187 citations · 319 across the 6 of their papers we have counts for
6 papers
World of Forms: Deformable Geometric Templates for One-Shot Surface Meshing in Coronary CT Angiography
Rudolf L. M. van Herten, Ioannis Lagogiannis, Jelmer M. Wolterink +8
Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large train…
Adversarial Heart Attack: Neural Networks Fooled to Segment Heart Symbols in Chest X-Ray Images
Gerda Bortsova, Florian Dubost, Laurens Hogeweg +2
Adversarial attacks consist in maliciously changing the input data to mislead the predictions of automated decision systems and are potentially a serious threat for automated medic…
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…
Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations
Gerda Bortsova, Florian Dubost, Laurens Hogeweg +2
The scarcity of labeled data often limits the application of supervised deep learning techniques for medical image segmentation. This has motivated the development of semi-supervis…
DeGraF-Flow: Extending DeGraF Features for accurate and efficient sparse-to-dense optical flow estimation
Felix Stephenson, Toby Breckon, Ioannis Katramados
Modern optical flow methods make use of salient scene feature points detected and matched within the scene as a basis for sparse-to-dense optical flow estimation. Current feature d…
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…