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Featured Co-authors

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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...

0 Mauricio Orbes-Arteaga, et al. ∙

∙ 06/04/2020

Uncertainty quantification in medical image segmentation with Normalizing Flows

Medical image segmentation is inherently an ambiguous task due to factor...

15 Raghavendra Selvan, et al. ∙

∙ 05/20/2020

Lung Segmentation from Chest X-rays using Variational Data Imputation

Pulmonary opacification is the inflammation in the lungs caused by many ...

14 Raghavendra Selvan, et al. ∙

∙ 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...

1 Arjun Desai, et al. ∙

∙ 12/22/2019

On the Initialization of Long Short-Term Memory Networks

Weight initialization is important for faster convergence and stability ...

28 Mostafa Mehdipour Ghazi, et al. ∙

∙ 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 ...

0 Mathias Perslev, et al. ∙

∙ 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...

6 Mauricio Orbes-Arteaga, et al. ∙

∙ 08/16/2019

Knowledge distillation for semi-supervised domain adaptation

In the absence of sufficient data variation (e.g., scanner and protocol ...

1 Mauricio Orbes-Arteaga, et al. ∙

∙ 08/14/2019

Robust parametric modeling of Alzheimer's disease progression

Quantitative characterization of disease progression using longitudinal ...

0 Mostafa Mehdipour Ghazi, et al. ∙

∙ 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...

10 Mostafa Mehdipour Ghazi, et al. ∙

∙ 10/03/2018

PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation

For proper generalization performance of convolutional neural networks (...

4 Mauricio Orbes-Arteaga, et al. ∙

∙ 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...

0 Mauricio Orbes-Arteaga, et al. ∙

∙ 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...

0 Mostafa Mehdipour Ghazi, et al. ∙

∙ 01/08/2018

Boundary Optimizing Network (BON)

Despite all the success that deep neural networks have seen in classifyi...

0 Marco Singh, et al. ∙

∙ 09/19/2017

Deep-Learnt Classification of Light Curves

Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...

0 Ashish Mahabal, et al. ∙

∙ 12/16/2016

A Stochastic Large Deformation Model for Computational Anatomy

In the study of shapes of human organs using computational anatomy, vari...

0 Alexis Arnaudon, et al. ∙

∙ 04/18/2016

Most Likely Separation of Intensity and Warping Effects in Image Registration

This paper introduces a class of mixed-effects models for joint modeling...

0 Line Kuhnel, et al. ∙

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