Silas Nyboe Ørting
Postdoc
Image Analysis, Computational Modelling and Geometry
Universitetsparken 1, 2100 København Ø
Silas is a Post Doc researcher affiliated with the Center for Quantification of Imaging Data from Max IV (QIM).
Silas received a Ph.D degree in medical image analysis in 2019 and a Master's degree in computer sicence in 2016, both from the Department of Computer Science, University of Copenhagen. His main area of research is within biomedical image analysis with an emphasis on the practical application of machine learning in settings where labeled data are scarce, expensive and noisy. This includes weakly supervised machine learning, as well as image annotation strategies such as crowdsourcing, visual similarity and low-effort annotations.
ID: 156727261
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341
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Assessing emphysema in CT scans of the lungs: Using machine learning, crowdsourcing and visual similarity
Publikation: Bog/antologi/afhandling/rapport › Ph.d.-afhandling › Forskning
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117
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Quantifying emphysema extent from weakly labeled CT scans of the lungs using label proportions learning
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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