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Uncertainty quantification in medical image segmentation with Normalizing Flows
Medical image segmentation is inherently an ambiguous task due to factor...
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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 ...
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The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset
Purpose: To organize a knee MRI segmentation challenge for characterizin...
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On the Initialization of Long Short-Term Memory Networks
Weight initialization is important for faster convergence and stability ...
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One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation
Many recent medical segmentation systems rely on powerful deep learning ...
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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...
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Knowledge distillation for semi-supervised domain adaptation
In the absence of sufficient data variation (e.g., scanner and protocol ...
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Robust parametric modeling of Alzheimer's disease progression
Quantitative characterization of disease progression using longitudinal ...
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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...
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PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
For proper generalization performance of convolutional neural networks (...
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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...
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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...
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Boundary Optimizing Network (BON)
Despite all the success that deep neural networks have seen in classifyi...
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Deep-Learnt Classification of Light Curves
Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...
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A Stochastic Large Deformation Model for Computational Anatomy
In the study of shapes of human organs using computational anatomy, vari...
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Most Likely Separation of Intensity and Warping Effects in Image Registration
This paper introduces a class of mixed-effects models for joint modeling...
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