research
∙
07/11/2023
Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering
One of the main issues of the current tractography methods is their high...
share
research
∙
05/23/2023
Mixup-Privacy: A simple yet effective approach for privacy-preserving segmentation
Privacy protection in medical data is a legitimate obstacle for centrali...
research
∙
05/15/2023
What Matters in Reinforcement Learning for Tractography
Recently, deep reinforcement learning (RL) has been proposed to learn th...
research
∙
05/03/2023
Extraction of volumetric indices from echocardiography: which deep learning solution for clinical use?
Deep learning-based methods have spearheaded the automatic analysis of e...
research
∙
11/30/2022
FIESTA: FIber gEneration and bundle Segmentation in Tractography using Autoencoders
White matter bundle segmentation is a cornerstone of modern tractography...
research
∙
11/23/2022
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans
Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent ...
research
∙
06/15/2022
CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation
Accurate uncertainty estimation is a critical need for the medical imagi...
research
∙
04/22/2022
Generative sampling in tractography using autoencoders (GESTA)
Current tractography methods use the local orientation information to pr...
research
∙
12/03/2021
Echocardiography Segmentation with Enforced Temporal Consistency
Convolutional neural networks (CNN) have demonstrated their ability to s...
research
∙
08/09/2021
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging
The physical and clinical constraints surrounding diffusion-weighted ima...
research
∙
07/23/2021
Deep Learning Based Cardiac MRI Segmentation: Do We Need Experts?
Deep learning methods are the de-facto solutions to a multitude of medic...
research
∙
05/11/2021
GANs for Medical Image Synthesis: An Empirical Study
Generative Adversarial Networks (GANs) have become increasingly powerful...
research
∙
12/02/2020
Neural Teleportation
In this paper, we explore a process called neural teleportation, a mathe...
research
∙
11/25/2020
Privacy Preserving for Medical Image Analysis via Non-Linear Deformation Proxy
We propose a client-server system which allows for the analysis of multi...
research
∙
10/07/2020
Tractography filtering using autoencoders
Current brain white matter fiber tracking techniques show a number of pr...
research
∙
07/23/2020
The Representation Theory of Neural Networks
In this work, we show that neural networks can be represented via the ma...
research
∙
06/15/2020
Cardiac Segmentation with Strong Anatomical Guarantees
Convolutional neural networks (CNN) have had unprecedented success in me...
research
∙
05/18/2020
On the effectiveness of GAN generated cardiac MRIs for segmentation
In this work, we propose a Variational Autoencoder (VAE) - Generative Ad...
research
∙
04/04/2020
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography
Segmentation of cardiac structures is one of the fundamental steps to es...
research
∙
09/09/2019
Privacy-Net: An Adversarial Approach For Identity-obfuscated Segmentation
This paper presents a privacy-preserving network oriented towards medica...
research
∙
07/05/2019
Cardiac MRI Segmentation with Strong Anatomical Guarantees
Recent publications have shown that the segmentation accuracy of modern-...
research
∙
05/17/2019
Spectral Metric for Dataset Complexity Assessment
In this paper, we propose a new measure to gauge the complexity of image...
research
∙
02/14/2019
Tractography and machine learning: Current state and open challenges
Supervised machine learning (ML) algorithms have recently been proposed ...
research
∙
11/23/2018
Structured Pruning of Neural Networks with Budget-Aware Regularization
Pruning methods have shown to be effective at reducing the size of deep ...
research
∙
05/24/2017
GridNet with automatic shape prior registration for automatic MRI cardiac segmentation
In this paper, we propose a fully automatic MRI cardiac segmentation met...
research
∙
07/18/2016
Deep learning trends for focal brain pathology segmentation in MRI
Segmentation of focal (localized) brain pathologies such as brain tumors...
research
∙
10/05/2015
Within-Brain Classification for Brain Tumor Segmentation
Purpose: In this paper, we investigate a framework for interactive brain...
research
∙
05/13/2015
Brain Tumor Segmentation with Deep Neural Networks
In this paper, we present a fully automatic brain tumor segmentation met...
research
∙
05/01/2014