129 citations · 212 across the 5 of their papers we have counts for
5 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…
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset
Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni +18
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to…
Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images
Suzanne C. Wetstein, Nikolas Stathonikos, Josien P. W. Pluim +5
Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerab…
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…
Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk
Suzanne C Wetstein, Allison M Onken, Christina Luffman +13
Terminal ductal lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cance…