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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...
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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...
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10/26/2022
How precise are performance estimates for typical medical image segmentation tasks?
An important issue in medical image processing is to be able to estimate...
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09/12/2022
Reproducibility in machine learning for medical imaging
Reproducibility is a cornerstone of science, as the replication of findi...
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04/14/2022
Interpretability of Machine Learning Methods Applied to Neuroimaging
Deep learning methods have become very popular for the processing of nat...
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09/08/2021
Axial multi-layer perceptron architecture for automatic segmentation of choroid plexus in multiple sclerosis
Choroid plexuses (CP) are structures of the ventricles of the brain whic...
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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 ...
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03/19/2020
Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort
BACKGROUND:Automated volumetry software (AVS) has recently become widely...
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03/11/2020
Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Gaussian Graphical Models (GGM) are often used to describe the condition...
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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...
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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...
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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...
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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...
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04/21/2018
Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training
Multiple sclerosis (MS) is a demyelinating disease of the central nervou...
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03/27/2018
Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms
We propose a method to learn a distribution of shape trajectories from l...
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11/23/2017
Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline
We propose a method to predict the subject-specific longitudinal progres...
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10/10/2017
Multilevel Modeling with Structured Penalties for Classification from Imaging Genetics data
In this paper, we propose a framework for automatic classification of pa...
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09/25/2017
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks
We introduce a mixed-effects model to learn spatiotempo-ral patterns on ...
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09/21/2017
Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease
In recent years, the number of papers on Alzheimer's disease classificat...
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09/18/2017
Multi-modal analysis of genetically-related subjects using SIFT descriptors in brain MRI
So far, fingerprinting studies have focused on identifying features from...
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09/18/2017
White Matter Fiber Segmentation Using Functional Varifolds
The extraction of fibers from dMRI data typically produces a large numbe...
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07/19/2017