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2017 Vol. 36, No. 5 Published: 2017-10-20

Reviews Communications Regular Papers

Regular Papers

	513	Lung 4D-CT Image Registration Based on Regression Prediction
		Liu Yueliang, Fang Shiting, Zhang Yu
		DOI: 10.3969/j.issn.0258-8021.2017.05.001
		To improve the low accuracy of lung 4D-CT image registration due to intensity inhomogeneity and large local deformation, a regression-based method for predicting initial deformation is presented. The core idea of this method is that the image information of different phase corresponding to the floating image is used to predict initialize deformation field. Firstly, the common registration algorithmis used to register the different phase images to the reference image to get the corresponding deformation field. Then, the image and the corresponding deformation field are divided into patches to build training set. Multi-dimensional support vector regressor is used to learn a regression model with respect to the correlation between patch appearances and their respective deformations. The floating image is then input into the regression model to achieve the initial deformation field prediction, which is used to construct intermediate image. Finally, the registration of intermediate image and reference image are refined. The experimental results show that the proposed method can effectively register lung 4D-CT images. A public dataset provided by the DIR-lab at the University of Texas M.D. Anderson Cancer Center (Houston, TX) was employed to evaluate the proposed method. Quantitative evaluation results indicate that the proposed method significantly decreases SSD (18.97±5.75,P<0.05) compared with Active Demons algorithm(49.34±23.92) and Spectral Log-Demons algorithm (31.81±15.09),significantly increases CC (0.980 ± 0.006,P<0.05) compared with Active Demons algorithm(0.952±0.022) and Spectral Log-Demons algorithm (0.967±0.015). Qualitative evaluation results also show that our approach can yield superior registration performance.
		2017 Vol. 36 (5): 513-519 [Abstract] ( 342 ) HTML (1 KB) PDF (10622 KB) ( 146 )

	520	A Contour Detection Method Based on Color Opponent and Dynamic Coding of Neurons
		Hu Junhao, Fan Yingle, Li Kangqun, Wu Wei
		DOI: 10.3969/j.issn.0258-8021.2017.05.002
		Based on characteristics of color opponent and dynamic coding mechanism of neuron population, to realize the contour detection of images. Modeling the single color opponent characteristics of neurons on sub-cortex, a kind of dynamic adjustment mechanism about receptive field with single color opponent was constructed, in order to respond sufficiently on both color and lightness boundaries. Using the dendrite polar distribution of single cells, a neuron network with double color opponent on primary cortex was built to detect visual stimulus of specific orientation, in order to effectively extract the contour. Finally, taking the dynamic synaptic link into consideration, spike frequency response of single cells was synchronized in receptive field of neuron population, in purpose of realizing the inhibition of texture information. BSDS500 database was used in the experiments, the result indicates that the proposed method can effectively inhibit the texture information in the process of extracting the contour, the mean value and standard deviation of measure P for 100 images was 0.58±0.04, relative to other contrast method, improves the accuracy of contour extraction. Our method is effective for image contour detection, and provides a new idea for the image coding or visual cognition of the higher cortex by using the color information and the dynamic coding between the neurons.
		2017 Vol. 36 (5): 520-528 [Abstract] ( 366 ) HTML (1 KB) PDF (7404 KB) ( 302 )

	529	Multi-atlas Segmentation of Brain Subcortical Structures Based on ITK Registration Framework
		Nie Xiuling, Liu Renyuan, Lu Jiaming, Zhang Bing, Sun Yu, Wan Suiren
		DOI: 10.3969/j.issn.0258-8021.2017.05.003
		Numerous studies indicated that the process of Alzheimer's disease (AD) was closely correlated with atrophy of subcortical structures. Atrophy of some subcortical structures like hippocampi, could be a biomarker of early diagnosis of AD, which makes the segmentation of subcortical structures very important. Based on 3DT1W-MR images of 30 AD and 30 normal controls, we firstly performed brain tissue extraction combining histogram analysis and three-dimensional morphological processing method, then registered 10 brain atlas to the preprocessed image based on ITK registration framework. A two-stage images registration was applied to register multiple atlas on the subject MR scan. First, we applied affine registration with mean squares as metric. Second, B-spline transform based on mutual information model was applied to further registration. In the two-stage registration method, linear interpolation model and the optimizer named regular step gradient descent were used. After registration, STAPLE algorithm was achieved to perform image fusion on the obtained 10 registered images to get the final segmented image. The results show that all volumes of subcortical structures except caudate show no statistical differences between our method and FSL-FIRST algorithm (P>0.05); bilateral hippocampus and right nucleus accumbens suffer atrophy in AD (P<0.05). Our experimental data shows the validity of the multi-atlas-based segmentation method on segmentation of the brain subcortical structures.
		2017 Vol. 36 (5): 529-535 [Abstract] ( 449 ) HTML (1 KB) PDF (7115 KB) ( 295 )

	536	Research on Gradient Projection for Sparse Recovery Algorithm in PPG Signals Reconstruction
		Hu Kaili, Jin Jie, Zhang Ruifeng
		DOI: 10.3969/j.issn.0258-8021.2017.05.004
		Photoplethaysmography (PPG) is a noninvasive technique that reflects blood volume changes in the vessel and plays a vital role in the diagnosis of cardiovascular diseases. Nevertheless, it is extremely susceptive to motion artifact (MA) caused by the objects’ intentional or unintentional movements and then affects the accuracy of the diagnosis results. To solve this problem, this paper employed the gradient projection for sparse recovery (GPSR) algorithm based on the compressed sensing (CS) theoretical framework. For the non-sparse signals, the CS theory mainly consist two steps: sparse and recovery. First, in order to ensure the significant information not be destroyed, the Haar wavelet base was used to find the best sparse field for sparse the signals. After that the MA was removed from the contaminated PPG signals while the sparse signals were recovered. During the experiment, three types of noise were measured, and then GPSR algorithm was used to process the noisy signals, results showed that the GPSR algorithm significantly reduced the movement interference in the signals. In order to make the conclusions more convincing, other 50 healthy adults with vertical movement of MA were measured, the heart rate and mean square error (MSE) of the original and reconstruct PPG signals were calculated. Comparing the obtained heart rates with the noiseless PPG signals’ heart rates through the Bland-Altman analysis method, it was shown that the range of the differences between the noisy and noiseless PPG signals were about ±23 beat/min, and the reconstructed PPG signals were about ±2.7 beat/min. The Box Plot chart indicated that the MSE of the reconstructed signals was reduced about 50% compared with that of the noisy signals.
		2017 Vol. 36 (5): 536-542 [Abstract] ( 438 ) HTML (1 KB) PDF (1073 KB) ( 633 )

	543	Investigation on Driver Fatigue Based on WBAN and Approximate Entropy of Multi-Physiological Signals
		Wang Lin, Fu Rongrong, Zhang Chen, Yin Xiaowei, Hua Chengcheng, Wang Hong
		DOI: 10.3969/j.issn.0258-8021.2017.05.005
		Aimed to reasonably evaluate driver fatigue in driving process, three kinds of physiological signals, including electroencephalograph (EEG), electromyography (EMG) and respiration (RESP) signals of 12 subjects are recorded by wireless body area network (WBAN). Then, the approximate entropy (ApEn) of the signals are investigated during the driving process. The experimental results show that, ApEn of EEG, EMG, and RESP decrease in driving process. After about 90 min, the ApEn stays at a certain range of value, indicating the deeply driver fatigue. From principle components analysis, the contributions of the first two components are 47.33% and 40.26% (the total is more than 85%), and the weight of EEG and EMG is higher than RESP. From the statistical analysis, the values of P of ApEn of EEG and EMG are lower than 0.05, indicating EEG and EMG have better discrimination on driver fatigue. In case of the combination of EEG-EMG, there is obvious discrimination for the probability distribution of normal and fatigued state. This combination can effectively evaluate the fatigue degree during driving. Therefore, an optimized combination of physiological signals may be obtained, which is reasonable and reliable to evaluate the physiological characteristics of driver fatigue. The research results of present work can give a guidance to evaluate and relieve the driver fatigue.
		2017 Vol. 36 (5): 543-549 [Abstract] ( 356 ) HTML (1 KB) PDF (2930 KB) ( 306 )

	550	Segmentation and Scoring of Coronary Calcium in 3D CTA Data Based on FCM Algorithm and Self-Adapting Threshold Determination
		Zhao Cong, Chen Xiaodong, Zhang Jiachen, Wang Yi, Jia Zhongwei, Chen Xiangzhi
		DOI: 10.3969/j.issn.0258-8021.2017.05.006
		Aiming at the problems of image noise and impressionable threshold in coronary calcium quantification with 3D CTA data, a new method based on fuzzy C-means (FCM) clustering algorithm and self-adapting threshold determination was proposed for automatically segmenting and quantifying the coronary calcium. Firstly, feature vectors are constructed for every voxel in the coronary artery, which contains spatial coordinates and CT value information of the voxel, and a clustering algorithm combined with a self-adapted group number referring to vessel skeleton number is used to divide the coronary artery into different candidate volumes; secondly, a robust threshold determination algorithm based on the histogram is used to extract calcium plaques among those candidate volumes acquired; finally, calcium volume and Agatston score are calculated. Result shows that the method proposed in this study has relatively high sensitivity of 89.5% and specificity of 98.6% in calcium detection in 30 coronary CTA data. The calcium volume and Agatston score calculated automatically show a high correlation with the standard result. The corresponding Pearson correlation coefficient being up to 0.974 and 0.975, respectively, much higher than the 0.523 and 0.501 that calculated by the derivative-based threshold determination (DBTD) method. Experimental results show that this method can be used for coronary calcium segmentation and quantification, and has the characteristics of full automation, robustness and noise immunity.
		2017 Vol. 36 (5): 550-556 [Abstract] ( 365 ) HTML (1 KB) PDF (5449 KB) ( 314 )

	557	A Biomedical Ontology Repository and Platform Focused on Precision Medicine
		Guo Jingwen, Yang Sheng, Shi Furen, Shao Chen, Zhang Lulu, Wang Heng, Yang Xiaolin
		DOI: 10.3969/j.issn.0258-8021.2017.05.007
		In the past decade, ontology has been widely used in biomedical data analysis, search, integration and reuse. As ontology itself is a specific type of data, the amount of ontologies has also increased rapidly. In order to promote the integration of precision medicine data sets and provide ontology resource service for domestic users, we constructed MedPortal, an ontology repository and platform. Reusing NCBO BioPortal technology, we constructed MedPortal software framework. We selected precision medicine-related ontologies and built MedPortal ontology repository. Further, we modified some original code in order that MedPortal could run smoothly in the new network environment. Now MedPortal ontology repository has been successfully constructed. So far, 42 biomedical ontologies have been imported into MedPortal, mappings among which have also been created. Several ontology services including term search, ontology mapping, and data annotation are provided through websites and REST API, accessible at: http://medportal.bmicc.cn. MedPortal will be of help to biomedical data integration.
		2017 Vol. 36 (5): 557-564 [Abstract] ( 362 ) HTML (1 KB) PDF (10312 KB) ( 143 )

	565	The Influence of Transcranial Alternating Current Stimulation on Mental Rotation
		Dong Guoya, Shi Jing, Yang Hui, Liu Ye, Wu Zuhe, Chen Xiaogang
		DOI: 10.3969/j.issn.0258-8021.2017.05.00
		Transcranial alternating current stimulation (tACS) is a new non-invasive technology that applies weak electrical stimulation on the scalp to regulate neural activity. It has been confirmed that tACS can regulate spontaneous brain rhythm and influence cognitive process. Mental rotation is an important benchmark to measure spatial cognitive ability by imaging rotate object or itself. This study used mental rotation experimental paradigm to explore the effects of tACS on the mental rotation cognitive, the main evaluation indexes were behavioral performance and electrophysiological parameters like event related potential (ERP) and event related desynchronization (ERD). Behavioral results showed that the alpha tACS significantly reduced the reaction time(P<0.05), and with the image rotation angle increasing, the reaction time increased first and then decreased. Compared the mental rotation related negative wave between control group and stimulation group, we found that the RRN amplitude of stimulation group was lower than that of control group (stim vs sham, P<0.05), and it decreased first and then increased with the rotation angel increasing. The time-frequency analysis showed that the event related desynchronization in alpha and beta bands of stimulation group was weaker than that of control group (stim vs sham, P<0.05), and it appeared earlier than that of control group, indicating that tACS reduced the level of brain activation based on the earlier results that ERD is related to brain activation level. These results implied that tACS could improve the mental rotation ability and was potential in becoming a new way to improve the spatial cognitive ability.
		2017 Vol. 36 (5): 565-572 [Abstract] ( 387 ) HTML (1 KB) PDF (6918 KB) ( 295 )

	573	A Knowledge Representation Method Based on Two-Layer Modeling for Constructing Medical Knowledge Base
		Zhang Yinsheng, Wang Rui, Qiao Qingzhi, Li Haomin, Lv Xudong, Duan Huilong
		DOI: 10.3969/j.issn.0258-8021.2017.05.009
		Medical knowledge base is an important asset for clinical decision support system (CDSS). Current CDSSs deployed in hospitals are mostly targeted at specific requirements (e.g. rational drug use, computer-aided diagnosis), and their knowledge bases usually contain one specific type of knowledge. A comprehensive knowledge base that can coordinate different types of medical knowledge is essential for building integral and effective decision support applications. This paper proposes a knowledge representation method based on two-layer modeling. First, an epistemological model is constructed to cover various diagnostic and therapeutic knowledge types used in clinical settings, as well as their coordinative relationships. Then, based on specific reasoning and computation requirements, concrete representation formulisms are assigned to each knowledge type to form the final computational model. A clinical decision support system based on this two-layer modeling method has been running for more than 4 years in a Class III hospital. Practices show that the system effectively solved the need of integrating and reasoning of different knowledge types, and has established a foundation for building integral and comprehensive knowledge applications.
		2017 Vol. 36 (5): 573-579 [Abstract] ( 377 ) HTML (1 KB) PDF (6885 KB) ( 179 )

	580	The Analysis of the Systemic Circulation of Human Blood Based on Fluid Network
		Xu Ke, Zhao Liangju, Li Mingyang
		DOI: 10.3969/j.issn.0258-8021.2017.05.010
		Hemodynamic parameters will be studied under the changes of different organs flow resistances, based on the principles of traditional Chinese medicine pulse diagnosis. A fluid network model of systemic circulation of human blood is established. Utilizing a 10 times harmonic hemodynamics expression of cardiac output and the average method of adaptive control, the model is solved when η is respectively set to 0.5, 1.0, 1.5, 2.0, 2.5 and 3.0. With the cardiac index keeping constant, the results show that the average flow rate decreases with the increase of flow resistance of corresponding branch. The aortic mean pressure increases with the rise of flow resistance of organ branch. When η is setted to 3.0, the aortic mean pressure increases 23.29%, 16.42%, 14.67%, 9.69%, 9.59% and 7.82% higher than normal by the flow resistance increase of brain, liver, kidney, stomach, intestine and spleen branch respectively. The flow resistance of liver and kidney branch has the great effect on the radial artery mean pressure, which respectively increases 22.85% and 11.17% when η is setted to 3.0. While the other organ branches have less influence. For the harmonic amplitude of the radial artery pressure, the biggest affecting factor is the brain branch flow. The liver and kidney branch have less influence than the brain. The stomach, intestine and spleen branch have little impact on it. In this paper, we have found the relationships between the hemodynamic parameters and the changes of different organs flow resistances by the simulation method, and it can provide some theoretical basis for traditional Chinese medicine pulse diagnosis.
		2017 Vol. 36 (5): 580-588 [Abstract] ( 370 ) HTML (1 KB) PDF (1164 KB) ( 775 )

	589	A Programmable Ultrasound Generator for Brain Stimulation
		Hu Shengnan, Wu Yongliang, Zhang Yingjuan, Xie Qiaohong, Jiang Xuheng, Tian Fuying, Zheng Zheng
		DOI: 10.3969/j.issn.0258-8021.2017.05.011
		Low intensity ultrasound can stimulate brain tissues. We designed a programmable ultrasound generator for brain stimulation. From a computer the generator receives the stimulate variables, based on which an embedded FPGA chip generates the stimulation pulses. The output power is controlled by setting the duty cycle of the power amplifier at the last stage, which works in switching style for high efficiency. An impedance matching network is inserted between the output terminal and the ultrasound transducer so that the rectangular waveform is transformed to sine. The variables of the pulses are easy to understand and adjust compared to those of the general-purpose functional generators because they are designed especially for brain stimulating. The highest ultrasound frequency of the generator is 2MHz and the maximum output power is more than 157.1 watts. Twelve SD rats were experimented with the generator and a home-made 500kHz transducer, when rat brains were stimulated under the condition of spatial-peak temporal averaged intensity I_sppa=5.36W/cm², 90% success rate was achieved in terms of the responsive muscle contracting. The test results and animal experiments show that the generator we designed is capable to be used in the research work of brain stimulation.
		2017 Vol. 36 (5): 589-595 [Abstract] ( 370 ) HTML (1 KB) PDF (1239 KB) ( 393 )

	596	Experimental Research of Finger Flexion Control Basedon Functional Electrical Stimulation (FES) with Small-Area Surface Electrodes on Acupoints
		Gao Yujie, Zhang Bing, Qian Qinqin, Gao Jianyun, Lv Xiaoying, Wang Zhigong
		DOI: 10.3969/j.issn.0258-8021.2017.05.012
		The aim of this research is to explore a biomedical engineering technique which can rebuild the flexion function of the five fingers of the paralyzed upper limb. Based on the patented concept of electromyographic bridge (EMGB) and combined the Chinese traditional medical skill of acupuncture, this study selects 10 volunteers (five men and five women)and uses small area surface electrodes on upper limb 216 pairs of acupoints of each healthy volunteer for functional electrical stimulation (FES) on skin surface to test the best stimulation sites of five fingers’ flexion. The five pairs of acupoints found for five finger flexion in the experiment. The current threshold is less than 10mA, the success rate of finger flexion is 100%, the purity rate of single finger flexion is over 80%, and the rate of comfort degree is over 90%.Compared with traditional FES, this way needs less current, has higher purity of five finger flexion and has a standard location rule which lays a foundation for clinical trials of patients’ healthy fingers driving paralytic fingers to flex.
		2017 Vol. 36 (5): 596-601 [Abstract] ( 345 ) HTML (1 KB) PDF (4557 KB) ( 383 )

Reviews

	602	The Survey of EEG Fingerprints Identification
		Wang Luyun, Kong Wanzeng, Zhang Xinyu, Fan Qiaonan
		DOI: 10.3969/j.issn.0258-8021.2017.05.013
		Personal identification is particularly important in information security. The traditional way of identification is not sufficient in terms of security. As a new type of biometrics, electroencephalogram(EEG) signals has unique advantages of unstolenness, unforgeability and in vivo detection. It provides a more secure biometric method for identification. Therefore, EEG fingerprints is promising both in terms of scientific research and real-world application. In this paper, the state of art of the identification technologies based on EEG signals are reviewed. It also introduces the principles and methods of EEG fingerprints identification with regarding to resting state, visual evoked potential (VEP), motor imagery and event-related potential (ERP). Meanwhile, both advantages and limitations of these methods are discussed. Finally, research direction is summarized.
		2017 Vol. 36 (5): 602-607 [Abstract] ( 477 ) HTML (1 KB) PDF (780 KB) ( 1098 )

	608	Review on Human Core Body Temperature Measurement Method
		Liu Bo, Tang Xiaoying, Liu Weifeng, Wang Lulu
		DOI: 10.3969/j.issn.0258-8021.2017.05.014
		Temperature is one of the four vital signs of human health. To maintain a constant body temperature is the necessary condition to keep metabolism and normal life activities. The body temperature is a barometer for health. How to monitor the body temperature effectively is becoming an important topic recently. The temperature in clinical refers to the average core temperature. In our daily life, we usually measure the temperature of alar, mouth and forehead. However, the measured temperature is the body surface temperature in a strict way. Influenced by the surrounding environment and personal factors, there is an error between body surface temperature and body core temperature. In order to solve the problem, this paper analyzed the monitoring and research status of core body temperature at home and abroad and divided the methods into two parts. The first part is to measure temperature data directly, replace the core body temperature by the body surface temperature within a certain error range. The second part is to estimate temperature data indirectly, use the body surface temperature or some physiological data such as heart rate to set up a modeling and calculate the actual temperature inside the human body. Then the paper analyzed the accuracy of each method and compared the advantages and disadvantages of each method. At the last, the paper analyzed the development tendency of the core body temperature monitoring method in the future.
		2017 Vol. 36 (5): 608-614 [Abstract] ( 1871 ) HTML (1 KB) PDF (5233 KB) ( 2414 )

	615	The Effect of Cryopreservation on Biospecimens and Biomacromolecules
		Liang Wei, Wang Meixia, Liu Baolin
		DOI: 10.3969/j.issn.0258-8021.2017.05.015
		The role of biobanking in modern medical research is becoming more and more important with the endless achievements based on biobanks, which greatly promotes the development of translational medicine. The qualities of the specimens from biobanks have a great effect on the reliability of the researches. So how to guarantee the qualities of the samples is the key of the research on biobanks. Cryopreservation technology can maintain the viability of the specimens, which will play a significant role in the development of biobanks if preserving the complete molecular information and maintaining the viabilities of the specimens. The damage which freezing or cold brings to the specimens (especially to the biological macromolecules of the samples) and how to reduce these damages are reviewed in this article.
		2017 Vol. 36 (5): 615-621 [Abstract] ( 365 ) HTML (1 KB) PDF (883 KB) ( 849 )

Communications

	622	3D EIT Model Construction Based on Lung and Image Reconstruction Research
		Chen Xiaoyan, Chu Mengli, Chang Xiaomin, Zhang Xiaojie
		DOI: 10.3969/j.issn.0258-8021.2017.05.016

		2017 Vol. 36 (5): 622-626 [Abstract] ( 540 ) HTML (1 KB) PDF (6135 KB) ( 559 )

	627	A Preliminary Study on Non-Contact Heart Rate Measurement
		Feng Jun, Tang Wengming, Cao Jianjian, Yu Ying
		DOI: 10.3969/j.issn.0258-8021.2017.05.017

		2017 Vol. 36 (5): 627-631 [Abstract] ( 549 ) HTML (1 KB) PDF (1015 KB) ( 934 )

	632	A Deep Convolutional Networks for Identifying Multiple Tissues from Colorectal Histologic Image of Whole Slide
		Cai Chengfei, Xu Jun, Liang Li, Wei Jianhua, Zhou Yangshu
		DOI: 10.3969/j.issn.0258-8021.2017.05.018

		2017 Vol. 36 (5): 632-636 [Abstract] ( 343 ) HTML (1 KB) PDF (3289 KB) ( 667 )

	637	Influence of TiN/Ti Nano-Multilayers Compositedon Medical NiTi Shape Memory Alloy
		Tang Huiqin, Wan Rongxin, Gu Hanqing, Li Dejun, Dong Lei
		DOI: 10.3969/j.issn.0258-8021.2017.05.019

		2017 Vol. 36 (5): 637-640 [Abstract] ( 332 ) HTML (1 KB) PDF (2150 KB) ( 637 )

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