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| 1 | A Memetic Algorithm Based Feature Weighting for Metabolomics Data Classification显示文摘A metaheuristic chain based memetic algorithm namely MCMA is proposed for the classification of metabolomics data. MCMA regards both global evolution and local search as equivalent elemental metaheuristics,and searches with a chain of metaheuristics performed alternatively on the target problem. A hidden Markov model based scheduling mechanism is employed in MCMA for the selection of metaheuristics. By using MCMA for optimizing the linkage weight vector, a feature weighting algorithm for metabolomics data is formed to identify relevant metabolite features and reveal their exact relationships with the given physiological states. An extreme learning machine based classifier is utilized in predicting the physiological states according to the weighted metabolite features. Experimental results on real metabolomics data of clinical liver transplantation demonstrate that the proposed feature weighting and classification method obtains better performance than the other compared algorithms. | ZHOU Jiarui ZHU Zexuan JI Zhen | 2014 | Chinese Journal of Electronics2014，23，4： | 5 |
| 2 | A momentbased nonlocal-means algorithm for image denoising显示文摘 | Ji Zexuan Chen Qiang Sun Quansen | 2009 | Information Processing Letters2009，109，2324： | 1 |
| 3 | Fuzzy C -means clustering with weighted image patch for image segmentation 显示文摘 | Ji Zexuan Xia Yong Chen Qiang | 2012 | Applied Soft Computing2012，12，6： | 1 |
| 4 | Generalized rough fuzzy c-means algorithm for brain MR image segmentation显示文摘 | Zexuan Ji Quansen Sun Yong Xia Qiang Chen Deshen Xia Dagan Feng | 2011 | Computer Methods and Programs in Biomedicine2011，，2： | 1 |
| 5 | Fuzzy local Gaussian mixture model for brain MR image segmentation 显示文摘 | Zexuan Ji Yong Xia | 2012 | IEEE Transactions on In- formation Technology in Biomedicine2012，2，5： | 1 |
| 6 | Fractional-order Sparse Representation for Image Denoising显示文摘Sparse representation models have been shown promising results for image denoising. However, conventional sparse representation-based models cannot obtain satisfactory estimations for sparse coefficients and the dictionary. To address this weakness, in this paper, we propose a novel fractional-order sparse representation(FSR) model. Specifically, we cluster the image patches into K groups, and calculate the singular values for each clean/noisy patch pair in the wavelet domain. Then the uniform fractional-order parameters are learned for each cluster.Then a novel fractional-order sample space is constructed using adaptive fractional-order parameters in the wavelet domain to obtain more accurate sparse coefficients and dictionary for image denoising. Extensive experimental results show that the proposed model outperforms state-of-the-art sparse representation-based models and the block-matching and 3D filtering algorithm in terms of denoising performance and the computational efficiency. | Leilei Geng Zexuan Ji Yunhao Yuan Yilong Yin | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，2： | 1 |
| 7 | A modified pos- sibifistic fuzzy C-means clustering algorithm for bias field estimation and segmentation of brain MR image 显示文摘 | ji Zexuan Sun Quansen Xia Deshen | 2011 | Computerized Medical Imaging and Graphics2011，35，5： | 1 |
| 8 | A moment-based Nonlocal-means Algorithm for Image Denoising显示文摘 | Ji Zexuan Chen Qiang Sun Quansen | | 0，，11： | 1 |
| 9 | A framework with modified fast FCM for brain MR images segmentation 显示文摘 | Ji Zexuan Sun Quansen Xia Deshen | 2011 | Pattern Recognition2011，5，44： | 1 |
| 10 | A Modified Possibilistic Fuzzy C-means Clustering Algorithm for Bias Field Estimation and Segmentation of Brain MR Image显示文摘 | JI Zexuan SUN Quansen XIA Deshen | 2001 | Computerzed Medical Imaging and Graphics2001，35，： | 1 |
| 11 | A framework with modified fast FCM for brain MR images segmentation显示文摘 | Ji Zexuan Sun Quansen | 2011 | Pattern Recogni- tion2011，44，5： | 1 |
| 12 | A moment-based nonlocal-means algorithm for image denoising 显示文摘 | JI Zexuan CHEN Qiang SUN Quansen | 2009 | Information Processing Letters(S0020-0190)2009，109，9： | 1 |
| 13 | A moment- based nonlocal-means algorithm for image denoising显示文摘 | JI ZEXUAN CHEN QIANG SUN QUAN-SEN | 2009 | Information Processing Letters2009，109，2324： | 1 |
| 14 | Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment显示文摘Perceptual image quality assessment(IQA)is one of the most indispensable yet challenging problems in image processing and computer vision.It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation.To further improve the prediction accuracy for the distortion of color images,in this paper,we propose a novel effective and efficient IQA model,called perceptual gradient similarity deviation(PGSD).Based on the gradient magnitude similarity,we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient.The luminance and chrominance channels are both took into account to characterize the quality degradation caused by intensity and color distortions.Finally,a multi-scale strategy is utilized and pooled with different weights to incorporate image details at different resolutions.Experimental results on LIVE,CSIQ and TID2013 databases demonstrate the superior performances of the proposed algorithm. | Manyu Jin Tao Wang Zexuan Ji Xiaobo Shen | 2018 | Computers, Materials & Continua2018，，9： | 1 |
| 15 | Elevated Kir2.1/nuclear N2ICD defines a highly malignant subtype of non-WNT/SHH medulloblastomas显示文摘Medulloblastoma(MB)is one of the most common childhood malignant brain tumors(WHO grade IV),traditionally divided into WNT,SHH,Group 3,and Group 4 subgroups based on the transcription profiles,somatic DNA alterations,and clinical outcomes.Unlike WNT and SHH subgroup MBs,Group 3 and Group 4 MBs have similar transcriptomes and lack clearly specific drivers and targeted therapeutic options.The recently revised WHO Classification of CNS Tumors has assigned Group 3 and 4 to a provisional non-WNT/SHH entity.In the present study,we demonstrate that Kir2.1,an inwardly-rectifying potassium channel,is highly expressed in non-WNT/SHH MBs,which promotes tumor cell invasion and metastasis by recruiting Adam10 to enhance S2 cleavage of Notch2 thereby activating the Notch2 signaling pathway.Disruption of the Notch2 pathway markedly inhibited the growth and metastasis of Kir2.1-overexpressing MB cell-derived xenograft tumors in mice.Moreover,Kir2.1^(high)/nuclear N2ICD^(high)MBs are associated with the significantly shorter lifespan of the patients.Thus,Kir2.1^(high)/nuclear N2ICD^(high)can be used as a biomarker to define a novel subtype of non-WNT/SHH MBs.Our findings are important for the modification of treatment regimens and the development of novel-targeted therapies for non-WNT/SHH MBs. | Yan-Xia Wang Haibo Wu Yong Ren Shengqing Lv Chengdong Ji Dongfang Xiang Mengsi Zhang Huimin Lu Wenjuan Fu Qing Liu Zexuan Yan Qinghua Ma Jingya Miao Ruili Cai Xi Lan Bin Wu Wenying Wang Yinhua Liu Dai-Zhong Wang Mianfu Cao Zhicheng He Yu Shi Yifang Ping Xiaohong Yao Xia Zhang Peng Zhang Ji Ming Wang Yan Wang Youhong Cui Xiu-Wu Bian | 2022 | Signal Transduction and Targeted Therapy2022，7，4： | 0 |
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