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2018 Vol. 37, No. 2 Published: 2018-04-20

Reviews Communications Regular Papers

Regular Papers

	129	The Application and Comparison of Phase Unwrapping Algorithms in Susceptibility Weighted Images
		Li Xinling, Tang Ming, Liu Qi
		DOI: 10.3969/j.issn.0258-8021.2018.02.001
		In order to develop an effective method to solve the phase unwrapping problem in the susceptibility weighted imaging (SWI), this paper analyzed and compared eight kinds of spatial domain unwrapping algorithms, among which five global optimization algorithms were selected, including WLS (weighted least square), PRELUDE (phase region expanding labeler for unwrapping discrete estimations), PUMA (phase unwrapping max-flow/min-cut), ARM (accumulation of residual maps), and SL-MC (sorted list, multi-clustering); and three integral algorithms were selected, including Branch-cut, WFF-QG (windowed Fourier-filtered and quality-guided method), and PUROR (phase unwrapping using recursive orthogonal referring). Experiments were carried out by using two sets of MATLAB simulation images and two sets of 1.5T real SWI data provided by Alltech. The reliability of the unwrapping methods was evaluated by using differences between wrapped and re-wrapped phase and time. The results show that the P±\|M\| value of PUROR was zero and it had the fastest running time, which implied the application potential in clinical practices.
		2018 Vol. 37 (2): 129-137 [Abstract] ( 434 ) HTML (1 KB) PDF (840 KB) ( 591 )

	138	Cervical Image Segmentation Based on Modified k Means Algorithm and Gaussian Mixture Model
		Liu Jun, Yu Tingting, Shi Huijuan
		DOI: 10.3969/j.issn.0258-8021.2018.02.002
		In order to segment the cervix region from colposcope images in the intelligent cervix cancer screening system, a kind of method based on modified k means algorithm and Gaussian mixture model was developed in this paper. Firstly, the data set to be classified was constructed according to the representative color of the cervix region and the distance to the image center point. Secondly, by recalculating the representative color of the cervix region, a dynamic regulation which enable the data set to be classified keep updating with the iteration was added in the k means algorithm, thus the k means algorithm can be applied to target images that obtained under different light environment. Lastly, the segmentation result was obtained by Gaussian mixture model that initialized by the result of the modified k means algorithm. 75 sets of cervical images that photographed under different conditions were used in the experiments. The results on these data showed that developed method gained a mean accuracy of 65.1%, which is 5.5%,5.8% and 8.5% higher comparing with the k means initialized Gaussian mixture model algorithm, fuzzy C means algorithm and basic Gaussian mixture model algorithm separately. It also gained a standard deviation of 11.5%, which is 5.6% lower comparing with level set algorithm. The results in these experiments proved the effectivity of the developed method in the cervix region segmentation from colposcope images.
		2018 Vol. 37 (2): 138-145 [Abstract] ( 426 ) HTML (1 KB) PDF (834 KB) ( 438 )

	146	Study on the Brain Network Characteristics before and after the Operation of Frontotemporal Tumor Patients
		Yang Yuxuan, Tao Ling, Qian Zhiyu, Xue Li, Yu Yun
		DOI: 10.3969/j.issn.0258-8021.2018.02.003
		Brain injury and surgery in brain tumor patients are the most concerned problems in clinical treatments. Based on resting state functional magnetic resonance imaging (fMRI) technology and small world network analysis method, this paper is to study the effect of tumor on the brain's default mode network and sensory motor network in 9 patients with temporal frontal lobe tumor. And the changes of brain function network characteristics were studied by tumor resection. First, the effect of the tumor and resection on the brain's default network and sensory motor network was studied based on the ICA method. Then, the small world network of the patients and normal control group were constructed. The network topology and network parameters were analyzed. We used the betweenness centrality to find out groups of brain functional network core node, and a comparative analysis of changes in patients and normal people at the core node, and preoperative and postoperative core nodes change. Finally, a comparative analysis was conducted on the patients before surgery and after the default mode networks and sensory motor network midbrain region specific changes. The results showed that the nerve activity in default mode network and sensory sports network became lower, suggesting significant damage caused by the tumor in the brain of two modules endogenous network. The small-world attributes(σ=γ/λ)of the patients were significantly reduced (preoperative: 3.591±0.302, postoperative: 3.263±0.174), the cluster coefficients were significantly lower (preoperative: 0.482±0.007, postoperative: 0.454±0.011), and the core nodes shifted to the contralateral side of the tumor. In default network, the resection of the tumor after the operation makes the right brain area activity becomes stronger (preoperative: 0.0125±0.0005, postoperative: 0.0184±0.0010). The activity of the left side of the brain is alleviated. (preoperative: 0.0180±0.0011, postoperative: 0.0122±0.0006). Through the study of the patient's default mode network and sensory motor network, the temporal frontal lobe tumor has a certain effect on the patient's cognitive ability and motor ability, and these abilities could be recovered after surgery.
		2018 Vol. 37 (2): 146-154 [Abstract] ( 389 ) HTML (1 KB) PDF (790 KB) ( 395 )

	155	Multi-modal MRI Image Registration Based on Adaptive Diffeomorphic Multi-Resolution Demons Algorithm
		Wang Chang, Ren Qiongqiong, Qin Xin, Liu Yan, Li Zhenxin, Yu Yi
		DOI: 10.3969/j.issn.0258-8021.2018.02.004
		Diffeomorphic Demons can guarantee the deformation smooth and reversible and avoid producing unreasonable deformation simultaneously. But its iterations need to be set manually and have great impact on registration results. In order to solve this problem, the adaptive diffeomorphic multi-resolution demons was proposed in this paper. Firstly optimization theory framework of non-rigid registration and multi-resolution strategy were used, then similarity energy function based on gray level was designed, and termination condition was set, finally the iteration number was realized adaptively. Check board image, same modality and different modality MRI were tested, quantitative analysis was made using registration evaluation index, and the influence of different driving forces and parameters on registration result were analyzed. Experimental results indicated that, for the same modality of MRI, the mean square error was 514.7965, normalized cross correlation was 0.9993, structural similarity was 0.9948 by this method. For the different modality of MRI, the mean square error was 1354.1, normalized cross correlation was 0.5935, structural similarity was 0.5116. The Mean square error ws the lowest, normalized cross correlation and structural similarity was the highest. In conclusion, this method is effective and robust, showing the application potential in the non-rigid registration of MRI images.
		2018 Vol. 37 (2): 155-162 [Abstract] ( 350 ) HTML (1 KB) PDF (774 KB) ( 465 )

	163	Automatic Detection of Leukocytes in Leucorrhea Based on Convolution Neural Network
		Zhong Ya, Zhang Jing, Xiao Jun
		DOI: 10.3969/j.issn.0258-8021.2018.02.005
		As the most common gynecological examination items, leucorrhea routine examination has a wide application and an important position in clinical testing. In view of the importance of leukocytes in clinical medicine and the many deficiencies of current detection methods, this paper focuses on the automatic detection of leukocytes. Microscopic images were obtained in a local hospital through a leucorrhea automatic detector. After filtering, the images were enhanced and segmented. The sample library was established, and the feature extraction and classification were done based on the convolution neural network. Finally, the validity of the method was verified by cross validation. In the automatic detection of leukocytes, for a dataset consisting of twenty thousand samples, our proposed method achieved 95% in sensitivity, 84% in specificity and 89.5% in accuracy, which meet the requirement of medical clinical testing. The digital image processing technology and the convolution neural network are applied to the detection of leukocytes in medical microscopic images. The proposed method solves the key problem of characteristic expression, verifies the feasibility of automatic identification, and improves the quality and efficiency of detection.
		2018 Vol. 37 (2): 163-168 [Abstract] ( 455 ) HTML (1 KB) PDF (789 KB) ( 1207 )

	169	Prediction of Near-Term Breast Cancer Risk in Mediolateral Oblique View of Mammography
		Li Yane, Zhang Peng, Fan Ming, Zheng Bin, Li Lihua
		DOI: 10.3969/j.issn.0258-8021.2018.02.006
		This study proposed a model for the prediction of near-term breast cancer risk in mediolateral oblique view (MLO) of negative full-field digital mammography (FFDM) images based on local and global region bilateral asymmetry features. The retrospective dataset included series of two sequential FFDM examinations of 556 women. In the “current” examination 278 women were diagnosed with pathology verified cancers and 278 cases remained negative. Patients’ age for breast cancers and negative cases were matched. After region of interest include local and global regions were segmented, spatial distribution, structural similarity and positional information related features were extracted. After decorrelation process, 7 features with Spearman correlations >0.6 were excluded and 78 features were remained for further analyses. Next, a short-term breast cancer risk prediction model was built using a leave-one-case-out cross-validation method to predict the likelihood of each woman having image-detectable cancer in the next sequential mammography screening. The computed areas under a receiver operating characteristic curves (AUC) was 0.6667±0.0226 with the specificity and sensitivity were 0.6906 and 0.5216 respectively when combined global-and local-based features. The odds ratio values was increased with a significantly increasing trend in slope (P=0.002033) as the model-generated risk score increased. In addition, for the three age groups of 37-49, 50-65 and 66-87 years old, the AUC values were 0.681 0±0.043 2,0.671 6±0.030 0 and 0.678 2±0.054 7 with the specificity were 0.702 7, 0.694 3 and0.723 4 and sensitivity were 0.554 1, 0.490 4 and 0.574 5 respectively. And AUC values of0.654 5 and 0.694 4 were yielded for BIRADS 2 and BIRADS 3, respectively. With the specificity were0.676 2 and 0.733 3 and sensitivity were 0.522 9 and 0.536 9 for BIRADS 2 and BIRADS 3, respectively. This study demonstrated the potential of bilateral asymmetry features extracted from MLO view mammography to assist the prediction of near-term breast cancer risk.
		2018 Vol. 37 (2): 169-180 [Abstract] ( 320 ) HTML (1 KB) PDF (843 KB) ( 344 )

	181	Study of B₁ Mapping Methods Based on the Amplitude of MRI
		Deng Guanhua, Lan Maoying, Duan Song, Wang Jiajia, Hu Can, Xin Xuegang
		DOI: 10.3969/j.issn.0258-8021.2018.02.007
		Recently developed technique of in vivo magnetic resonance electrical tomography (MR EPT) can extract the electrical properties of human tissues by using the information of B₁field. Thus, robust B₁ mapping technique, regarded as the base of the technique of MR EPT, is critical for MR EPT, because the quality of B₁ maps directly affects the accuracy of MR EPT. In this paper, the B₁ field scale factor (R_i) for double angle methods (DAM), saturated turbo flash (satTFL) in the scan of the phantom and human head were calculated using the FDTD simulation, and then the performance of DAM and satTFL was evaluated based on the mean relative difference(MRD). The results indicated that the difference of R_i between above methods was less than 10% in the tissue with low dielectric properties; on the contrary, the value of R_i of DAM was higher than that of satTFL, in the tissue with high dielectric properties such as cerebrospinal fluid, even up to 21% for DAM. The research of this study can be used to select the appropriate B₁ mapping technique for different dielectric property tissues and promote the practical application of MR EPT technology.
		2018 Vol. 37 (2): 181-187 [Abstract] ( 432 ) HTML (1 KB) PDF (789 KB) ( 744 )

	188	Study on Mechanical Characteristics of Massage for Knee Osteoarthritis and Fatigue Status of Upper Limb Core Muscle Group
		Wang Peng, Wang Shuyi, Gong Li, Du Yunxiao, Zuo Yan
		DOI: 10.3969/j.issn.0258-8021.2018.02.008
		The aim of this study was to investigate the biomechanical and physiological (surface electromyography) characteristics of massage for knee osteoarthritis, analyze the mechanical properties of this manipulation maneuver quantitatively, and establish a method to objectively evaluate the fatigue status of the upper limb muscle groups of the massage physicians. Ten massage physicians were recruited to collect the vertical pressure of thumb and the surface electromyogram of upper limbs in real time to calculate the vertical strength and the time ratio between secondary work period and primary work period. This paper was to study the upper limb core muscle group and the fatigue status of the core muscle groups when manipulating the massage techniques. Results showed that the frequency of press was four times in one minute. The duration of primary work period was 4.83±0.88 seconds and secondary work period was 11.43±1.94 seconds. The time ratio between the secondary work period and the primary work period was 2.37±0.63. The average vertical strength of the massage manipulation was 228±13N. According to descending order of the integrated EMG(iEMG)and contribution rate of the upper limb muscle groups, the core muscles of the upper limbs were the thumb muscle (8.32±0.29,21.65%), the flexor carpi ulnaris (5.67±0.32,14.74%), the triceps(4.79±0.36,12.46%), and the flexor carpi radialis (4.60±0.12,11.96%). In a 4 min massage process, the degree of decline of the average median frequency (MF) and average mean power frequency (MPF) of the thumb muscle were the largest. They are 30% and 22% respectively. So the thumb muscle was more prone to fatigue. Therefore, the biomechanical characteristics and physiology (surface electromyography) characteristics of the massage techniques of knee osteoarthritis in this paper will lay the foundation for the follow-up research of human engineering and the development of an automated device which can replace the manipulation of massage doctors.
		2018 Vol. 37 (2): 188-193 [Abstract] ( 350 ) HTML (1 KB) PDF (803 KB) ( 403 )

	194	Construction and Simulation of Constitutive Model of PeriodontalLigament Based on Hyperelasticity-Viscoelasticity
		Wu Jianlei, Peng Wei, Dong Huiyue, Jiang Xianfeng, Liu Yunfeng
		DOI: 10.3969/j.issn.0258-8021.2018.02.009
		In order to describe the biomechanical behaviors of PDL (periodontal ligament) accurately, based on the theory of continuum mechanics in large deformation and the hypothesis of incompressible isotropy, a hyperelastic-viscoelastic model of PDL and parameters were constructed by data fitting function in finite element software ABAQUS based on experimental data of plane shear and stress relaxation of human PDL. Then, the PDL hyperelastic-viscoelastic model was evaluated on the accuracy through simulations to the plane shear experiments of five PDL specimens. Finally, the mechanical responses to loads of PDL linear elastic model and hyperelastic-viscoelastic model were compared and analyzed by finite element simulations. The results indicated PDL was approximately expressed by linear elastic model when the displacements of root were within 0～0.06 mm, while hyperelastic-viscoelastic model was more accurate to describe the material characteristics of PDL when the displacements exceed 0.06 mm, meanwhile a significant difference between two models could be observed. Based on this study, a practical PDL hyperelastic-viscoelastic model was acquired and a strong theoretical foundation was constructed for orthodontic biomechanical investigating and accurate treatment planning.
		2018 Vol. 37 (2): 194-201 [Abstract] ( 496 ) HTML (1 KB) PDF (762 KB) ( 564 )

	202	Preparation and Characterization of a Brain Decellularized Scaffold
		Zheng Fangping, Mao Kaili, Zhao Yingzheng
		DOI: 10.3969/j.issn.0258-8021.2018.02.010
		The aim of this work is to prepare a brain decellularized scaffold by chemical extraction combined with oscillation, and to perform preliminary characterization. Twenty SD rats were divided into decellularization and control group. In the decellularization group, the brain extracellular matrix (dBECM) was prepared by chemical extraction combined with oscillation, successively with 3% TritionX-100, 1%SDS,4% deoxycholic acid sodium and deionized water in 37℃. The microscopic morphology of dBECM was observed by scanning electron microscopy. The decellularization was analyzed by HE staining and DAPI staining. The components were identified by Masson staining and immunofluorescence staining. A lot of collagen fibers could be seen with HE and immunohistochemistry stain but no visible cell nuclei remained after decellularization. The degree of decellularization was about 99%. Masson staining and immunofluorescence staining revealed that dBECM retained elastin (4±1.1%), laminin (19±1.6%), fibronectin (9±2.1%) and collagen IV (16±1.9%). In conclusion, the method of chemical extraction combined with oscillation can effectively remove all cellular components while retain the extracellular matrix and three-dimensional structure. It is a convenient and ideal preparation method on decellularized brain scaffold for tissue engineering.
		2018 Vol. 37 (2): 202-207 [Abstract] ( 339 ) HTML (1 KB) PDF (738 KB) ( 323 )

Reviews

	208	Research Advancements in the Regulation of Transcranial Direct Current Stimulation (tDCS) for Cerebral Cognitive Function
		Zhou Peng, Wei Jinwen, Sun Chang, Qi Hongzhi, Ming Dong
		DOI: 10.3969/j.issn.0258-8021.2018.02.011
		Transcranial direct current stimulation (tDCS) is a noninvasive technique that regulates neuronal activity in the cerebral cortex by using constant and low intensity direct current (0.5-2 mA) with duration of typically 5 to 30 minutes. Due to its low cost, high portability and excellent regulation effects, in recent years, transcranial direct current stimulation has been widely studied and applied in the fields of neuroscience and neuropathology. This paper introduced its physiological effects and approaches of implementation, and discussed the current research status and development trend of tDCS applied to the regulation of cognitive functions in the aspects of learning and memory, attention, perception, emotion and decision.
		2018 Vol. 37 (2): 208-214 [Abstract] ( 462 ) HTML (1 KB) PDF (809 KB) ( 1312 )

	215	Progress of Low-Field Nuclear Magnetic Resonance Imaging in Extremely Inhomogeneous Magnetic Field
		Miao Zhiying, Xia Tian, Wang Hongzhi, Ma Junshan
		DOI: 10.3969/j.issn.0258-8021.2018.02.012
		Conventional MRI (magnetic resonance imaging) equipments are usually bulky, expensive, large noise and difficult to set up, which limits their wide application. Low field mobile MRI devices are expected to solve these disadvantages. In the conventional magnetic resonance imaging, small sample is surrounded by a large magnet and the image is taken in the highly uniform magnetic environment (<5 ppm/40 mm DSV). The hardware design of the conventional magnetic resonance imaging and its corresponding technology are relatively mature and perfect. The open NMR (nuclear magnetic resonance) system is based on extremely inhomogeneous magnetic field conditions (>1000 ppm/mm DSV), and has a wide gap between the traditional hardware design and imaging techniques, and the difficulty is also increased dramatically. This paper reviews the origin, development and key technologies of the low field open magnetic resonance imaging technology, including hardware such as magnet, RF coil, gradient coil and method such as the design of radio frequency pulses, imaging sequence, image post processing. The aim of the review is to provide insights about the research and development of mobile MRI equipment.
		2018 Vol. 37 (2): 215-228 [Abstract] ( 435 ) HTML (1 KB) PDF (857 KB) ( 860 )

	229	Recent Advances in Quantitative Assessment of Parkinsonian Motor Symptoms Based on Wearable Devices
		Dai Houde, Xiong Yongsheng, Cai Guoen, Lin Zhirong, Ye Qinyong
		DOI: 10.3969/j.issn.0258-8021.2018.02.013
		The quantitative assessment of motor symptoms of Parkinson's disease (PD) has remained a significant challenge since PD was first defined in 1817. However, with benefits of MEMS (Micro-Electro-Mechanical Systems) motion sensors for high-precision motion tracking, together with the multivariate statistical analysis and estimation theory, PD motor symptoms quantification has become available. In this article, at first, the MEMS motion sensing technique and the typical wearable systems for the quantification of PD motor symptoms were introduced. Secondly, the quantification methods of the four primary motor symptoms and their correlations to the UPDRS judgments of neurologists were compared and analyzed. After that, the impacts of motor fluctuations and the side effects of treatments such as dyskinesia for the quantification of PD symptoms were discussed. This paper also introduced the recent advances in quantitative assessment of parkinsonian motor symptoms based on wearable devices, and provides a system structure for the research of quantitative assessment of PD motor symptoms.
		2018 Vol. 37 (2): 229-236 [Abstract] ( 442 ) HTML (1 KB) PDF (804 KB) ( 900 )

	237	A Methodological Review on Morphometric Parameters of Micro-CT Trabecular Bone Images
		Liu Rong, Guo Xinlu, Zhang Yakun, Wang Yongxuan
		DOI: 10.3969/j.issn.0258-8021.2018.02.014
		Osteoporosis is one of the hotspots in the orthopedic field. Some studies have revealed that not only the changes in bone mineral density (bone mass) but also changes of trabecular bone structure are pathogenic factors. The trabecular bone morphometric analysis is one kinds of important method to study trabecular bone structure change. In this paper, some methods to calculate the trabecular bone morphometric parameters based on Micro-CT images were introduced, such as trabecular anisotropy, connectivity, structure model index, texture and other trabecular bone characteristics. Meanwhile, some examples were given to summarize the applicability, pros and cons of the trabecular bone morphometric parameters to provide evidence for the effective evaluation of osteoporosis and drug treatment.
		2018 Vol. 37 (2): 237-246 [Abstract] ( 939 ) HTML (1 KB) PDF (852 KB) ( 2663 )

Communications

	247	The Effect on White Matter Diffusivity of Prolonged Dance Training: A TBSS Study
		Li Gujing, Li Xin, He Hui, Gong Jinnan, Luo Cheng, Yao Dezhong
		DOI: 10.3969/j.issn.0258-8021.2018.02.015

		2018 Vol. 37 (2): 247-251 [Abstract] ( 330 ) HTML (1 KB) PDF (733 KB) ( 604 )

	252	Assessment of Lead Shielding Protective Effect Based on Body Mass Index
		Li Shuai, Chao Yong, Li Tianran, Xu Qiming, Li Qin
		DOI: 10.3969/j.issn.0258-8021.2018.02.016

		2018 Vol. 37 (2): 252-256 [Abstract] ( 320 ) HTML (1 KB) PDF (766 KB) ( 534 )

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