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20172025
most citedAdversarial training and dilated convolutions for brain MRI segmentation

23 citations · 31 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023

Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge

Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan +27

Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with…

cs.CV2021

Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge

Maxime W. Lafarge, Viktor H. Koelzer

Automated detection of mitotic figures in histopathology images is a challenging task: here, we present the different steps that describe the strategy we applied to participate in…

cs.CV2020

Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis

Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim +2

Rotation-invariance is a desired property of machine-learning models for medical image analysis and in particular for computational pathology applications. We propose a framework t…

cs.CV2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis

Erik J Bekkers, Maxime W Lafarge, Mitko Veta +3

We propose a framework for rotation and translation covariant deep learning using group convolutions. The group product of the special Euclidean motion group descri…

cs.CV2018

Inferring a Third Spatial Dimension from 2D Histological Images

Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof +2

Histological images are obtained by transmitting light through a tissue specimen that has been stained in order to produce contrast. This process results in 2D images of the specim…

cs.CV201723 cited

Adversarial training and dilated convolutions for brain MRI segmentation

Pim Moeskops, Mitko Veta, Maxime W. Lafarge +2

Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversa…