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2017 Vol. 36, No. 6 Published: 2017-12-20 Reviews Communications Regular Papers        Regular Papers 641 Non-Contact Detection and Estimation of Heart Rate by Improved Chrominance Model Zhang Jiacheng, Qiu Tianshuang, Ma Jitong DOI: 10.3969/j.issn.0258-8021.2017.06.001 Camera-based image photoplethysmography method enables a low-cost, non-contact way to estimate physiological parameters. The method based on chrominance model has a high computational efficiency and motion resistance. However, this model ignores the interference caused by the illumination fluctuations. Considering this problem, this paper proposed an improved chrominance model. In this model, we defined the reflection model of the ROI area and background area and subtract the illumination interference by using the ratio of these two area. So we can get a new chrominance model without illumination interference and use it to extract the pulse signal and estimate the heart rate. By using the face images from 10 subjects, we found the average relative error of heart rate estimated by this method was only 3.52%±2.53% and the average relative error of heart rate estimated by previous chrominance method was 7.23%±2.82%, which has significant difference (P<0.01). It also improved the signal\|to\|noise of the extracted pulse signal by 1.52 dBcompared to the chrominance model. It has an important significance on the non\|contact estimation of heart rate and extraction of pulse signal. 2017 Vol. 36 (6): 641-646 [Abstract] ( 487 ) HTML (1 KB)  PDF (1834 KB)  ( 700 ) 647 An Algorithm of the LBP Feature Extraction Method Combining Sparse Representation in Liver Diseases Recognition Han Xiuzhi, Zhao Ximei, Yu Kexin, Wang Guodong DOI: 10.3969/j.issn.0258-8021.2017.06.002 Because of the existence of the uneven echo, the dim edge and other factors under the ultrasonic environment, the diagnose accuracy of liver diseases can be influenced. Besides, the clinical diagnosis for liver diseases based on liver ultrasonic figure is mainly based on the conventional visual assessment that relies on the subjective experience of radiologists, leading to inaccurate and inadequate results. This study therefore proposed alocal binary pattern feature extraction method combining sparse representation algorithm. The proposed method extracted theregions of interest from liver ultrasonic figures, LBP method for feature extraction, dictionary learning method for training, andsupport vector machine for classification. In order to verify this approach, experiments were carried out by selecting samples from department of hepatobiliary surgery of affiliated hospital of Qingdao University. Results showed in the first experiment that the accuracy rate reached 99.50% of 100 normal liver samples and 100 liver cirrhosis samples. And results showed in the second experiment that the AUC of liver cirrhosis, fatty liver, hemangioma and liver cancer reached 67.2%, 65.1%, 55.0% and 62.6% separately of total 200 samples. The comparison between the proposed method and conventional methods, via receiver operating characteristic curve, demonstrated that the proposed method possessed the advantages both in accuracy and generalization performance. The proposed method would be helpful for clinical diagnosis of liver diseases. 2017 Vol. 36 (6): 647-653 [Abstract] ( 412 ) HTML (1 KB)  PDF (1665 KB)  ( 334 ) 654 Detecting and Locating the Macular Using Morphological Features and k-means Clustering Cao Xinrong, Lin Jiawen, Xue Lanyan, Yu Lun DOI: 10.3969/j.issn.0258-8021.2017.06.003 Color fundus images have been widely used in the diagnosis and screening of ophthalmic diseases. The macular detection and foveal location in fundus images are important steps in grading and diagnosis of ophthalmic diseases. An efficient method not relying on the optic and vascular information was proposed in this work for detecting and locating macular foveal. After a general analysis on morphological characteristics of macular, which was low brightness and round, the area of macular could be ensured in the binary images. Then, an improvedk-means clustering method was proposed on the basis of spatial information of images and optimizes clustering objects to obtain the edge information of macular and achieve accurate position of the macula foveal. Experimental tests showed good performance in the public fundus images database. For the normal and the pathological changes of the fundus images, the effective location rate of the macula was 96.11% and 92.12% respectively, and the average accuracy reached 93.92%. Thus the proposed method based on morphological features and k-means clustering proved a simple, efficient and useful tool for computer-aided diagnosis of ocular diseases. 2017 Vol. 36 (6): 654-660 [Abstract] ( 363 ) HTML (1 KB)  PDF (8106 KB)  ( 225 ) 661 Application of Numerical Observer CHO in Evaluation of Filtering Method in PET Xie Jing, Yang Yong, Ye Hongwei, Chen Dongmei DOI: 10.3969/j.issn.0258-8021.2017.06.004 In clinical applications, it is necessary to limit the scan time and dose, which tends to lower the resolution of the positron emission tomography (PET) image and increase the noisein PET. A denoise method is required to achieve the clinically acceptable images, and a post filter after reconstruction is the most widely used method. Therefore, the comparison of smoothing effect of different filters, for instance the selection of filter parameters, is an important step in PET image reconstruction. Generally, the signal-to-noise ratio (SNR), recovery coefficient (RC) or similar methods are used in the parameter selections. But researchers still rely on their experience since those methods cannot be used quantitatively. As a generalized numerical observer, channelized hotelling observer (CHO) has been used in selection of various parameters in PET, such as reconstruction algorithm parameters, system design parameters, clinical protocol parameters and so on. However its application in the assessment of different filtering methods of image reconstruction is not widely studied. The purpose of this paper is to select the optimal parameters of two widely used filters, i.e. Gauss filter and Non-Local Mean (NLM) filter, and evaluate their smoothing effect in PET by comparing the area under the receiver operating characteristic(ROC)curve (AUC) values calculated by CHO. Experimental results showed that for the 13 mm sphere, Gauss filter with σ of1.1~1.4 and NLM filter with f of 0.5-0.9 achieved the maximum detectability, and for the 10 mm sphere, Gauss filter with σ of 1.4~2.0 and NLM filter with f of 0.5~0.9 achieved the maximum detectability. Though AUC values of both filters were as high as 0.9, the AUC value of NLM filter was larger than that of Gauss filter. It was also found out that bright spots had better contrast and lower noise in IEC images and patient images with the NLM filter than that with the Gauss filter. This conclusion was consistent with results obtained by traditional evaluation methods of the filter, which indicated that CHO accurately compared the performance of these two filters in the lesion detection task of PET. 2017 Vol. 36 (6): 661-669 [Abstract] ( 384 ) HTML (1 KB)  PDF (5266 KB)  ( 287 ) 670 Respiratory Motion Correction of Liver Contrast-Enhanced Ultrasound Sequences by Selecting Reference Image Automatically Zhang Ji, Zhang Yanrong, Chen Juan, Chen Xiaohui, Zhong Xiaoli DOI: 10.3969/j.issn.0258-8021.2017.06.005 The selection of reference image is one of the key roles for the efficiency of respiratory motion correction method based on liver contrast-enhance ultrasound (CEUS) image sequences. The selection method is worthwhile exploring. First, the original high-dimensional ultrasound data was mapped into a two-dimensional space by using Laplacian eigenmaps. Then, the cluster analysis was adopted using k-means, and the optimal ultrasound reference image was obtained for the respiratory motion correction. Finally, the effectiveness of this proposed method was validated with 18 CEUS cases of VX2 tumor implanted in the rabbit liver. Before correction, the average of total mean structural similarity and the average of mean correlation coefficient from image sequences were 0.45±0.11 and 0.67±0.16,respectively. After correction, the two parameters were increased obviously (P<0.001) as 0.59±0.11 and 0.81±0.11 respectively. The average of deviation valve (DV) from image sequences before correction was 92.16±18.12. After correction, the average of DV was reduced to one-third of the original value. The proposed respiratory motion method improved the accuracy of the quantitative analysis of CEUS by using the reference image based on the traditionally manual selection as well as operated simply, therefore is of potentials in the clinical application. 2017 Vol. 36 (6): 670-677 [Abstract] ( 451 ) HTML (1 KB)  PDF (3203 KB)  ( 392 ) 678 A Synthetic Algorithm of FECG Extraction from Single-Lead Abdominal Signals Tian Fuying DOI: 10.3969/j.issn.0258-8021.2017.06.006 In this paper, a synthetic algorithm was proposed to extract the fetal electrocardiogram (FECG) from single-lead abdominal signals. We extracted maternal electrocardiogram (MECG) and FECG successively and then calculated maternal and fetal heart rate. In the algorithm, we first applied Teager energy operator with parameter k (k=19) to protrude QRS waves of MECG, so that the location of maternal R peaks was detected correctly by simple threshold. Then we resampled between every adjacent R peaks to get same R-R interval T. After applying a comb filter whose teeth coincide with the maternal R-R interval T, we obtained the MECG with same R-R interval. And the real MECG was obtained by resampling between every adjacent R peaks in the filtered signals again to recover the original R-R intervals. The extracted MECG was subtracted from the abdominal signals. In the residual signal the QRS waves of FECG had better signal-noise-ratio. Next, the same procedure was applied on the residual signal to extract the FECG signal. We analyzed 8 sets of abdominal signals (total 26 channels) that were selected from the Physionet non-invasive FECG database. The sensitivity (Se), positive predictive value (PPV) and accuracy (F1) of fetal QRS waves detection were calculated. Results showed that the detection accuracy of fetal QRS waves reached 87.1%, with six channel even reached 100%. The maternal heart rate (MHR) and fetal heart rate (FHR) of each channel were also calculated. We found out that the MHRs, as well as the FHRs, showed good consistence with channels of the same set. In the same set, the maximum error of the mean MHR was 0.1 times per minute and the maximum error of mean FHR was 0.9 times per minute. Such a phenomenon also proved the reliability of the proposed algorithm. 2017 Vol. 36 (6): 678-684 [Abstract] ( 432 ) HTML (1 KB)  PDF (1038 KB)  ( 589 ) 685 Improving Brain Function States by Special Game Training Li Xin, Sun Xiaoqi, Cai Erjuan, Fan Mengdi, Hou Yongjie DOI: 10.3969/j.issn.0258-8021.2017.06.007 Focusing on the issue of improving the state of brain and supporting memory retention by serious game training, this study investigated the human state of brain function before and after experiments and their adaptation to a single game with long duration. EEG signals were collected with 10 individuals before and after playing a special game lasting 20 days, and the changes of brain function were assessed using memory test. The sample entropy of alpha wave, beta wave and their ratio alpha/beta were used to analyze the changes before and after game training. Furthermore the adaptability under a single game was discussed with the feature of theta/SMR. Compared with that before game training, the sample entropy of alpha wave showen the trend of increase, the sample entropy of beta wave decreased significantly(0.62±0.05 vs 0.54±0.04,P<0.05), and the alpha/beta increased significantly(0.44±0.02 vs 0.83±0.20,P<0.05). The memory test verified the results from the sample entropy. After game training, D-CAT raised significantly(35.60±6.21 vs 37.81±6.42,P<0.05), and SRT(ms)had a significant reduction(292±25 vs 281±20,P<0.05). Theta/SMR appeared a upward trend and the sensitivity a downward one. Serious game training can boost brain function states as an assistant method. 2017 Vol. 36 (6): 685-691 [Abstract] ( 475 ) HTML (1 KB)  PDF (875 KB)  ( 548 ) 692 A Selection Method of Biomarkers for Schizophrenia Based on Sparse Representation Wu Jie, Wei Fengxian, Fu Ling DOI: 10.3969/j.issn.0258-8021.2017.06.008 Schizophrenia is a complex mental disease characterized by the division of thinking, emotion and behavior. A large number of studies have found out that genetic factors are the important causes of the disease all over the world. In order to identify the biomarkers of schizophrenia from a large number of imaging genetic data, we proposed an imaging genetic data integration analysis method based on sparse representation inspired by the sparse representation, and applied it for biomarkers selection for schizophrenia. From 208 samples, 41236 groups fMRI and 722177 groups SNP data were extracted. The generalized penalty restriction was applied to the traditional sparse representation model, and the weight factor α1,α2 were applied to fMRI and SNP data. With the primary aim to find out the pattern of significant association of two kinds of data under different conditions, various Lp(p=0, 0.5, 1)norm was used to solve our model. It turned out that gene DAOA and HTR2A were selected under different situations: 1. Weight factor of fMRI α1changed from 0.35 to 0.8, 2. SNP weight α2 was only 0.2, 3. All three norms of Lp(p=0, 0.5, 1). In addition, the results of imaging data suggested that Parietal_Inf_L and Parietal_Inf_R were associated with schizophrenia, which was same with previous studies of schizophrenia. The results show that the sparse representation of biomarkers selection method for schizophrenia is a feasible method; it may provide a new approach for the study of schizophrenia in the field of imaging genetics. 2017 Vol. 36 (6): 692-696 [Abstract] ( 372 ) HTML (1 KB)  PDF (780 KB)  ( 266 ) 697 Feature Dimension Reduction of Hepatitis B Virus Reactivation Prediction Model in Patients with Primary Liver Cancer after Precise Radiotherapy Wang Huina, Huang Wei, Liu Yihui DOI: 10.3969/j.issn.0258-8021.2017.06.009 This study established a classification prediction model for hepatitis B virus (HBV) reactivation after the precise radiotherapy in patients with primary liver cancer (PLC), which is expected to use to prevent HBV reactivation and reduce the incidence of the disease. Ninety of HBV-related HCC patients after receiving precise radiotherapy were recruited from Shandong Cancer Hospital. Each sample tests involved thirty characteristics of sexuality, age, KPS score, AFP level, HBV DNA level, tumor stage TNM etc. In this paper, we proposed a sequential feature selection (SFS) method to select key features which would be combined into a brand new feature subset and then establish Bayesian classification prediction model. The method of sequential backward selection (SBS) showed that the KPS score, HBV DNA, outer margin of radiotherapy, TNM, and total hepatic maximum dose were the risk factors that lead to HBV reactivation. The classification accuracy of Bayesian classification reached to 85.75% using 3 fold cross validation. Besides, Sequential forward selection showed that the sexuality, KPS score, HBV DNA, HBeAg and the two kinds of code of outer margin of radiotherapy were the risk factors that lead to HBV reactivation, meanwhile, the classification accuracy of Bayesian classification reached to 84.06% with 5 fold cross validation. The experimental results showed that the Bayesian classification could be used to study the reactivation of HBV. The key feature had a better classification performance after the feature selection. 2017 Vol. 36 (6): 697-701 [Abstract] ( 336 ) HTML (1 KB)  PDF (819 KB)  ( 313 ) 702 Short-term Prediction of Blood Glucose Based on CEEMDAN and ELM Wang Yannian, Guo Zhanli, Yuan Jinlei, Li Quanzhong DOI: 10.3969/j.issn.0258-8021.2017.06.010 A short-term prediction model of blood glucose based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and extreme learning machine (ELM) was proposed to improve the forecasting accuracy of blood glucose, which is timing-varying, nonlinear and non-stationary in diabetics. Firstly, by means of CEEMDAN, time sequence of blood glucose was decomposed into several intrinsic mode function (IMF) with different frequencies and a residual to reduce the non-stationary. Next, ELMs were built for each IMF and residual component to improve the forecasting accuracy, and the all forecasts of ELMs were fused to produce the prediction of blood glucose. Finally, an early alarm algorithm of hypoglycemia was proposed based on the short-term prediction model. The model was verified by 56 cases of diabetic in Department of Endocrinology of Henan Province People's Hospital. The experimental results showed that comparing to ELM model and EMD-ELM model, the proposed prediction model of blood glucose based on CEEMDAN-ELM could achieve 45 min prediction in advance, the RMSE was 0.2051 and the MAPE was 2.1164%. The false alarm rate and missing alarm rate of early alarm algorithm of hypoglycemia were 0.97% and 7.55% respectively. The 45 min prediction ahead provided sufficient time for doctors and diabetics to control the blood glucose concentration, especially for diabetics with hypoglycemia. 2017 Vol. 36 (6): 702-710 [Abstract] ( 375 ) HTML (1 KB)  PDF (1189 KB)  ( 545 ) 711 The Numerical Simulation and Design of a 6-Channel Array Coil for MRI Li Huayong, Cao Shuangliang, Wang Peipei, Chen Meiling, Lu Lijun, Chen Wufan DOI: 10.3969/j.issn.0258-8021.2017.06.011 The multi-channel array coil has been widely applied in MRI to improve the quality of images in recent years. Aimed at optimizing the radio frequency (RF) field in the local region of interest (ROI), we proposed a model of a 6-channel array coil consisting of elements of different dimensions, which was proved to be able to optimize the RF field in the local region of interest in the pelvic cavity. The model was made up of coils with two different widths (10 cm and 20 cm). In this paper, geometry overlapping and capacitive network methods were adopted to decouple coils, and the finite difference time domain (FDTD) method was applied to simulation and calculation. The RF field in ROI produced by the proposed array coil was analyzed and evaluated. The simulation results showed that the decoupling levels S12 and S13 of the proposed array coil combined with the elliptic cylinder electromagnetic model were -27.19 dB and -33.46 dB, respectively. Additionally, the RF field B+1 mean value in ROI was approximately 5.21% larger than a conventional array coil made up of same elements with width of 15 cm. In conclusion, the array coil made up of elements with different dimensions improved the RF field in ROI, thereby providing inspiration for the design of RF coils for MRI. 2017 Vol. 36 (6): 711-717 [Abstract] ( 317 ) HTML (1 KB)  PDF (2827 KB)  ( 351 ) 718 Biomechanical Study of Posterior Fixation for Thoracolumbar Burst Fractures Pei Baoqing, Shi Zhenpeng, Wang Wei, Lu Shibao, Kong Chao DOI: 10.3969/j.issn.0258-8021.2017.06.012 In order to provide theoretical support and clinical basis for the choice of surgical methods for patients with thoracolumbar burst fractures, five finite element models of the T10-L2 segment were established in this work including intact model, burst fracture model, mono-segment pedicle screw fixation, intermediate bilateral pedicle screw fixation, and traditional short-segment pedicle screw fixation. To analyze the biomechanics of the three fixation models, flexion, extension, lateral bending, and rotation moments of 7.5N-m with a compressive preload of 400 N were imposed on the superior surfaces of the T10 vertebral body. Results showed that the range of motion at the three fixation models decreased for all loading cases, compared with that at the intact model. Compared with the intermediate bilateral pedicle screw fixation model, the largest maximal stress of the pedicle screw at mono-segment pedicle screw fixation model increased by78.1% in flexion, 87.8% in extension, 90.5% in left bend, 81.3% in right bend, 51.3% in left rotation,72.3% in right rotation. In conclusion, the range of motion of the mono-segment pedicle screw fixation model was the most similar to that of the intact model, and it was most likely to protect the original mechanical properties of the spine while restoring the stability of the spine, but the largest maximal stress of pedicle screws was much higher than the intermediate bilateral pedicle screw fixation. For severe damage to the instability, the intermediate bilateral pedicle screw fixation significantly reduced the pedicle screw stress while improving the stability of the spine. 2017 Vol. 36 (6): 718-723 [Abstract] ( 373 ) HTML (1 KB)  PDF (6808 KB)  ( 272 )        Reviews 724 Current Research Status and Trends of Emotional Influence on Working Memory Liu Shuang, Tong Jingjing, Guo Dongyue, Ke Yufeng Xu, Minpeng, Wan Baikun, Ming Dong DOI: 10.3969/j.issn.0258-8021.2017.06.013 The emotion plays an important role in the cognition process, such as perception, attention, memory, and decision. Working memory is a finite memory system processing and storing the information momentarily, which builds up a platform to communicate for perception, memory and behavior. Up to date studies have found out that emotional status can affect the working memory, and the working memory of the patients with emotional disease can be damaged because of the negative emotion. Therefore the relationship between the emotion and working memory, especially the influence of emotion status on the working memory, has been the research issue that attracts intensive interests in the field of cognitive psychology and cognitive neuroscience. One of the crucial issues is how the emotion affects the working memory. This paper reviewed the physiological mechanism, classical theories, common experimental paradigms, and current researches results. Additionally existing problems and development trends were discussed. 2017 Vol. 36 (6): 724-732 [Abstract] ( 615 ) HTML (1 KB)  PDF (3542 KB)  ( 1007 ) 733 EEG Inverse Problem and its Application in Motor Rehabilitation Area Xu Lichao, Wang Zhongpeng, Xu Minpeng, He Feng, Zhou Peng, Ming Dong, Qi Hongzhi DOI: 10.3969/j.issn.0258-8021.2017.06.014 The EEG-based BCI rehabilitation system has been growing lots of interests in the motor rehabilitation area. However, conventional BCI paradigms limit the intuitive use of these systems. The EEG source imaging can reveal and identify the self-modulated neural activity with high spatial and time resolution thereby expand command sets used by motor rehabilitation systems. This review introduced state-of-the-art EEG source imaging methods and its applications in motor rehabilitation area. We also summarized problem and analyzed the trend that combing EEG source imaging for guiding rehabilitation in the future. 2017 Vol. 36 (6): 733-740 [Abstract] ( 297 ) HTML (1 KB)  PDF (816 KB)  ( 654 ) 741 Research Progress of Positioning Method ofTranscranial Magnetic Stimulation Zhou Tianpeng, Zhang Guanghao, Wu Changzhe, Zhang Cheng, Huo Xiaolin DOI: 10.3969/j.issn.0258-8021.2017.06.015 The popularity of transcranial magnetic stimulation (TMS) technology has been limited by its poor positioning accuracy. As a kind of technical means which relies on hardware devices to implement functionality, the positioning accuracy of TMS is related to many factors. Based on the in-depth research in recent decades, the related research progress in this field was described from two aspects: the hardware optimization method and the positioning theory. According to the analysis and comparison of the positioning features of circular coil, figure-of-eight coil, Slinky coil, H-coil and double-cone coil these five different coil types, and the brief description of the positioning effect of the conventional navigation system, the importance of basic positioning theory for hardware operation guidance was revealed. Based on the key difficulties of current positioning technology and the hot spots of positioning research, this review proposed a direction of future development, that is, by constructing a high spatial resolution stimulating navigation system and combing with medical imaging technology, to seek the microcosmic mechanism of TMS on the structural scale which eliminates the individual difference, aiming to derive the general solution to the problem of positioning. 2017 Vol. 36 (6): 741-748 [Abstract] ( 565 ) HTML (1 KB)  PDF (4319 KB)  ( 732 ) 749 The Effect of Macrophages on the Post-Implantation Reaction of Biomaterials and Tissue Regeneration Shi Jie, Tang Di Gao, Jingchen, Kong Deling, Wang Shufang DOI: 10.3969/j.issn.0258-8021.2017.06.016 There is a growing demand for biomaterials in clinical therapeutics. The implantation of biomaterials might end up in failure due to post-implantation inflammation. An effective approach to induce tissue regeneration would be the modulation of the macrophages responses to the implanted biomaterials. This review summaried the origin, subtypes, expression markers and functions of macrophages. Meanwhile strategies to induce macrophages toward the role of alleviating inflammation and promoting tissue regeneration after biomaterials implantation were introduced comprehensively. Some noteworthy challenges and directions in the research on facilitating tissue regeneration through the modulation of macrophages were discussed as well. 2017 Vol. 36 (6): 749-754 [Abstract] ( 343 ) HTML (1 KB)  PDF (4315 KB)  ( 700 )        Communications 755 Analysis of the Cortex Thickness in Patients with Temporal Lobe Epilepsy Cui Jingxuan, Cui Yuan, Liu Qi, Zhang Junpeng DOI: 10.3969/j.issn.0258-8021.2017.06.017 2017 Vol. 36 (6): 755-758 [Abstract] ( 367 ) HTML (1 KB)  PDF (2877 KB)  ( 474 ) 759 Multi-Body Dynamics Modeling and Mechanical Characteristics Research of Patient Rehabilitation Transfer Device Ren Wu, Zhang Zhaowei, Tang Hongbin, Yu Yi DOI: 10.3969/j.issn.0258-8021.2017.06.018 2017 Vol. 36 (6): 759-763 [Abstract] ( 307 ) HTML (1 KB)  PDF (1285 KB)  ( 358 ) 764 A New Method and Device for Fast HBV Genotyping in Point-of-Care Diagnostics Niu Yanan, Yang Yongliang, Song Liuwei, Yuan Quan, Ge Shengxiang, Min Xiaoping, Tang Zhanghong, Yu Duli, Qiu Xianbo DOI: 10.3969/j.issn.0258-8021.2017.06.019 2017 Vol. 36 (6): 764-768 [Abstract] ( 328 ) HTML (1 KB)  PDF (2653 KB)  ( 300 )

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