15.4k citations · 15.4k across the 7 of their papers we have counts for
7 papers
Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language
Michelle Stegeman, Lena Philipp, Fennie van der Graaf +20
Foundation models are changing the way we develop medical artificial intelligence. By learning broadly generalizable features across diverse data modalities, a single model can be…
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset
Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni +18
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to…
Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer
Caner Mercan, Maschenka Balkenhol, Roberto Salgado +13
Nuclear pleomorphism, defined herein as the extent of abnormalities in the overall appearance of tumor nuclei, is one of the components of the three-tiered breast cancer grading. G…
HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images
Mart van Rijthoven, Maschenka Balkenhol, Karina Siliņa +2
We propose HookNet, a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of encoder-decoder convolutional n…
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning
David Tellez, Diederik Hoppener, Cornelis Verhoef +5
We focus on the problem of training convolutional neural networks on gigapixel histopathology images to predict image-level targets. For this purpose, we extend Neural Image Compre…
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…
A Survey on Deep Learning in Medical Image Analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi +6
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning…