Akshay Pai

is this you? claim profile

∙ 0 followers
Københavns Uni

Featured Co-authors

Sébastien Ourselin
57 publications
Ulas Bagci
51 publications
M. Jorge Cardoso
30 publications
Stefan Sommer
26 publications
Christian Igel
20 publications
Marc Modat
17 publications
Raghavendra Selvan
17 publications
Mads Nielsen
15 publications
Parashkev Nachev
14 publications
Mehmet Akcakaya
12 publications
Lauge Sørensen
12 publications

Uncertainty quantification in medical image segmentation with Normalizing Flows

Medical image segmentation is inherently an ambiguous task due to factor...
06/04/2020 ∙ by Raghavendra Selvan, et al. ∙ 15 ∙ share

read it
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

read it
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...
04/29/2020 ∙ by Arjun D. Desai, et al. ∙ 1 ∙ share

read it
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

read it
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 ...
11/05/2019 ∙ by Mathias Perslev, et al. ∙ 0 ∙ share

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Boundary Optimizing Network (BON)

Despite all the success that deep neural networks have seen in classifyi...
01/08/2018 ∙ by Marco Singh, et al. ∙ 0 ∙ share

read it
Deep-Learnt Classification of Light Curves

Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...
09/19/2017 ∙ by Ashish Mahabal, et al. ∙ 0 ∙ share

read it
A Stochastic Large Deformation Model for Computational Anatomy

In the study of shapes of human organs using computational anatomy, vari...
12/16/2016 ∙ by Alexis Arnaudon, et al. ∙ 0 ∙ share

read it
Most Likely Separation of Intensity and Warping Effects in Image Registration

This paper introduces a class of mixed-effects models for joint modeling...
04/18/2016 ∙ by Line Kuhnel, et al. ∙ 0 ∙ share

read it