Bangquan Xu

Anhui Jianzhu University

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Jiarui Lin

Tianjin University

Jia‐Rui Lin

Tsinghua University

Zhiyong Gao

Shanghai Jiao Tong University

Xue‐Mei Lin

Hong Kong Polytechnic University

Yingjian Zhan

Ningbo University

Zhuang Ye

Huazhong University of Science and Technology

Ruihong Chen

Southern University of Science and Technology

Bin Li

Northeast Forestry University

Fansan Zhu

Renal Research Institute

Yangxiezi Cao

Huazhong University of Science and Technology

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Huazhong University of Science and Technology

Chinese Academy of Sciences

Guangdong University of Technology

Hong Kong Polytechnic University

Ningbo University

Ministry of Agriculture and Rural Affairs

Southern University of Science and Technology

Guilin University of Electronic Technology

Guangdong Medical College

Institute of Biophysics

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The affection of grey levels on mutual information based medical image registration

IEEE Nuclear Science Symposium conference record (2004)

Zhiyong Gao Jia‐Rui Lin Bangquan Xu

Multimodal registration, which bringing images from different modality into spatia correspondence, is of importance in many clinical applications. Medical image registration is an active research filed in medical image processing in the last two decades. Over the years, research of multinodal registration has produced a lot of different methods. Surveys of medical image registration with a classification have been made.

Image registration

Medical information

10.1109/nssmic.2002.1239623

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Citations (6)

Research of gastro-oesophageal disease aided diagnose expert system

Hong Song Jiarui Lin Bangquan Xu Xue‐Mei Lin Fansan Zhu

Describes a method for the development of a gastro-oesophageal disease diagnostic expert system. Results obtained from gastric multiparameter monitoring are the important way of knowledge acquisition in this system. Medical knowledge is also included. For different kinds of knowledge, different kinds of knowledge expression and methods of acquisition are used. Three kinds of inferring methods are then used to obtain the conclusion. The test results show that the expert system will help to diagnose digestive diseases, and it also provides a new method for clinical and basic medical research.

Knowledge Acquisition

Gastro-

Medical knowledge

10.1109/iembs.1996.656899

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Citations (1)

A model for evaluating the robustness of network covert channels based on entropy TOPSIS method

Jiajing Zhang Bangquan Xu

Robustness

Covert

TOPSIS

10.1145/3672919.3672930

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The effect of grey levels on mutual information based medical image registration

Jia‐Rui Lin Zhiyong Gao Bangquan Xu Yangxiezi Cao Yingjian Zhan

Medical image registration is an active research field in medical image processing in the last two decades. One of the surveys of medical image registration is voxel-based method, which is generally considered as very accurate, almost fully automatic. The most efficient voxel-based method is maximization of mutual information (MI). In This work, we will discuss the effects of rescaling intensity values of an image on MI method, and then compare the registration results and computation time of the same image pairs with different grey levels. We implemented series rigid registration of CT and MR image, in each registration, the intensity values of CT and MR images are linearly reseated to the same range. We adopt 5 different levels in our experiments, i.e. 256, 128. 64, 32 and 16 grey levels to exploit the affection of grey levels on MI based registration method. We also count the time cost on the calculation of single MI value and the whole registration procedure. Finally we reach this conclusion that the results become worse with the reduction of grey levels of the image, and rescaling the intensity values of the original images into [0,63] is an excellent tradeoff in brain registration by mutual information.

Image registration

Maximization

10.1109/iembs.2004.1403524

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Citations (15)

Research on gastric multiparameter expert system

Xue‐Mei Lin Jiarui Lin Bangquan Xu Bin Li Zhuang Ye

A gastric multiparameter expert diagnostic system is introduced. The system is based on the monitoring of four parameters, that is gastric pH, pressure, temperature and electrogastrography (EGG). First, the basic theory of the diagnostic system is described, and then methods of inference are given. The results show that the expert system can provide a new method for clinical and basic medical research.

10.1109/iembs.1995.575319

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