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20132020
most citedDomain-adversarial neural networks to address the appearance variability of histopathology images

1.1k citations · 1.9k across the 13 of their papers we have counts for

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Showing 2018 · cs.CVShow all

5 papers · 2 filters

cs.CV2018★ 283 cited

Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification

Marc Combalia, Veronica Vilaplana

We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared w…

cs.CV2018

Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2

We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the im…

cs.CV2018

Model Agnostic Saliency for Weakly Supervised Lesion Detection from Breast DCE-MRI

Gabriel Maicas, Gerard Snaauw, Andrew P. Bradley +2

There is a heated debate on how to interpret the decisions provided by deep learning models (DLM), where the main approaches rely on the visualization of salient regions to interpr…

cs.CV2018★ 387 cited

Why rankings of biomedical image analysis competitions should be interpreted with care

Lena Maier-Hein, Matthias Eisenmann, Annika Reinke +35

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of c…

cs.CV2018

Training Medical Image Analysis Systems like Radiologists

Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2

The training of medical image analysis systems using machine learning approaches follows a common script: collect and annotate a large dataset, train the classifier on the training…