research
∙
09/12/2023
A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation
We present a semi-supervised domain adaptation framework for brain vesse...
share
research
∙
02/25/2023
Frequency Disentangled Learning for Segmentation of Midbrain Structures from Quantitative Susceptibility Mapping Data
One often lacks sufficient annotated samples for training deep segmentat...
research
∙
11/02/2022
Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI
Early and accurate diagnosis of parkinsonian syndromes is critical to pr...
research
∙
09/12/2022
Reproducibility in machine learning for medical imaging
Reproducibility is a cornerstone of science, as the replication of findi...
research
∙
04/14/2022
Interpretability of Machine Learning Methods Applied to Neuroimaging
Deep learning methods have become very popular for the processing of nat...
research
∙
04/30/2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
In this paper, we propose a new method to perform data augmentation in a...
research
∙
04/16/2021
Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse
Many studies on machine learning (ML) for computer-aided diagnosis have ...
research
∙
11/19/2019
Visualization approach to assess the robustness of neural networks for medical image classification
The use of neural networks for diagnosis classification is becoming more...
research
∙
04/16/2019
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation
In the past two years, over 30 papers have proposed to use convolutional...
research
∙
12/28/2018
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease
Diffusion MRI is the modality of choice to study alterations of white ma...
research
∙
08/20/2018
Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data
A large number of papers have introduced novel machine learning and feat...
research
∙
09/21/2017
