Search Results - "Liu, Mingxia"

Domain Adaptation for Medical Image Analysis: A Survey by Guan, Hao, Liu, Mingxia

“…Machine learning techniques used in computer-aided medical image analysis usually suffer from the domain shift problem caused by different distributions…”
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Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks by Zhang, Jun, Liu, Mingxia, Shen, Dinggang

“…One of the major challenges in anatomical landmark detection, based on deep neural networks, is the limited availability of medical imaging data for network…”
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Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment by Liu, Mingxia, Zhang, Daoqiang, Shen, Dinggang

“…As shown in the literature, methods based on multiple templates usually achieve better performance, compared with those using only a single template for…”
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Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease by Jie, Biao, Liu, Mingxia, Shen, Dinggang

“…•A new measure to characterize the spatial variability of DCN is proposed.•A novel learning framework to integrate both temporal and spatial variabilities of…”
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Microglia in depression: an overview of microglia in the pathogenesis and treatment of depression by Wang, Haixia, He, Yi, Sun, Zuoli, Ren, Siyu, Liu, Mingxia, Wang, Gang, Yang, Jian

“…Major depressive disorder is a highly debilitating psychiatric disorder involving the dysfunction of different cell types in the brain. Microglia are the…”
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DomainATM: Domain adaptation toolbox for medical data analysis by Guan, Hao, Liu, Mingxia

“…•An open-source platform (DomainATM) for domain adaptation in medical imaging.•Fast facilitation and customization of domain adaptation for medical data.•Both…”
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Joint Binary Classifier Learning for ECOC-Based Multi-Class Classification by Liu, Mingxia, Zhang, Daoqiang, Chen, Songcan, Xue, Hui

“…Error-correcting output coding (ECOC) is one of the most widely used strategies for dealing with multi-class problems by decomposing the original multi-class…”
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Pairwise Constraint-Guided Sparse Learning for Feature Selection by Liu, Mingxia, Zhang, Daoqiang

“…Feature selection aims to identify the most informative features for a compact and accurate data representation. As typical supervised feature selection…”
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View-centralized multi-atlas classification for Alzheimer's disease diagnosis by Liu, Mingxia, Zhang, Daoqiang, Shen, Dinggang

“…Multi‐atlas based methods have been recently used for classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment…”
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The effect of ultrasonic surface rolling process on the fretting fatigue property of GH4169 superalloy by Yang, Jing, Liu, Daoxin, Zhang, Xiaohua, Liu, Mingxia, Zhao, Weidong, Liu, Chengsong

“…•The fretting fatigue performance is significantly improved by USRP treatment.•The gradient nanostructure is formed on the surface of USRP sample.•The…”
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Strength and similarity guided group-level brain functional network construction for MCI diagnosis by Zhang, Yu, Zhang, Han, Chen, Xiaobo, Liu, Mingxia, Zhu, Xiaofeng, Lee, Seong-Whan, Shen, Dinggang

“…Sparse representation-based brain functional network modeling often results in large inter-subject variability in the network structure. This could reduce the…”
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Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification by Guan, Hao, Liu, Yunbi, Yang, Erkun, Yap, Pew-Thian, Shen, Dinggang, Liu, Mingxia

“…•An unsupervised domain adaptation framework for brain disorder identification.•Avoid the demand for labeled target data for training.•Automatically locate…”
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Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease by Jie, Biao, Liu, Mingxia, Liu, Jun, Zhang, Daoqiang, Shen, Dinggang

“…Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild…”
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Stepwise extraction of valuable components from red mud based on reductive roasting with sodium salts by Li, Guanghui, Liu, Mingxia, Rao, Mingjun, Jiang, Tao, Zhuang, Jinqiang, Zhang, Yuanbo

“…•An integrated route for comprehensive utilization of red mud was proposed.•Sodium salts are favorable to the magnetic separation and acid leaching…”
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Two-Stage Cost-Sensitive Learning for Software Defect Prediction by Liu, Mingxia, Miao, Linsong, Zhang, Daoqiang

“…Software defect prediction (SDP), which classifies software modules into defect-prone and not-defect-prone categories, provides an effective way to maintain…”
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First-year development of modules and hubs in infant brain functional networks by Wen, Xuyun, Zhang, Han, Li, Gang, Liu, Mingxia, Yin, Weiyan, Lin, Weili, Zhang, Jun, Shen, Dinggang

“…The human brain develops rapidly in the first postnatal year, in which rewired functional brain networks could shape later behavioral and cognitive…”
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Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research by Liu, Mingxia, Ma, Wen, He, Yi, Sun, Zuoli, Yang, Jian

“…Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass…”
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A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis by Zhang, Li, Wang, Mingliang, Liu, Mingxia, Zhang, Daoqiang

“…Deep learning has recently been used for the analysis of neuroimages, such as structural magnetic resonance imaging (MRI), functional MRI, and positron…”
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Attribute relation learning for zero-shot classification by Liu, Mingxia, Zhang, Daoqiang, Chen, Songcan

“…In computer vision and pattern recognition communities, one often-encountered problem is that the limited labeled training data are not enough to cover all the…”
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Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification by Zhang, Yangyang, Jiang, Xiao, Qiao, Lishan, Liu, Mingxia

“…Function brain network (FBN) analysis has shown great potential in identifying brain diseases, such as Alzheimer's disease (AD) and its prodromal stage, namely…”
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