Search Results - "Xiahai Zhuang"
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Disentangle domain features for cross-modality cardiac image segmentation
Published in Medical image analysis (01-07-2021)“…•Disentangling domain features for cross-modality cardiac image segmentation.•Implementing unsupervised domain adaptation on both feature and image…”
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Diagnosis of Alzheimer's Disease via Multi-Modality 3D Convolutional Neural Network
Published in Frontiers in neuroscience (31-05-2019)“…Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. In the last decade, studies on AD diagnosis has attached great significance to…”
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Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge
Published in Medical image analysis (01-12-2019)“…•This work presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart…”
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PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network at Unpaired Cross-Modality Cardiac Segmentation
Published in IEEE access (2019)“…Deep convolutional networks have demonstrated state-of-the-art performance on various challenging medical image processing tasks. Leveraging images from…”
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A Registration-Based Propagation Framework for Automatic Whole Heart Segmentation of Cardiac MRI
Published in IEEE transactions on medical imaging (01-09-2010)“…Magnetic resonance (MR) imaging has become a routine modality for the determination of patient cardiac morphology. The extraction of this information can be…”
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A Nonrigid Registration Framework Using Spatially Encoded Mutual Information and Free-Form Deformations
Published in IEEE transactions on medical imaging (01-10-2011)“…Mutual information (MI) registration including spatial information has been shown to perform better than the traditional MI measures for certain nonrigid…”
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Automatic infection detection based on electronic medical records
Published in BMC bioinformatics (11-04-2018)“…Making accurate patient care decision, as early as possible, is a constant challenge, especially for physicians in the emergency department. The increasing…”
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Multivariate Mixture Model for Myocardial Segmentation Combining Multi-Source Images
Published in IEEE transactions on pattern analysis and machine intelligence (01-12-2019)“…The author proposes a method for simultaneous registration and segmentation of multi-source images, using the multivariate mixture model (MvMM) and maximum of…”
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SeRN: A Two-Stage Framework of Registration for Semi-Supervised Learning for Medical Images
Published in Shanghai jiao tong da xue xue bao (01-04-2022)“…Significant breakthroughs in medical image registration have been achieved using deep neural networks (DNNs). However, DNN-based end-to-end registration…”
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A Comprehensive Cardiac Motion Estimation Framework Using Both Untagged and 3-D Tagged MR Images Based on Nonrigid Registration
Published in IEEE transactions on medical imaging (01-06-2012)“…In this paper, we present a novel technique based on nonrigid image registration for myocardial motion estimation using both untagged and 3-D tagged MR images…”
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A Fully Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images
Published in Frontiers in neuroscience (23-08-2019)“…Parkinson's disease (PD) is a prevalent long-term neurodegenerative disease. Though the criteria of PD diagnosis are relatively well defined, current…”
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Editorial: Radiopharmaceuticals, Imaging Techniques and Clinical Applications in Neurodegenerative Diseases
Published in Frontiers in neurology (04-09-2019)Get full text
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Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI
Published in Medical image analysis (01-07-2016)“…•Multi-scale patch is proposed for hierarchical local atlas ranking.•A multi-modality multi-atlas scheme is developed for whole heart segmentation.•A…”
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Computer-Aided Classification Framework of Parkinsonian Disorders Using 11C-CFT PET Imaging
Published in Frontiers in aging neuroscience (01-02-2022)“…Purpose To investigate the usefulness of a novel computer-aided classification framework for the differential diagnosis of parkinsonian disorders (PDs) based…”
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CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI
Published in Scientific data (25-06-2024)“…Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow…”
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Unsupervised Domain Adaptation With Variational Approximation for Cardiac Segmentation
Published in IEEE transactions on medical imaging (01-12-2021)“…Unsupervised domain adaptation is useful in medical image segmentation. Particularly, when ground truths of the target images are not available, domain…”
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CF Distance: A New Domain Discrepancy Metric and Application to Explicit Domain Adaptation for Cross-Modality Cardiac Image Segmentation
Published in IEEE transactions on medical imaging (01-12-2020)“…Domain adaptation has great values in unpaired cross-modality image segmentation, where the training images with gold standard segmentation are not available…”
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Minimizing Estimated Risks on Unlabeled Data: A New Formulation for Semi-Supervised Medical Image Segmentation
Published in IEEE transactions on pattern analysis and machine intelligence (01-05-2023)“…Supervised segmentation can be costly, particularly in applications of biomedical image analysis where large scale manual annotations from experts are…”
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X-Metric: An N-Dimensional Information-Theoretic Framework for Groupwise Registration and Deep Combined Computing
Published in IEEE transactions on pattern analysis and machine intelligence (01-07-2023)“…This article presents a generic probabilistic framework for estimating the statistical dependency and finding the anatomical correspondences among an arbitrary…”
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A fully automatic deep learning method for atrial scarring segmentation from late gadolinium-enhanced MRI images
Published in 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) (01-04-2017)“…Precise and objective segmentation of atrial scarring (SAS) is a prerequisite for quantitative assessment of atrial fibrillation using non-invasive late…”
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