758 citations · 2.1k across the 52 of their papers we have counts for
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Cats or CAT scans: transfer learning from natural or medical image source datasets?
Veronika Cheplygina
Transfer learning is a widely used strategy in medical image analysis. Instead of only training a network with a limited amount of data from the target task of interest, we can fir…
Characterizing multiple instance datasets
Veronika Cheplygina, David M. J. Tax
In many pattern recognition problems, a single feature vector is not sufficient to describe an object. In multiple instance learning (MIL), objects are represented by sets (\emph{b…
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…
Crowd disagreement about medical images is informative
Veronika Cheplygina, Josien P. W. Pluim
Classifiers for medical image analysis are often trained with a single consensus label, based on combining labels given by experts or crowds. However, disagreement between annotato…
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Veronika Cheplygina, Marleen de Bruijne, Josien P. W. Pluim
Machine learning (ML) algorithms have made a tremendous impact in the field of medical imaging. While medical imaging datasets have been growing in size, a challenge for supervised…