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Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation
Multi-modal medical image segmentation plays an essential role in clinic...
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Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
The recent outbreak of COVID-19 has led to urgent needs for reliable dia...
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LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
Deep Learning (DL) models are becoming larger, because the increase in m...
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Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Knowledge graph models world knowledge as concepts, entities, and the re...
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NeurReg: Neural Registration and Its Application to Image Segmentation
Registration is a fundamental task in medical image analysis which can b...
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Privacy-preserving Federated Brain Tumour Segmentation
Due to medical data privacy regulations, it is often infeasible to colle...
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Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets
Brain tissue segmentation from multimodal MRI is a key building block of...
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Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss
Automatic segmentation of vestibular schwannoma (VS) tumors from magneti...
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2017 Robotic Instrument Segmentation Challenge
In mainstream computer vision and machine learning, public datasets such...
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Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation
Automatic brain tumor segmentation plays an important role for diagnosis...
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Deep Boosted Regression for MR to CT Synthesis
Attenuation correction is an essential requirement of positron emission ...
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Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Despite the state-of-the-art performance for medical image segmentation,...
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Test-time augmentation with uncertainty estimation for deep learning-based medical image segmentation
Data augmentation has been widely used for training deep learning system...
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Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration
One of the fundamental challenges in supervised learning for multimodal ...
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Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Multi-task neural network architectures provide a mechanism that jointly...
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Interpretable Fully Convolutional Classification of Intrapapillary Capillary Loops for Real-Time Detection of Early Squamous Neoplasia
In this work, we have concentrated our efforts on the interpretability o...
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Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning
Convolutional neural networks (CNNs) have achieved state-of-the-art perf...
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NiftyNet: a deep-learning platform for medical imaging
Medical image analysis and computer-assisted intervention problems are i...
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Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations
Deep-learning has proved in recent years to be a powerful tool for image...
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On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task
Deep convolutional neural networks are powerful tools for learning visua...
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DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation
Accurate medical image segmentation is essential for diagnosis, surgical...
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Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks
The Dice score is widely used for binary segmentation due to its robustn...
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ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools
Real-time tool segmentation from endoscopic videos is an essential part ...
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Scalable multimodal convolutional networks for brain tumour segmentation
Brain tumour segmentation plays a key role in computer-assisted surgery....
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