296 citations · 734 across the 10 of their papers we have counts for
9 papers · 1 filter
Robust Cross-vendor Mammographic Texture Models Using Augmentation-based Domain Adaptation for Long-term Breast Cancer Risk
Andreas D. Lauritzen, My Catarina von Euler-Chelpin, Elsebeth Lynge +4
Purpose: Risk-stratified breast cancer screening might improve early detection and efficiency without comprising quality. However, modern mammography-based risk models do not ensur…
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks
David Tellez, Maschenka Balkenhol, Irene Otte-Holler +10
Manual counting of mitotic tumor cells in tissue sections constitutes one of the strongest prognostic markers for breast cancer. This procedure, however, is time-consuming and erro…
Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR
Mohsen Ghafoorian, Jonas Teuwen, Rashindra Manniesing +4
Ventricular volume and its progression are known to be linked to several brain diseases such as dementia and schizophrenia. Therefore accurate measurement of ventricle volume is vi…
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
Babak Ehteshami Bejnordi, Guido Zuidhof, Maschenka Balkenhol +6
Automated classification of histopathological whole-slide images (WSI) of breast tissue requires analysis at very high resolutions with a large contextual area. In this paper, we p…
Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks
Thijs Kooi, Nico Karssemeijer
We investigate the addition of symmetry and temporal context information to a deep Convolutional Neural Network (CNN) with the purpose of detecting malignant soft tissue lesions in…
Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation
Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur +11
Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of nor…
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images
Babak Ehteshami Bejnordi, Jimmy Linz, Ben Glass +6
Diagnosis of breast carcinomas has so far been limited to the morphological interpretation of epithelial cells and the assessment of epithelial tissue architecture. Consequently, m…
Deep Multi-scale Location-aware 3D Convolutional Neural Networks for Automated Detection of Lacunes of Presumed Vascular Origin
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +8
Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel d…
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +7
The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in co…