activity
20192024
most citedAdversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors

129 citations · 232 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2024

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…

cs.CR2020★ 129 cited

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…

cs.CV2019★ 36 cited

Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images

Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken +1

Interpretability of deep learning (DL) systems is gaining attention in medical imaging to increase experts' trust in the obtained predictions and facilitate their integration in cl…

eess.IV2019★ 67 cited

A deep learning model for segmentation of geographic atrophy to study its long-term natural history

Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo +6

Purpose: To develop and validate a deep learning model for automatic segmentation of geographic atrophy (GA) in color fundus images (CFIs) and its application to study growth rate…