Ozan Oktay

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Imperial College London

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Image-and-Spatial Transformer Networks for Structure-Guided Image Registration

Image registration with deep neural networks has become an active field ...
07/22/2019 ∙ by Matthew C. H. Lee, et al. ∙ 2 ∙ share

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Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling

Quantification of anatomical shape changes still relies on scalar global...
06/28/2019 ∙ by Carlo Biffi, et al. ∙ 1 ∙ share

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Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study

Background: The trend towards large-scale studies including population i...
01/27/2019 ∙ by Robert Robinson, et al. ∙ 38 ∙ share

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A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

In the clinical routine, short axis (SA) cine cardiac MR (CMR) image sta...
10/03/2018 ∙ by Giacomo Tarroni, et al. ∙ 8 ∙ share

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Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

We propose a novel attention gate (AG) model for medical image analysis ...
08/22/2018 ∙ by Jo Schlemper, et al. ∙ 6 ∙ share

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Recurrent neural networks for aortic image sequence segmentation with sparse annotations

Segmentation of image sequences is an important task in medical image an...
08/01/2018 ∙ by Wenjia Bai, et al. ∙ 6 ∙ share

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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

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Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction

Deep learning approaches have shown promising performance for compressed...
06/28/2018 ∙ by Maximilian Seitzer, et al. ∙ 4 ∙ share

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Real-time Prediction of Segmentation Quality

Recent advances in deep learning based image segmentation methods have e...
06/16/2018 ∙ by Robert Robinson, et al. ∙ 14 ∙ share

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Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

We propose a fully automatic method to find standardized view planes in ...
06/08/2018 ∙ by Amir Alansary, et al. ∙ 10 ∙ share

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Attention-Gated Networks for Improving Ultrasound Scan Plane Detection

In this work, we apply an attention-gated network to real-time automated...
04/15/2018 ∙ by Jo Schlemper, et al. ∙ 0 ∙ share

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Attention U-Net: Learning Where to Look for the Pancreas

We propose a novel attention gate (AG) model for medical imaging that au...
04/11/2018 ∙ by Ozan Oktay, et al. ∙ 0 ∙ share

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Learning-Based Quality Control for Cardiac MR Images

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...
03/25/2018 ∙ by Giacomo Tarroni, et al. ∙ 0 ∙ share

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TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

Deep convolutional neural networks (DCNN) are currently ubiquitous in me...
01/29/2018 ∙ by Mattias P. Heinrich, et al. ∙ 0 ∙ share

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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

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Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

Incorporation of prior knowledge about organ shape and location is key t...
05/22/2017 ∙ by Ozan Oktay, et al. ∙ 0 ∙ share

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Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging

3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast bu...
02/28/2017 ∙ by Steven McDonagh, et al. ∙ 0 ∙ share

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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

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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

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