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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Xu, Changchang Hu, Dong Zhang, YaoDong Pang, Yuwei Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications Nanjing210003 China Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Education Ministry’s Engineering Research Center of Ubiquitous Network and Heath Service Nanjing University of Posts and Telecommunications Nanjing210003 China first clinical medical college of Nanjing Medical University Nanjing University of Posts and Telecommunications Nanjing210003 China

As a common malignant tumor disease, hepatocellular carcinoma is the most common cancers in the world. The incidence of hepatocellular carcinoma in China is higher than that in the world. Therefore, it is very important for doctors to separate liver and tumor from CT images by means of computer-aided diagnosis and treatment. In this paper, a multiscale DC-CUNets network liver tumor segmentation method is proposed to enhance the fusion of multi-phase image features in CT, the scale of liver tumors, and the optimization of network training process. (1) A multistage CT liver tumor segmentation method based on two-channel cascaded U-Nets (DC-CUNets) is proposed. The liver was segmented using the first-order U-Net, and then the segmented area of interest of the liver was input into the second-order U-Net network to segment liver tumors. We designed two-channel U-Nets to learn the image characteristics of CT images in arterial and venous phases respectively, and to achieve two-channel feature fusion through feature cascade to improve the overall accuracy of liver tumor segmentation.(2) A multistage CT liver tumor segmentation method based on multiscale DC-CUNets was proposed. For the scale problem of liver tumors, we designed a two-layer multiscale void convolution module to obtain image features at different scales for large, medium and small tumors, and fuse the multiscale features at the output of the module. We have replaced the convolution layer of the fourth module in the second-order two-channel liver tumor segmentation U-Nets by the two-layer multiscale cavity convolution module to implement multiscale DC-CUNets. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Convolution

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Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Platform

Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Pl...

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2018 3rd International Conference on Electrical, Automation and Mechanical Engineering(EAME 2018)

作者： Chuanwei Yin Dong Hu Tao Gu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

Although wavefront parallel processing(WPP) proposed in the HEVC standard and various inter frame WPP algorithms can achieved comparatively high parallelism, their scalability for its parallelism is still very limited due to various dependencies introduced in spatial and temporal prediction in HEVC. In this paper, through pixel correlation analysis, establishment of CTU node model, multi-core resource allocation strategy, we proposed an intra/inter-frame joint WPP coding algorithm for multi-core platform which can significantly improve the parallelism, while achieved good results in bit rate, PSNR, and acceleration ratio. Experiments on standard HD test sequence show that the proposed algorithm can lead to up to 2x, 1.3x speed up compared with the original WPP and IWF parallelism.

关键词： video coding HEVC multicore platform high parallelism WPP

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A Novel Multi-level Wavelet image Coding Algorithm by Full Sub-band Compressed Sensing

A Novel Multi-level Wavelet Image Coding Algorithm by Full S...

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2018 3rd International Conference on Electrical, Automation and Mechanical Engineering(EAME 2018)

作者： Weiping Qiu Dong Hu Yongyang He Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

The performance of wavelet transform based image compressed sensing coding algorithms severely rely on the level of wavelet transform. To this end, this paper investigated the combination of mutil-level wavelet full sub-band in compressed sensing framework. Firstly, we constructed a full sub-band coefficient sparse vector of mutil-level discrete wavelet transform. Secondly, we designed a weight matrix to improve measurement matrix. Finally, sparsity vector was processed by compressed sensing to get the measured value. Compared with the exiting algorithms, the experimental results of the proposed algorithm show that the PSNRs of reconstructed images is improve up to 1～2 dB under the same objective quality.

关键词： image coding wavelet transform compressed sensing full sub-band coefficient sparsity vector

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A Novel Two-Stage PCA Algorithm for Object Tracking

A Novel Two-Stage PCA Algorithm for Object Tracking

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2016 International Conference on communications, Information Management and Network Security (CIMNS2016)

作者： Yuanyuan Yang Dong Hu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781510830981

In this paper, we propose a two-stage PCA algorithm to deal with the problem of target appearance changes in object tracking. Our method is based on particle filter framework and aims at building up a robust appearance model for the target. In the first-stage, PCA is applied on several templates collected before tracking to construct a low dimensional subspace for the targets. Correspondingly, in the later tracking, all particles will be projected into this subspace to calculate the weight of particles, as well as the location of the target by weighted sum of particles. In the second-stage, PCA is adopted to decompose the reconstruction error into orthogonal basis to find the basis with biggest variance which can best present the appearance changes. Correspondingly, we uses this basis to update the old subspace. Besides, a threshold is set to decide when to update which greatly reduce the numbers of update. The two stages work together to establish a robust appearance model making our tracking algorithm more robust. Experimental results on public video sequence demonstrate the effectiveness of our proposed algorithm.

关键词： particle filter two-stage PCA eigenspace reconstruction error

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A Fast Quality Scalable Video Coding Method Based on Compressed Sensing

A Fast Quality Scalable Video Coding Method Based on Compres...

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2018 3rd International Conference on Electrical, Automation and Mechanical Engineering(EAME 2018)

作者： Min Sun Dong Hu Jianyu Ding Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

This paper presents a fast quality scalable video coding method based on compressed sensing(CS). The proposed method obtained the coding scheme of the enhancement MJU by using the interlayer and spatial correlation and kept the base layer's coding scheme unchanged. And the part in the enhancement layer which needed to be fine quantified was combined with the compressed sensing theory selectively which based on the sparsity of the signal and the complexity of the reconstruction. In order to satisfy the coding syntax structure of the reference software, the measurement value got by compressed sensing was complemented by 0 s and the flag bit was set to distinguish the special sub-blocks coded by CS. Experimental results show that the proposed algorithm can effectively improve the efficiency of scalable video coding and reduce the computational complexity.

关键词： video coding compressed sensing quality scalable video coding

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Motion compensation optimization of H.264 decoder based on DSP hardware platform

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Nanjing Youdian Daxue Xuebao (Ziran Kexue Ban)/Journal of Nanjing University of Posts and Telecommunications (Natural Science) 2007年第2期27卷 80-84页

作者： Gan, Zong-Liang Wang, Kai Zhu, Xiu-Chang Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

The H.264 video coding standard has a significant performance benefit versus former standards. However, motion compensation decoding process takes up a significant decoding time due to the advanced coding features. In this paper, the theory of motion compensation decoding in H.264 is given at first. Then the improved method is proposed by motion compensation fast decoding algorithm and optimization based on ADI Blackfin533 hardware platform. Both PC and ADI Blackfin533 experimental results show that the proposed optimization strategy can substantially improve the efficiency of real-time H.264 decoder.

关键词： Digital signal processor Direct memory access H.264 Motion compensation decoding

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Analysis of Beta Wave Epileptic EEG Signals Based on Symbolic Transfer Entropy

Analysis of Beta Wave Epileptic EEG Signals Based on Symboli...

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2015 International Conference on Artificial Intelligence and Industrial Engineering(AIIE 2015)

作者： Xiang Ye Tian Tian Tianpei Xu Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm

ISBN: (纸本)9781510806450

Epilepsy is a common neurological diseases caused by abnormal discharge of neurons in the brain. the attack is sudden and repeated characteristics. Therefore, in order to advance seizure prediction has important meaning for patients to take timely measures in this paper, the seizures in patients with EEG by using the method of symbolic transfer entropy are research and analysis, Through the EEG signal of epilepsy patients during attack and normal human alpha wave is extracted, By using the method of symbolic transfer entropy for analysis and research, Prior to the transfer characteristics which have been analyzed under entropy alpha wave component, this paper starts from beta wave components. then make a study by using the method of symbolic transfer entropy, the study found that using this method can differentiate the normal EEG and EEG in patients with epilepsy, Also found that the existence of nonlinear large amount of time series of EEG. This method is also proved symbolic transfer entropy based algorithm can be used to analyze the EEG signals fully, reveals the difference between epileptic EEG and normal EEG, clinical contribution made certain detection and prediction of epilepsy.

关键词： symbolic transfer entropy beta wave epileptic EEG detection prediction

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A parallel HEVC encoder scheme based on Multi-core platform

A parallel HEVC encoder scheme based on Multi-core platform

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2015 4th National Conference on Electrical,Electronics and Computer Engineering(NCEECE 2015)

作者： Shu Jun Hu Dong Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry’s Engineering Research Center of Ubiquitous Network and Health Service System Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing University of Post and Telecommunications

ISBN: (纸本)9781510819085

In this paper, we propose a parallel HEVC encoder scheme based on multi-core platform, which provides maximized parallel scalability by exploiting two-level parallelism, namely, the frame level parallelism and the CTB level parallelism. Inspired by the intra-CTB row level parallelism of WPP in HEVC, we investigate the inter-frame CTB prediction dependency to its reference CTBs, and find the inter-CTB correlation. Using this inter-correlation, we divide a frame into CTB units and create CTB-row level coding threads when their corresponding reference CTBs are available. Each thread is bonded to a processing core, therefore, both intra- and inter-CTB rows can be encoded in parallel. Moreover, we introduce a priority scheduling mechanism to control the coding threads. Experiments on Tilera-Gx36 multi-core platform show that, compared with serial execution, the proposed method achieves 3.6 and 4.3 times speedup for 1080 P and 720 P video sequences, respectively.

关键词： HEVC multi-core platform parallel processing frame-level CTB-level

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Multiscale Relative Transition Entropy Analysis of Electroencephalogram

Multiscale Relative Transition Entropy Analysis of Electroen...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Ying Wang Fengzhen Hou Jiafei Dai Jin Li Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ.of Posts & Telecomm. School of Science China Pharmaceutical University Nanjing General Hospital of Nanjing Military Command College of Physics and Information Technology Shaanxi Normal University

ISBN: (纸本)9781510823808

Recently,quantifying the complexity of the physiological time series has become more and more *** one of the most complex physiological signals,electroencephalogram(EEG) including a large number of physiological and pathological information attracts widespread ***,many traditional algorithms fail to account for the multiple times scales inherent in physiologic *** this paper,we proposed multiscale relative transition entropy algorithm(MRTE) to analyze the white noise and pink noise,the adolescent and adults EEG as well as normal and epileptic *** results indicate that there are distinct tendency among different types EEG which indicating that the multiscale relative transition entropy can distinguish different physiological and pathological signals.

关键词： multiscale relative transition entropy complexity

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Analyzing Occupational Stress Based On Inner Composition Alignment Algorithm

Analyzing Occupational Stress Based On Inner Composition Ali...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics

作者： Zhen Shi Shitong Wang Jun Wang Jiafei Dai Fengzhen Hou Jin Li Image Processing and Image Communications Key Lab Nanjing Univ. of Posts & Telecomm China Nanjing Brain Hospital China School of Science China Pharmaceutical University Nanjing China College of Physics and Information Technology Shaanxi Normal University Xi'an China

ISBN: (纸本)9781509037117

To distinguish different level of occupational stress of students and nurses, this paper applied inner composition alignment (IOTA) algorithm to analyse differences between the students' Electroencephalogram (EEG) and the nurses' EEG and to explore the influence of occupational stress on EEG. First, we selected nine cases of students EEG data and the same quantity of nurses EEG data from General Hospital of Nanjing Military Region, then, constructed two different brain networks by utilizing IOTA method and analyzed the networks characteristics which include IOTA coefficient, Clustering coefficient and Average degree. In order to verify the accuracy of the results, we used SPSS to analyse the significant difference hypothesis testing. The IOTA coefficients are inconsistent between students' EEG and nurses' EEG. Compared with the students, nurses' brain network is more complex. The level of occupational stress of nurses is higher than students. The IOTA algorithm can significantly distinguish occupational stress between students and nurses, and all results demonstrated the validity of the algorithm.

关键词： Brain Network Occupational Stress EEG IOTA Complex Network

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