721 citations · 1.4k across the 6 of their papers we have counts for
8 papers
CNN-based Lung CT Registration with Multiple Anatomical Constraints
Alessa Hering, Stephanie Häger, Jan Moltz +3
Deep-learning-based registration methods emerged as a fast alternative to conventional registration methods. However, these methods often still cannot achieve the same performance…
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images
Hans Pinckaers, Bram van Ginneken, Geert Litjens
Due to memory constraints on current hardware, most convolution neural networks (CNN) are trained on sub-megapixel images. For example, most popular datasets in computer vision con…
BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek +11
The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common…
Automated Gleason Grading of Prostate Biopsies using Deep Learning
Wouter Bulten, Hans Pinckaers, Hester van Boven +6
The Gleason score is the most important prognostic marker for prostate cancer patients but suffers from significant inter-observer variability. We developed a fully automated deep…
iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network
Guilherme Aresta, Colin Jacobs, Teresa Araújo +4
We propose iW-Net, a deep learning model that allows for both automatic and interactive segmentation of lung nodules in computed tomography images. iW-Net is composed of two blocks…
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard
Wouter Bulten, Péter Bándi, Jeffrey Hoven +7
Prostate cancer (PCa) is graded by pathologists by examining the architectural pattern of cancerous epithelial tissue on hematoxylin and eosin (H&E) stained slides. Given the impor…
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier-Hein, Matthias Eisenmann, Annika Reinke +35
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of c…
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…