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02/23/2022
Augmentation based unsupervised domain adaptation
The insertion of deep learning in medical image analysis had lead to the...
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06/04/2020
Uncertainty quantification in medical image segmentation with Normalizing Flows
Medical image segmentation is inherently an ambiguous task due to factor...
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05/20/2020
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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04/29/2020
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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12/22/2019
On the Initialization of Long Short-Term Memory Networks
Weight initialization is important for faster convergence and stability ...
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11/05/2019
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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08/16/2019
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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08/16/2019
Knowledge distillation for semi-supervised domain adaptation
In the absence of sufficient data variation (e.g., scanner and protocol ...
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08/14/2019
Robust parametric modeling of Alzheimer's disease progression
Quantitative characterization of disease progression using longitudinal ...
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03/17/2019
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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10/03/2018
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
For proper generalization performance of convolutional neural networks (...
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08/20/2018
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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08/16/2018
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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01/08/2018
Boundary Optimizing Network (BON)
Despite all the success that deep neural networks have seen in classifyi...
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09/19/2017
Deep-Learnt Classification of Light Curves
Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...
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12/16/2016
A Stochastic Large Deformation Model for Computational Anatomy
In the study of shapes of human organs using computational anatomy, vari...
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04/18/2016