Yong Yang

Tianjin Polytechnic University

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i-10 index

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Shuying Huang

Tianjin Polytechnic University

102

Weiguo Wan

Jiangxi University of Finance and Economics

Pan Lin

Hunan Normal University

Wei Tu

Jiangxi Science and Technology Normal University

Hangyuan Lu

Jinhua Polytechnic

Junfeng Gao

State Ethnic Affairs Commission

Yuming Fang

Jiangxi University of Finance and Economics

Yue Que

East China Jiaotong University

Nini Rao

University of Electronic Science and Technology of China

Zhijun Fang

Shanghai University of Engineering Science

Cooperative Institutions

Jiangxi University of Finance and Economics

Chinese Academy of Sciences

Huazhong University of Science and Technology

University of Chinese Academy of Sciences

Peking University

Zhejiang University

University of Science and Technology of China

Xi'an Jiaotong University

Hangzhou Dianzi University

Shanghai Jiao Tong University

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Image Segmentation by Fuzzy C-Means Clustering Algorithm with a Novel Penalty Term

Computing and Informatics / Computers and Artificial Intelligence (2007)

Yong Yang Shuying Huang

To overcome the noise sensitiveness of conventional fuzzy c-means (FCM) clustering algorithm, a novel extended FCM algorithm for image segmentation is presented in this paper. The algorithm is developed by modifying the objective function of the standard FCM algorithm with a penalty term that takes into account the influence of the neighboring pixels on the centre pixels. The penalty term acts as a regularizer in this algorithm, which is inspired from the neighborhood expectation maximization algorithm and is modified in order to satisfy the criterion of the FCM algorithm. The performance of our algorithm is discussed and compared to those of many derivatives of FCM algorithm. Experimental results on segmentation of synthetic and real images demonstrate that the proposed algorithm is effective and robust.

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Citations (152)

Radiation Exposure for Patients and Staff during Different Interventional Procedures Using Anthropomorphic Phantoms: A Complete Evaluation of Different Body Regions.

PubMed (2023)

Zhi Xin Zhao Pei Yi Qian Hai Hua Wang Qian Qian Yong Yang

10.3967/bes2023.156

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Citations (0)

Multimodal Medical Image Fusion Based on Weighted Local Energy Matching Measurement and Improved Spatial Frequency

IEEE Transactions on Instrumentation and Measurement (2020)

Yong Yang Sihua Cao Shuying Huang Weiguo Wan

Multimodal medical image fusion (MMIF) technology can effectively improve the efficiency and accuracy of doctors in clinical diagnosis and treatment by combining different modes of medical images into a medical image with rich information. To achieve an optimal balance between computational loss and fusion quality, this article presents a new MMIF method based on weighted local energy matching measurement (WLEMM) and improved spatial frequency (SF). First, the latent low-rank representation (LatLRR) is employed to learn a decomposition matrix that is applied to decompose a source image into its base part and saliency part. Then, in order to adaptively select a fusion strategy for the base part, we propose a novel fusion rule, namely WLEMM, which is constructed by calculating the matching degree between the corresponding pixels of the base parts. Meanwhile, after considering the characteristics of the main diagonal SF and the secondary diagonal SF, a fusion strategy based on improved SF and L2 norm is designed to merge saliency parts. Finally, the fused image is obtained by combining the fused base part and saliency part. Various experiments on multiple groups of medical images demonstrate that the proposed method has superior performance compared with the state-of-the-art fusion methods, in subjective visual and objective index evaluations. Furthermore, the research work of this article is helpful for further detection and segmentation of medical images.

10.1109/tim.2020.3046911

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Citations (17)

Practical remote sensing image fusion method based on guided filter and improved SML in the NSST domain

Signal Image and Video Processing (2018)

Weiguo Wan Yong Yang Hyo Jong Lee

Panchromatic film

Fusion rules

10.1007/s11760-018-1240-x

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Citations (17)

Computer Vision in Healthcare Applications

Journal of Healthcare Engineering (2018)

Junfeng Gao Yong Yang Pan Lin Dong Sun Park

The research of computer vision, imaging processing and pattern recognition has made substantial progress during the past several decades.Also, medical imaging has attracted increasing attention in recent years due to its vital component in healthcare applications.Investigators have published a wealth of basic science and data documenting the progress and healthcare application on medical imaging.Since the development of these research fields has set the clinicians to advance from the bench to the bedside, the Journal of Healthcare Engineering set out to publish this special issue devoted to the topic of advanced computer vision methods for healthcare engineering, as well as review articles that will stimulate the continuing efforts to understand the problems usually encountered in this field.The result is a collection of fifteen outstanding articles submitted by investigators.Following the goal of special issue, we identify four major domains covered by the papers.The first is medical image analysis for healthcare, the second is the computer vision for predictive analytics and therapy, the third is fundamental algorithms for medical images, and the last one focuses on the machine learning algorithms for medical images.Here, we give the review of these published papers.

Publication

10.1155/2018/5157020

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Citations (92)

Pansharpening Based on Fuzzy Logic and Edge Activity

IEEE Geoscience and Remote Sensing Letters (2024)

Huan Dai Yong Yang Shuying Huang Weiguo Wan Hangyuan Lu

Pansharpening technology aims to extract spatial information from a panchromatic (PAN) image and integrate it into a multispectral (MS) image to generate a high-spatial resolution MS image. To overcome the problem of spatial and spectral distortion of traditional methods, this letter presents a pansharpening method based on fuzzy logic and edge activity. To obtain more accurate spatial details of source images, details extracted using the component substitution and multiresolution analysis methods are fused via the proposed fuzzy logic algorithm. To preserve the edges of the fusion result, the edge maps of the source images are detected and fused based on the edge activity. The optimized detail maps are obtained by multiplying the fused details and edge maps, which are then injected into the upsampled MS image to obtain the final pansharpened image. Reduced- and full-scale experimental results on the Pléiades and IKONOS datasets demonstrate the effectiveness of our method compared with state-of-the-art pansharpening algorithms. Specifically, the proposed method improves the ERGAS metrics by 9.0% and 11.1% compared to the second-best comparison approach on Pléiades and IKONOS, respectively.

10.1109/lgrs.2024.3356600

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Citations (2)

Single-point Residual Correction Method for Articulated Arm Coordinate Measuring Machine Based on Pose Configuration's polynomial model

You Xu Qun Gao Limin Yu Yong Yang

Due to the dynamic factor effect in different measuring configuration, the measurement accuracy of the articulated arm coordinate measuring machine (AACMM) is associated with the measuring configuration. A residual correction method based on polynomial model was proposed for single-point measurement. In order to build the polynomial model, the relationship between the AACMM's joint angles and probe coordinates in cylindrical coordinate system was investigated and the polynomial model was established. The calibration work was carried out by data collection in the workspace of AACMM, and the polynomial coefficient can be calculated. The experiments showed that the proposed method was effective and correct, and can meet the measurement requirements.

Coordinate-measuring machine

Work space

10.1109/cyber.2017.8446573

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Citations (1)

Should simultaneous ureteral reimplantation be performed during sigmoid bladder augmentation to reduce vesicoureteral reflux in neurogenic bladder cases?

International Urology and Nephrology (2015)

Peng Zhang Yong Yang Zhijin Wu Ning Zhang Chaohua Zhang

Bladder augmentation

Nephrology

Upper urinary tract

Posterior urethral valve

Voiding cystourethrogram

10.1007/s11255-015-0958-4

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Citations (1)

MFTN: Multi-Level Feature Transfer Network Based on MRI-Transformer for MR Image Super-resolution

Proceedings of the AAAI Conference on Artificial Intelligence (2024)

Shuying Huang Ge Chen Yong Yang Xiaozheng Wang Chenbin Liang

Due to the unique environment and inherent properties of magnetic resonance imaging (MRI) instruments, MR images typically have lower resolution. Therefore, improving the resolution of MR images is beneficial for assisting doctors in diagnosing the condition. Currently, the existing MR image super-resolution (SR) methods still have the problem of insufficient detail reconstruction. To overcome this issue, this paper proposes a multi-level feature transfer network (MFTN) based on MRI-Transformer to realize SR of low-resolution MRI data. MFTN consists of a multi-scale feature reconstruction network (MFRN) and a multi-level feature extraction branch (MFEB). MFRN is constructed as a pyramid structure to gradually reconstruct image features at different scales by integrating the features obtained from MFEB, and MFEB is constructed to provide detail information at different scales for low resolution MR image SR reconstruction by constructing multiple MRI-Transformer modules. Each MRI-Transformer module is designed to learn the transfer features from the reference image by establishing feature correlations between the reference image and low-resolution MR image. In addition, a contrast learning constraint item is added to the loss function to enhance the texture details of the SR image. A large number of experiments show that our network can effectively reconstruct high-quality MR Images and achieves better performance compared to some state-of-the-art methods. The source code of this work will be released on GitHub.

Feature (linguistics)

10.1609/aaai.v38i3.28011

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Citations (1)

Structure of the Singular Manifold of Protein Backbone and Its Applications

IEEE Access (2020)

Yonggang Chen Guanfeng Liu Yong Yang

This paper aims to study the structure of the singular manifold of a fragment of protein backbone using the method of robot kinematics. By modeling chemical bonds as rigid links, and torsional motion around chemical bonds as revolute joints, a fragment of protein backbone turns into a kinematic linkage. The singular manifold of the forward kinematic map of this linkage contains important information about the structure of its inverse kinematics map, and the results also apply to the study of the conformation space of protein loops. By splitting the forward kinematic map into an orientation and position map, we derive equations of the singular manifolds for both maps and analyze their geometric and combinatorial structures. We discuss the application of singular manifolds in several problems of computational biology, including minimal parametrization of protein conformation space and conformation space sampling of protein loops.

Manifold (fluid mechanics)

10.1109/access.2020.2978546

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Citations (3)