activity
20182020
most citedNeural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands

17 citations · 17 across the 1 of their papers we have counts for

collaborators

5 papers

eess.IV2020

Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels

Hans Pinckaers, Wouter Bulten, Jeroen van der Laak +1

Prostate cancer is the most prevalent cancer among men in Western countries, with 1.1 million new diagnoses every year. The gold standard for the diagnosis of prostate cancer is a…

cs.CV2019

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…

eess.IV201917 cited

Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands

Hans Pinckaers, Geert Litjens

Automated medical image segmentation plays a key role in quantitative research and diagnostics. Convolutional neural networks based on the U-Net architecture are the state-of-the-a…

eess.IV2019

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…

cs.CV2018

Training convolutional neural networks with megapixel images

Hans Pinckaers, Geert Litjens

To train deep convolutional neural networks, the input data and the intermediate activations need to be kept in memory to calculate the gradient descent step. Given the limited mem…