4 papers · 1 filter
A Survey of Crowdsourcing in Medical Image Analysis
Silas Ørting, Andrew Doyle, Arno van Hilten +6
Rapid advances in image processing capabilities have been seen across many domains, fostered by the application of machine learning algorithms to "big-data". However, within the re…
Learning to quantify emphysema extent: What labels do we need?
Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen +2
Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression and to predict lung cancer risk. However, visual assess…
Deep Learning from Label Proportions for Emphysema Quantification
Gerda Bortsova, Florian Dubost, Silas Ørting +5
We propose an end-to-end deep learning method that learns to estimate emphysema extent from proportions of the diseased tissue. These proportions were visually estimated by experts…
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
Silas Nyboe Ørting, Jens Petersen, Veronika Cheplygina +3
Supervised feature learning using convolutional neural networks (CNNs) can provide concise and disease relevant representations of medical images. However, training CNNs requires a…