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Geometric shape representation algorithms are key technologies in the fields of computer graphics and geometric modeling. The Medial Axis Transform (MAT) is an important geometric model description tool that provides a simplified representation of complex geometric shapes while ensuring accurate descriptions of geometric shape and topology. Therefore, it can meet the requirements of many modern research fields, including geometric modeling, pattern recognition, model segmentation, model deformation, physical simulation, path planning, and more. This paper first introduces the basic concept of the medial axis transform, including the definition of the medial axis transform and the concept of medial axis primitives. It then describes the extraction algorithms for the medial axis transform, specific research on the medial axis transform in computer vision and computer graphics, potential applications of the medial axis transform, and medial axis transform datasets. Finally, the disadvantages and advantages of the medial axis transform are discussed, and some suggestions on possible future research directions are presented.

Background Percutaneous vertebral augmentation (PVA) is widely applied for the treatment of osteoporotic vertebral fractures. The degree of vertebral body height restoration and deformity correction after the procedure is not consistent. Methods We retrospectively reviewed 97 patients who underwent PVA, because of osteoporotic vertebral compression fractures. The following data about the patients were recorded: age, sex, bone density, number of treated vertebrae, severity of fracture of the treated vertebrae, operative approach (PVP or PKP), volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, cement leakage, postoperative vertebral body height restoration ratio, follow-up period, and latest follow-up height loss ratio. Bivariate regression analysis and t-test were applied for univariate analysis, while multivariate linear regression analysis was applied for multivariate analysis. Results The postoperative vertebral body height restoration ratio was (14.7% ± 15.2%), and the last follow-up height loss ratio was (13.5% ± 11.5%). The multivariate analysis showed that the number of treated vertebrae, preoperative vertebral compression ratio, and preoperative local kyphosis angle are the main factors influencing the postoperative vertebral body height restoration. The univariate analysis also showed that only the postoperative vertebral body height restoration ratio is related to the last follow-up height loss ratio. Conclusions The number of treated vertebrae, preoperative vertebral compression ratio, and preoperative local kyphosis angle are the main influencing factors of patients' vertebral body height restoration after PVA, and the postoperative vertebral body height restoration ratio is the main factor influencing the last follow-up height loss ratio.

A meta-analysis of randomized controlled trials (RCTs) was performed to compare the incidence of cement leakage between unilateral and bilateral percutaneous vertebral augmentation (PVA) in treating osteoporotic vertebral compression fractures (OVCFs).PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials were searched to retrieve the reported data from the establishment of the databases until August 1, 2018. The RCTs on unilateral and bilateral PVA for OVCFs were included. RevMan software, version 5.3, was used for the meta-analysis.Six RCTs were selected from the reported data. The studies included a total of 676 vertebras, 339 of which had received unilateral PVA and the rest, bilateral PVA. The incidence of cement leakage in the unilateral PVA group was less than that in the bilateral PVA group, and the difference between the 2 groups was statistically significant (risk ratio, 0.50; 95% confidence interval, 0.35-0.72; P = 0.0002). The cement dosage in the unilateral PVA group was less than that in the bilateral PVA group, and the difference between the 2 groups was statistically significant (weighted mean difference, -1.98; 95% confidence interval, -2.24 to -1.72; P0.00001). The cement dosage and the incidence of cement leakage in the unilateral PVA group were lower than those in the bilateral PVA group.The results of our meta-analysis have provided sufficient evidence to show that the unilateral approach can decrease the incidence of cement leakage in PVA. We believe the unilateral approach could reduce the risk of cement leakage owing to the lower cement dosage in the treated vertebra.

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Descriptive study.This study aimed to evaluate the hidden blood loss (HBL) of patients who underwent lumbar fusion surgery for degenerative spine and to analyze its risk factors.When planning transfusion strategies, blood loss calculation is important. However, in clinical practice, spine surgeons usually ignore the possibility that a large amount of HBL may occur after lumbar fusion surgery.We studied the patients who underwent posterior lumbar fusion (PLF) surgery for degenerative spine from 2014 to 2015 in one institution. The patient's demographics, comorbid conditions, coagulation panel value, surgical time, number of levels fused, American Society of Anesthesiologists (ASA) classification, cell saver, preoperative hematocrit level, preoperative hemoglobin level, and postoperative complications were collected retrospectively. Pearson correlation analyses were used to find an association between patient characteristics and HBL. Multivariate linear analysis was used to determine independent risk factors of HBL.We reviewed 169 consecutive patients who underwent PLF surgery for degenerative spine in one institution. The mean amount of HBL was 588 mL, which was 39% of the total blood loss. On the basis of the model of multiple linear regression analysis, the multilevel fusion (P=0.001), surgical time (P=0.034), and fibrinogen level (P=0.027) were independent risk factors that contributed to HBL, but age of 60 years or above (P=0.110), postoperative complications (P=0.278), and cell saver were not (P=0.739).We conclude that a large amount of HBL may occur in patients who underwent PLF surgery for degenerative spine. In addition, significant hidden loss may have a correlation with postoperative mortality. Multilevel fused, surgical time, and fibrinogen level should be paid close attention when considering strategies of fluid infusion and blood transfusion.

Study Design A retrospective study. Objectives Anterior cervical fusion surgery is widely used procedure in cervical spondylosis. When considering the blood reinfusion strategies of cervical fusion surgery, the amount of blood loss is one of the key elements. We usually calculate the blood loss according to the surgical bleeding plus the postoperative drainage; however, this method ignores the possibility that there may be hidden blood loss (HBL). Methods We performed a retrospective study to determine the risk factors for HBL in patients who underwent anterior cervical fusion surgery for degenerative spine from 2013 to 2016. The Pearson correlation, Spearman correlation, and multivariate liner analysis were used to find association between patient characteristics and HBL. Results A total of 107 consecutive patients who underwent anterior cervical fusion surgery for degenerative spine in our hospital were reviewed. The amount of HBL was 261 mL, or 50% of the total blood loss. According to the model of multiple linear regression analysis, patient sex ( P = 0.028) and American Society of Anesthesiologists physical status classification ( P = 0.029) were independent risk factors contributing to HBL, but preoperative hematocrit was not ( P = 0.741). Conclusions We concluded that sex and American Society of Anesthesiologists physical status classification were independent risk factors of HBL in anterior cervical fusion surgery. In addition, there was a high proportion of HBL in anterior cervical fusion. When considering the strategies of transfusion, we should pay attention to the risk factors for HBL.

Osteoporosis is a common age-related disorder characterized by low bone mass and deterioration in bone microarchitecture, leading to increased skeletal fragility and fracture risk. The pathophysiology of osteoporosis is multifactorial. It is related to the imbalance between osteoblasts and osteoclasts; reduced bone mass and increased adipogenesis in the bone marrow. Moreover, angiogenesis, inflammatory process and miRNAs have shown effects in the formation of osteoporosis. In the recent years, mesenchymal stem cells (MSCs) have been regarded as an excellent choice for cell-based tissue engineering therapy of osteoporosis. Growing evidence showed that paracrine effect has been considered as the predominant mechanism for the role of MSCs in tissue repair. Recently, many studies have proposed that MSCs-derived exosomes are effective for a variety of diseases like cancer, cardiovascular diseases, etc. However, whether the MSCs-derived exosomes could serve as a novel therapeutic tool for osteoporosis has not clearly described. In this review, we summarize the MSCs-derived exosomes and the relationship with osteogenesis, osteoclast differentiation, angiogenesis, immune processes and miRNAs. Finally, we suggest that MSCs-derived exosomes might be a promising therapeutic method for osteoporosis in the future.

Background Under the transcriptional control of numerous factors and intracellular signals, mesenchymal stem cells (MSCs) can differentiate into various cell types, including adipocytes and osteoblasts. However, the precise cellular signaling factors that determine the cell fate of MSCs in bone marrow remain largely unknown. Objective In this review, we focus on the ties of PPAR-γ and Wnt signaling in MSC differentiation into adipocytes and osteoblasts. Results Peroxisome proliferator-activated receptor-γ (PPAR-γ) is well established as a prime inducer of adipogenesis, while the Wnt pathway is regarded as the master moderator of osteogenesis. A theoretical inverse relationship exists between adipogenic and osteogenic lineage commitment and differentiation: the differentiation toward an osteoblast phenotype occurs at the expense of an adipocyte phenotype. Conclusion It has been proposed that the balance between osteogenic and adipogeneic MSC differentiation is disrupted in diverse areas of human health. Therefore, understanding the ties between PPAR- γand Wnt signaling in MSC differentiation has significant implications in diverse areas of human health, from obesity to osteoporosis to regenerative medicine.

Study design: The related factors for the vertebral height restoration were retrospectively reviewed in 97 patients who underwent percutaneous vertebral augmentation (PVA). Objective: To discuss the factors associated with the vertebral body height restoration and follow-up height loss of patients underwent PVA for osteoporotic vertebral compression fractures. Background: PVA is widely applied for the treatment of osteoporotic vertebral fractures. The degree of vertebral body height restoration and deformity correction after the procedure is not consistent. Methods: We retrospectively reviewed 97 patients who underwent PVA, because of osteoporotic vertebral compression fractures. The following data about the patients were recorded: age, gender, bone density, number of treated vertebrae, severity of fracture of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, cement leakage, postoperative vertebral body height restoration ratio, follow-up period, and latest follow-up height loss ratio. Bivariate regression analysis and t-test were applied for univariate analysis, while multivariate linear regression analysis was applied for multivariate analysis. Results: The postoperative vertebral body height restoration ratio was (14.7 ± 15.2)% and the last follow-up height loss ratio was (13.5 ± 11.5)%. The multivariate analysis showed that the number of treated vertebrae, preoperative vertebral compression ratio, and preoperative local kyphosis angle are the main factors influencing the postoperative vertebral body height restoration. The univariate analysis also showed that only the postoperative vertebral body height restoration ratio is related to the last follow-up height loss ratio. Conclusion: The number of treated vertebrae, preoperative vertebral compression ratio and preoperative local kyphosis angle are the main influencing factors of patients’ vertebral body height restoration after PVA and the postoperative vertebral body height restoration ratio is the main factor influencing the last follow-up height loss ratio.

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA).To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures.PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial.A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis.The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively.High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

A meta-analysis of randomized controlled trials was performed that compares the relationship between percutaneous vertebral augmentation (PVA) and conservative treatments with the incidence of new vertebral fractures. Using meta-analytic techniques, this study compares PVA and conservative treatment for incidence of new vertebral fractures, particularly incidence of adjacent fractures that occur following treatment.A focus of clinicians has been on whether PVA increases the risk of new vertebral fractures. Pubmed, EMBASE, and the Cochrane Central Register of Controlled Trials were searched to retrieve literature published from the establishment of the databases until April 28, 2015. Literature of related areas was searched manually. The main outcome indicator was the incidence of new vertebral fractures at final follow-up appointment. In addition, we evaluated the incidence of new vertebral fractures in different follow-up periods and the incidence of adjacent fractures. The RevMan 5.3 software program of the Cochrane Collaboration was used to analyze the data. For dichotomous variables, the risk ratio (RR) and a confidence interval (CI) of 95% were used to express the heterogeneity of the effect size. Seven randomized controlled trial studies were selected from the literature. The studies include 871 patients, 436 of whom received PVA treatment and the rest received conservative treatment. Combined analysis of the 7 studies showed that the numbers of new vertebral fractures in the 2 groups are not significantly different. Six studies reported the numbers of new adjacent fractures. Considering the heterogeneity among the studies, 2 subgroups were formed. The 5 studies in the European group showed that the incidence of new adjacent fractures in the PVA-treated group is higher than that in the conservatively treated group, and the difference is statistically significant. The one study in the Asian group showed no significant difference between the incidences of adjacent fractures in the 2 groups. PVA treatment does not increase the incidence of new vertebral fractures. Most studies reported that PVA increases the incidence of adjacent fractures, yet it is rarely stated that both PVA and conservative treatment lead to the same incidence of adjacent fractures.

The weighting exponent m is an important parameter in fuzzy c-means (FCM) algorithm. In this paper, three basic problems about m in FCM algorithm: clustering validity method based on optimal m (or whether does optimal m exist), how does m effect on the performance of fuzzy clustering, and which is the proper range of m in general applications, are studied with the knee of objective function Jm, and fuzzy decision-making methods. Numerical experimental results show that the optimal m* for specific data set does exist. Moreover, a group of numerical experimental results indicate that, within the range of m (epsilon) (1.5, 3.5), the optimal m* monotone increase linearly against the separability (rho) of data set. So in practical applications, one can choose the value of m within the range of [1.5, 3.5].

This paper proposes a novel method for on-line recognition of line-based graphic symbol. The input strokes are usually warped into a cursive form due to the sundry drawing style, and classifying them is very difficult. To deal with this, an ART-2 neural network is used to classify the input strokes. It has the advantages of high recognition rate, less recognition time and forming classes in a self-organized manner. The symbol recognition is achieved by an Attribute Relational Graph (ARG) matching algorithm. The ARG is very efficient for representing complex objects, but computation cost is very high. To over come this, we suggest a fast graph matching algorithm using symbol structure information. The experimental results show that the proposed method is effective for recognition of symbols with hierarchical structure.

This paper studies a design method of decentralized signal detection system which consists of the adaptive fuzzied local detectors and a data fusion rule of self-learning the weights on-line. The local detectors for the inaccurate signal parameters are modeled by means of fuzzy sets. Such a model can be adapted to change of the inaccurate signal parameters. The data fusion center can learn itself the local decision weights on-line based on the optimal decision rules. The combination the robustness of the fuzzied local detectors and the adaptability of the self-learned fusion rule make it true that the detection performance of the decentralized signal detection with an unknown parameter of unknown distribution and non-random unknown parameter.

In this paper, a neural networks based approach for distortion invariant image recognition is presented. To reduce the dimension of the required networks, as well as to achieve invariancy, six distortion-invariant feature are extracted from each image and are used as inputs to the neural networks. These six features are derived from the modified geometrical moments of the image, which are calculated through a corrected discrete formula for computing moments more accurately. A multilayer perceptron network trained by the back-propagation algorithm can carry out the classification based on the above features. Experimental results on industrial tools and character recognition are to be given.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper proposes an improvement of the approximate fuzzy c-means (AFCM) clustering algorithm, called BAFCM, that is based on a fast method for edge detection using fuzzy sets which is used to initialize the c clusters effectively. Our results show that the BAFCM requires about half as much computer time as the AFCM while yielding the same accuracy as the AFCM. One may use BAFCM to accelerate AFCM processing.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Kohonen networks are well known for clustering analysis. Classical Kohonen networks for hard c-means clustering (trained by winner-take-all learning) have some severe drawbacks. Fuzzy Kohonen networks (FKCNN) for fuzzy c-means clustering are trained by fuzzy competition learning, and can get better clustering results than the classical Kohonen networks. However, both winner-take-all and fuzzy competition learning algorithms are in essence local search techniques that search for the optimum by using a hill-climbing technique. Thus, they often fail in the search for the global optimum. In this paper we combine genetic algorithms (GAs) with fuzzy competition learning to train the FKCNN. Our experimental results show that the proposed GA/FC learning algorithm has much higher probabilities of finding the global optimal solutions than either the winner-take-all or the fuzzy competition learning.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Radial basis function(RBF) neural networks have been used extensively in many applications for their simple ar-chitecture and fast learning. This paper principally discusses the training problem of RBF classifiers which canbe used for classification. For RBF classifiers, how to correctly initialize the number of network hidden nodes andtheir parameters is very important. Genetic-based Gaussian kernel clustering method and fuzzy decision techniqueare explored to complete this work. Then the network is trained further with back propagation learning algorithmin order to attain optimal performance. Results from the typical experiments are used to illustrate the pow and efficiency of the method. Keywords: radial basis function, neural networks, classifiers, training algorithms, clustering, fuzzy decision 1.INTRODUCTION RBF neural network is an important type of the multilayer feed-forward neural networks which have becomevery powerful tool in the domain of pattern recognition. It is a two-layer network whose output nodes form a linear