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Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling
Machine learning has been widely adopted for medical image analysis in r...
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Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
Gliomas are the most common malignant brain tumourswith intrinsic hetero...
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Deep learning for cardiac image segmentation: A review
Deep learning has become the most widely used approach for cardiac image...
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Transfer Learning from Partial Annotations for Whole Brain Segmentation
Brain MR image segmentation is a key task in neuroimaging studies. It is...
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Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image
Accelerating the acquisition of magnetic resonance imaging (MRI) is a ch...
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Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
In this work, we present a fully automatic method to segment cardiac str...
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Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images
Cardiac MR image segmentation is essential for the morphological and fun...
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VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
In this work, we propose a deep learning approach for parallel magnetic ...
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Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
In the recent years, convolutional neural networks have transformed the ...
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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...
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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...
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Multi-Task Learning for Left Atrial Segmentation on GE-MRI
Segmentation of the left atrium (LA) is crucial for assessing its anatom...
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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...
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Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach
Deep learning approaches have achieved state-of-the-art performance in c...
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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...
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Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension
In this paper we introduce a novel and accurate optimisation method for ...
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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...
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Real-time Prediction of Segmentation Quality
Recent advances in deep learning based image segmentation methods have e...
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Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Cardiac motion estimation and segmentation play important roles in quant...
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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 ...
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Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy
The variations in multi-center data in medical imaging studies have brou...
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Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks
Measurement of head biometrics from fetal ultrasonography images is of k...
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Learning-Based Quality Control for Cardiac MR Images
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...
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Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Deep learning approaches such as convolutional neural nets have consiste...
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Human-level CMR image analysis with deep fully convolutional networks
Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...
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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...
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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...
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