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06/05/2023
A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge
This work proposes a method to accelerate the acquisition of high-qualit...
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01/16/2023
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held ...
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09/27/2021
Optimized Automated Cardiac MR Scar Quantification with GAN-Based Data Augmentation
Background: The clinical utility of late gadolinium enhancement (LGE) ca...
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02/15/2021
Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty
Corneal thickness (pachymetry) maps can be used to monitor restoration o...
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11/25/2020
Physics-informed neural networks for myocardial perfusion MRI quantification
Tracer-kinetic models allow for the quantification of kinetic parameters...
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10/07/2020
Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images
Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can...
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08/26/2020
Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation
Cine cardiac magnetic resonance (CMR) has become the gold standard for t...
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08/26/2020
Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology
Unsupervised learning enables modeling complex images without the need f...
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04/24/2020
Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks
Purpose: We developed a method to automatically locate and quantify graf...
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02/20/2020
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
Rotation-invariance is a desired property of machine-learning models for...
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11/22/2019
Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study
Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to b...
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10/31/2019
Deep learning assessment of breast terminal duct lobular unit involution: towards automated prediction of breast cancer risk
Terminal ductal lobular unit (TDLU) involution is the regression of milk...
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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...
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07/27/2019
Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI
The quantification of myocardial perfusion MRI has the potential to prov...
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07/22/2018
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge
Tumor proliferation is an important biomarker indicative of the prognosi...
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04/10/2018
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis
We propose a framework for rotation and translation covariant deep learn...
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01/10/2018
Inferring a Third Spatial Dimension from 2D Histological Images
Histological images are obtained by transmitting light through a tissue ...
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07/19/2017
Domain-adversarial neural networks to address the appearance variability of histopathology images
Preparing and scanning histopathology slides consists of several steps, ...
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07/11/2017
Adversarial training and dilated convolutions for brain MRI segmentation
Convolutional neural networks (CNNs) have been applied to various automa...
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06/12/2017
Exploring the similarity of medical imaging classification problems
Supervised learning is ubiquitous in medical image analysis. In this pap...
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06/20/2016
Cutting out the middleman: measuring nuclear area in histopathology slides without segmentation
The size of nuclei in histological preparations from excised breast tumo...
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11/21/2014