-
Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging
Detecting acoustic shadows in ultrasound images is important in many cli...
11/20/2018 ∙ by Qingjie Meng, et al. ∙
20
∙
share
read it
-
Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling
Alterations in the geometry and function of the heart define well-establ...
07/18/2018 ∙ by Carlo Biffi, et al. ∙
8
∙
share
read it
-
Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging
Recent advances in deep learning led to novel generative modeling techni...
06/14/2018 ∙ by Xiaoran Chen, et al. ∙
4
∙
share
read it
-
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
NeuroNet is a deep convolutional neural network mimicking multiple popul...
06/11/2018 ∙ by Martin Rajchl, et al. ∙
8
∙
share
read it
-
DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images
We present DLTK, a toolkit providing baseline implementations for effici...
11/18/2017 ∙ by Nick Pawlowski, et al. ∙
0
∙
share
read it
-
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
11/04/2017 ∙ by Konstantinos Kamnitsas, et al. ∙
0
∙
share
read it
-
Implicit Weight Uncertainty in Neural Networks
We interpret HyperNetworks within the framework of variational inference...
11/03/2017 ∙ by Nick Pawlowski, et al. ∙
0
∙
share
read it
-
Human-level CMR image analysis with deep fully convolutional networks
Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...
10/25/2017 ∙ by Wenjia Bai, et al. ∙
0
∙
share
read it
-
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
Evaluating similarity between graphs is of major importance in several c...
03/07/2017 ∙ by Ira Ktena, et al. ∙
0
∙
share
read it
-
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
In this paper we present a novel method for the correction of motion art...
11/22/2016 ∙ by Amir Alansary, et al. ∙
0
∙
share
read it
-
Learning under Distributed Weak Supervision
The availability of training data for supervision is a frequently encoun...
06/03/2016 ∙ by Martin Rajchl, et al. ∙
0
∙
share
read it
-
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks
In this paper, we propose DeepCut, a method to obtain pixelwise object s...
05/25/2016 ∙ by Martin Rajchl, et al. ∙
0
∙
share
read it
-
A Proximal Bregman Projection Approach to Continuous Max-Flow Problems Using Entropic Distances
One issue limiting the adaption of large-scale multi-region segmentation...
01/30/2015 ∙ by John S. H. Baxter, et al. ∙
0
∙
share
read it
-
A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization
The incorporation of region regularization into max-flow segmentation ha...
05/05/2014 ∙ by John S. H. Baxter, et al. ∙
0
∙
share
read it
