Anne L. Martel | DeepAI

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Featured Co-authors

Bram van Ginneken
49 publications
Lena Maier-Hein
46 publications
Tal Arbel
28 publications
Mitko Veta
22 publications
Henning Müller
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Seung Wook Kim
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Annika Reinke
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Pierre Jannin
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Jianan Chen
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Annette Kopp-Schneider*
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Mahdi Biparva
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∙ 03/11/2022

ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI

Deep artificial neural networks (DNNs) have moved to the forefront of me...

20 Lyndon Boone, et al. ∙

∙ 03/09/2022

Metastatic Cancer Outcome Prediction with Injective Multiple Instance Pooling

Cancer stage is a large determinant of patient prognosis and management ...

0 Jianan Chen, et al. ∙

∙ 10/14/2021

BI-RADS BERT Using Section Tokenization to Understand Radiology Reports

Radiology reports are the main form of communication between radiologist...

0 Grey Kuling, et al. ∙

∙ 08/16/2021

Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology

Self-supervised learning (SSL) has recently shown tremendous potential t...

0 Chetan L. Srinidhi, et al. ∙

∙ 02/07/2021

Self-supervised driven consistency training for annotation efficient histopathology image analysis

Training a neural network with a large labeled dataset is still a domina...

0 Chetan L. Srinidhi, et al. ∙

∙ 12/12/2020

AMINN: Autoencoder-based Multiple Instance Neural Network for Outcome Prediction of Multifocal Liver Metastases

Colorectal cancer is one of the most common and lethal cancers and color...

0 Jianan Chen, et al. ∙

∙ 12/01/2020

Overcoming the limitations of patch-based learning to detect cancer in whole slide images

Whole slide images (WSIs) pose unique challenges when training deep lear...

0 Ozan Ciga, et al. ∙

∙ 11/27/2020

Self supervised contrastive learning for digital histopathology

Unsupervised learning has been a long-standing goal of machine learning ...

35 Ozan Ciga, et al. ∙

∙ 12/28/2019

Learning to segment images with classification labels

Two of the most common tasks in medical imaging are classification and s...

8 Ozan Ciga, et al. ∙

∙ 12/28/2019

Deep neural network models for computational histopathology: A survey

Histopathological images contain rich phenotypic information that can be...

0 Chetan L. Srinidhi, et al. ∙

∙ 10/09/2019

BIAS: Transparent reporting of biomedical image analysis challenges

The number of biomedical image analysis challenges organized per year is...

12 Lena Maier-Hein, et al. ∙

∙ 09/06/2019

Unsupervised Clustering of Quantitative Imaging Phenotypes using Autoencoder and Gaussian Mixture Model

Quantitative medical image computing (radiomics) has been widely applied...

0 Jianan Chen, et al. ∙

∙ 09/05/2019

Intensity augmentation for domain transfer of whole breast segmentation in MRI

The segmentation of the breast from the chest wall is an important first...

0 Linde S. Hesse, et al. ∙

∙ 11/28/2018

Cluster-Based Learning from Weakly Labeled Bags in Digital Pathology

To alleviate the burden of gathering detailed expert annotations when tr...

0 Shazia Akbar, et al. ∙

∙ 06/27/2016

Interpreting extracted rules from ensemble of trees: Application to computer-aided diagnosis of breast MRI

High predictive performance and ease of use and interpretability are imp...

0 Cristina Gallego-Ortiz, et al. ∙

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