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08/02/2023
Harder synthetic anomalies to improve OoD detection in Medical Images
Our method builds upon previous Medical Out-of-Distribution (MOOD) chall...
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07/27/2023
MIM-OOD: Generative Masked Image Modelling for Out-of-Distribution Detection in Medical Images
Unsupervised Out-of-Distribution (OOD) detection consists in identifying...
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05/22/2023
NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detection
NeSy4VRD is a multifaceted resource designed to support the development ...
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06/30/2022
Implicit U-Net for volumetric medical image segmentation
U-Net has been the go-to architecture for medical image segmentation tas...
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06/09/2021
Implicit field learning for unsupervised anomaly detection in medical images
We propose a novel unsupervised out-of-distribution detection method for...
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12/12/2020
Anomaly detection through latent space restoration using vector-quantized variational autoencoders
We propose an out-of-distribution detection method that combines density...
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06/11/2020
Blissful Ignorance: Anti-Transfer Learning for Task Invariance
We introduce the novel concept of anti-transfer learning for neural netw...
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11/09/2019
Deep learning for cardiac image segmentation: A review
Deep learning has become the most widely used approach for cardiac image...
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08/20/2019
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
In this work, we present a fully automatic method to segment cardiac str...
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07/23/2019
Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images
Cardiac MR image segmentation is essential for the morphological and fun...
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07/05/2019
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
In the recent years, convolutional neural networks have transformed the ...
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06/28/2019
Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling
Quantification of anatomical shape changes still relies on scalar global...
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02/28/2019
3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders
Accurate segmentation of heart structures imaged by cardiac MR is key fo...
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10/03/2018
A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks
In the clinical routine, short axis (SA) cine cardiac MR (CMR) image sta...
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08/01/2018
Recurrent neural networks for aortic image sequence segmentation with sparse annotations
Segmentation of image sequences is an important task in medical image an...
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07/18/2018
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling
Alterations in the geometry and function of the heart define well-establ...
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03/25/2018
Learning-Based Quality Control for Cardiac MR Images
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...
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10/25/2017
Human-level CMR image analysis with deep fully convolutional networks
Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...
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06/03/2016
