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04/26/2023
Effect of latent space distribution on the segmentation of images with multiple annotations
We propose the Generalized Probabilistic U-Net, which extends the Probab...
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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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07/26/2022
Generalized Probabilistic U-Net for medical image segementation
We propose the Generalized Probabilistic U-Net, which extends the Probab...
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06/22/2022
Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection
Deep learning techniques show success in detecting objects in medical im...
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07/27/2021
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification
We present ENHANCE, an open dataset with multiple annotations to complem...
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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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01/12/2021
Using uncertainty estimation to reduce false positives in liver lesion detection
Despite the successes of deep learning techniques at detecting objects i...
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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
Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology
Unsupervised learning enables modeling complex images without the need f...
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06/30/2020
Primary Tumor Origin Classification of Lung Nodules in Spectral CT using Transfer Learning
Early detection of lung cancer has been proven to decrease mortality sig...
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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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03/16/2020
clDice – a Topology-Preserving Loss Function for Tubular Structure Segmentation
Accurate segmentation of tubular, network-like structures, such as vesse...
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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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10/15/2019
Liver segmentation and metastases detection in MR images using convolutional neural networks
Primary tumors have a high likelihood of developing metastases in the li...
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08/22/2019
Motion correction of dynamic contrast enhanced MRI of the liver
Motion correction of dynamic contrast enhanced magnetic resonance images...
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08/22/2019
Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation
Most MRI liver segmentation methods use a structural 3D scan as input, s...
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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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06/21/2018
Crowd disagreement of medical images is informative
Classifiers for medical image analysis are often trained with a single c...
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04/17/2018
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Machine learning (ML) algorithms have made a tremendous impact in the fi...
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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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08/09/2017
Isointense infant brain MRI segmentation with a dilated convolutional neural network
Quantitative analysis of brain MRI at the age of 6 months is difficult b...
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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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06/20/2016
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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03/01/2016
Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest
Colorectal adenocarcinoma originating in intestinal glandular structures...
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11/21/2014
