31 citations · 103 across the 26 of their papers we have counts for
6 papers · 1 filter
Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study
Friso G. Heslinga, Josien P. W. Pluim, A. J. H. M. Houben +6
Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to blindness and cardiovascular disease. Information about early stage T2D might be present in retinal fundus im…
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…
Patient-specific fine-tuning of CNNs for follow-up lesion quantification
Mariëlle J. A. Jansen, Hugo J. Kuijf, Ashis K. Dhara +4
Convolutional neural network (CNN) methods have been proposed to quantify lesions in medical imaging. Commonly more than one imaging examination is available for a patient, but the…
Liver segmentation and metastases detection in MR images using convolutional neural networks
Mariëlle J. A. Jansen, Hugo J. Kuijf, Maarten Niekel +4
Primary tumors have a high likelihood of developing metastases in the liver and early detection of these metastases is crucial for patient outcome. We propose a method based on con…
Motion correction of dynamic contrast enhanced MRI of the liver
Mariëlle J. A. Jansen, Wouter B. Veldhuis, Maarten S. van Leeuwen +1
Motion correction of dynamic contrast enhanced magnetic resonance images (DCE-MRI) is a challenging task, due to changes in image appearance. In this study a groupwise registration…
Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation
Mariëlle J. A. Jansen, Hugo J. Kuijf, Josien P. W. Pluim
Most MRI liver segmentation methods use a structural 3D scan as input, such as a T1 or T2 weighted scan. Segmentation performance may be improved by utilizing both structural and f…