Mads Nielsen

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Københavns Uni

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Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts

Multimodal generative models should be able to learn a meaningful latent...
01/18/2021 ∙ by Svetlana Kutuzova, et al. ∙ 23 ∙ share

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Lung Segmentation from Chest X-rays using Variational Data Imputation

Pulmonary opacification is the inflammation in the lungs caused by many ...
05/20/2020 ∙ by Raghavendra Selvan, et al. ∙ 14 ∙ share

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The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

We present the findings of "The Alzheimer's Disease Prediction Of Longit...
02/09/2020 ∙ by Razvan V. Marinescu, et al. ∙ 0 ∙ share

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On the Initialization of Long Short-Term Memory Networks

Weight initialization is important for faster convergence and stability ...
12/22/2019 ∙ by Mostafa Mehdipour Ghazi, et al. ∙ 28 ∙ share

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Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning

Supervised learning algorithms trained on medical images will often fail...
08/16/2019 ∙ by Mauricio Orbes-Arteaga, et al. ∙ 6 ∙ share

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Knowledge distillation for semi-supervised domain adaptation

In the absence of sufficient data variation (e.g., scanner and protocol ...
08/16/2019 ∙ by Mauricio Orbes-Arteaga, et al. ∙ 1 ∙ share

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Robust parametric modeling of Alzheimer's disease progression

Quantitative characterization of disease progression using longitudinal ...
08/14/2019 ∙ by Mostafa Mehdipour Ghazi, et al. ∙ 0 ∙ share

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Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modeling

Disease progression modeling (DPM) using longitudinal data is a challeng...
03/17/2019 ∙ by Mostafa Mehdipour Ghazi, et al. ∙ 10 ∙ share

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PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation

For proper generalization performance of convolutional neural networks (...
10/03/2018 ∙ by Mauricio Orbes-Arteaga, et al. ∙ 4 ∙ share

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On Variational Methods for Motion Compensated Inpainting

We develop in this paper a generic Bayesian framework for the joint esti...
09/21/2018 ∙ by François Lauze, et al. ∙ 0 ∙ share

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Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs

Segmenting vascular pathologies such as white matter lesions in Brain ma...
08/20/2018 ∙ by Mauricio Orbes-Arteaga, et al. ∙ 0 ∙ share

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Robust training of recurrent neural networks to handle missing data for disease progression modeling

Disease progression modeling (DPM) using longitudinal data is a challeng...
08/16/2018 ∙ by Mostafa Mehdipour Ghazi, et al. ∙ 0 ∙ share

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Convolutional neural networks for segmentation and object detection of human semen

We compare a set of convolutional neural network (CNN) architectures for...
04/03/2017 ∙ by Malte Stær Nissen, et al. ∙ 0 ∙ share

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Towards a theory of statistical tree-shape analysis

In order to develop statistical methods for shapes with a tree-structure...
07/23/2012 ∙ by Aasa Feragen, et al. ∙ 0 ∙ share

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Higher-Order Momentum Distributions and Locally Affine LDDMM Registration

To achieve sparse parametrizations that allows intuitive analysis, we ai...
12/14/2011 ∙ by Stefan Sommer, et al. ∙ 0 ∙ share

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