clinical practice to ensure high standards, as well as in the development stage of machine learning algorithms that operate on me…
A study on the adequacy of common IQA measures for medical images
Anna Breger, Clemens Karner, Ian Selby +11
Image quality assessment (IQA) is standard practice in the development stage of novel machine learning algorithms that operate on images. The most commonly used IQA measures have b…
Unsupervised Learning of the Total Variation Flow
Tamara G. Grossmann, Sören Dittmer, Yury Korolev +1
The total variation (TV) flow generates a scale-space representation of an image based on the TV functional. This gradient flow observes desirable features for images, such as shar…