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Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss
Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) ...
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Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention
Radiotherapy is the main treatment modality for nasopharynx cancer. Deli...
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Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning
Despite that deep learning has achieved state-of-the-art performance for...
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One-Shot Object Localization in Medical Images based on Relative Position Regression
Deep learning networks have shown promising performance for accurate obj...
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Semi-supervised Segmentation via Uncertainty Rectified Pyramid Consistency and Its Application to Gross Target Volume of Nasopharyngeal Carcinoma
Gross Target Volume (GTV) segmentation plays an irreplaceable role in ra...
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Learning Euler's Elastica Model for Medical Image Segmentation
Image segmentation is a fundamental topic in image processing and has be...
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Semi-supervised Medical Image Segmentation through Dual-task Consistency
Deep learning-based semi-supervised learning (SSL) algorithms have led t...
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Automatic Ischemic Stroke Lesion Segmentation from Computed Tomography Perfusion Images by Image Synthesis and Attention-Based Deep Neural Networks
Ischemic stroke lesion segmentation from Computed Tomography Perfusion (...
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Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation
The segmentation of coronary arteries in X-ray angiograms by convolution...
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SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualization
Clinical research on smart healthcare has an increasing demand for intel...
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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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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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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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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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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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