NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (12)

cs.CV2017

The importance of stain normalization in colorectal tissue classification with convolutional networks

Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi +6

cs.CV2019

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

Amber L. Simpson, Michela Antonelli, Spyridon Bakas +21

cs.CV2019

Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Wouter Bulten, Péter Bándi, Jeffrey Hoven +7

cs.CV2016

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities

Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes +7

cs.CV2017

A Survey on Deep Learning in Medical Image Analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi +6

cs.CV2018

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

cs.CV2018

Training convolutional neural networks with megapixel images

Hans Pinckaers, Geert Litjens

cs.CV2017

Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images

Péter Bándi, Rob van de Loo, Milad Intezar +5

cs.CV2018

Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study

Zhang Li, Zheyu Hu, Jiaolong Xu +10

cs.CV2019

Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification

Koen Dercksen, Wouter Bulten, Geert Litjens

cs.CV2018

Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders

Wouter Bulten, Geert Litjens

cs.CV2017

Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images

Babak Ehteshami Bejnordi, Guido Zuidhof, Maschenka Balkenhol +6