187 citations · 721 across the 60 of their papers we have counts for
7 papers · 1 filter
Crowdsourcing Airway Annotations in Chest Computed Tomography Images
Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo +2
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine lea…
Medical Imaging with Deep Learning: MIDL 2020 -- Short Paper Track
Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne +3
This compendium gathers all the accepted extended abstracts from the Third International Conference on Medical Imaging with Deep Learning (MIDL 2020), held in Montreal, Canada, 6-9…
Region-of-interest guided Supervoxel Inpainting for Self-supervision
Subhradeep Kayal, Shuai Chen, Marleen de Bruijne
Self-supervised learning has proven to be invaluable in making best use of all of the available data in biomedical image segmentation. One particularly simple and effective mechani…
DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data
Soumick Chatterjee, Kartik Prabhu, Mahantesh Pattadkal +7
Blood vessels of the brain provide the human brain with the required nutrients and oxygen. As a vulnerable part of the cerebral blood supply, pathology of small vessels can cause s…
Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors
Gerda Bortsova, Cristina González-Gonzalo, Suzanne C. Wetstein +9
Adversarial attacks are considered a potentially serious security threat for machine learning systems. Medical image analysis (MedIA) systems have recently been argued to be vulner…
Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images
Subhradeep Kayal, Florian Dubost, Harm A. W. M. Tiddens +1
Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present…
When Weak Becomes Strong: Robust Quantification of White Matter Hyperintensities in Brain MRI scans
Oliver Werner, Kimberlin M. H. van Wijnen, Wiro J. Niessen +4
To measure the volume of specific image structures, a typical approach is to first segment those structures using a neural network trained on voxel-wise (strong) labels and subsequ…