Jesper Molin

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos et al. · Medical Image Analysis · 2019 · 308 citations · Full text

Breast Oncology, Image Analysis, Whole-slide Imaging +14

Implementation of large-scale routine diagnostics using whole slide imaging in Sweden: Digital pathology experiences 2006-2013

Sten Thorstenson, Jesper Molin, Claes Lundström · Journal of Pathology Informatics · 2014 · 175 citations · Full text

Deep learning nuclei detection: A simple approach can deliver state-of-the-art results

Henning Höfener, André Homeyer, Nick Weiss et al. · Computerized Medical Imaging and Graphics · 2018 · 90 citations · Full text

Towards grading gleason score using generically trained deep convolutional neural networks

H.L.A. van der Kallen, Jesper Molin, Anders Heyden et al. · 2016 · 71 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +21

The human‐in‐the‐loop: an evaluation of pathologists’ interaction with artificial intelligence in clinical practice

Anna Bodén, Jesper Molin, Stina Garvin et al. · Histopathology · 2021 · 39 citations · Full text