Segmentation of CT Lung Images Using FCM with Active Contour and CNN Classifier

Objective: Lung cancer is one of the unsafe diseases for human which reduces the patient life time. Generally, most of the lung cancers are identified after it has been spread into the lung parts and moreover it is difficult to find the lung cancer at the early stage. It requires radiologist and special doctors to find the tumoral tissue of the lung cancer. For this reason, the recommended work helps to segment the tumoral tissue of CT lung image in an effective way. Methods:  The research work uses hybrid segmentation technique to separate the lung cancer cells to diagnose the lung tumour. It is a technique which combines active contour along with Fuzzy c means to diagnose the tumoral tissue. Further the segmented portion was trained by Convolutional Neural Network (CNN) in order to classify the segmented region as normal or abnormal. Results: The evaluation of the proposed method was done by analyzing the results of test image with the ground truth image. Finally, the results of the implemented technique provided good accuracy, Peak signal to noise ratio (PSNR), Mean Square Error (MSE) value. In future the other techniques can be utilized to improve the details before segmentation. The proposed work provides 96.67 % accuracy. Conclusion: Hybrid segmentation technique involves several steps like preprocessing, binarization, thresholding, segmentation and feature extraction using GLCM.     

TOPSIS法和秩和比法模糊联合在基本公共卫生服务质量综合评价中的应用研究

背景国家基本公共卫生服务项目的开展是我国新医改的重要举措，自2009年国家基本公共卫生服务项目开展后，其服务经费与服务项目不断扩增，由于涉及指标较多，覆盖面较广，探寻科学、客观、全面的基本公共卫生服务综合评价方法十分必要。目的探索适宜的基本公共卫生服务质量综合评价方法，通过质量评价为调整相关政策和提高服务质量提供依据。方法2019年2—4月，采用多阶段立意抽样方式从Z省南部、中部和北部地区共选取24家社区卫生服务中心（乡镇卫生院）作为评价对象，记为机构A~X。采用逼近理想解排序法（TOPSIS法）、秩和比法及二者模糊联合的方法对24家社区卫生服务中心（乡镇卫生院）2018年基层医疗卫生机构基本公共卫生服务质量进行综合评价（参考2018年国家基本公共卫生服务项目选取12项评价指标）。结果在TOPSIS法评价中，Ci值排名前三名的为A（0.917 4）、C（0.875 9）和G（0.787 9），Ci值排名后三名的为I（0.414 2）、W（0.413 7）和N（0.407 7）。在秩和比法评价中，RSR值排名前三名的为A（0.890 6）、G（0.765 6）和C（0.711 8），RSR值排名后三名的为V（0.381 9）、W（0.362 8）和K（0.357 6）。根据模糊集理论，将W1Ci+W2RSR值进行排序，依据"择多原则"，排名前三名的分别为A、C和G，排名后三名的分别为I、K和W，这与TOPSIS法和秩和比法的评价结果基本一致。结论TOPSIS法和秩和比法模糊联合得到的评价结果及影响因素与其他研究结果相一致，并且两者联用能克服单一使用TOPSIS法或秩和比法的局限性，适宜在基本公共卫生服务质量评价中推广应用。     

Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment

Medication selection for Type 2 Diabetes (T2D) is a challenging medical decision-making problem involving multiple medications that can be prescribed to control the patient’s blood glucose. The wide range of hyperglycemia lowering agents with varying effects and various side effects makes the decision quite difficult. This paper presents computer-aided medical decision support using a fuzzy Multi-Criteria Decision-Making (MCDM) model that hybridizes a Step-wise Weight Assessment Ratio Analysis (SWARA) method with a modification of Fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full multiplicative form (FMULTIMOORA) method for pharmacological therapy selection of T2D. It makes the use of SWARA for obtaining the relative significance of every selected criterion by soliciting experts’ opinions and FMULTIMOORA method for evaluation of each alternative according to all criteria based on a published clinical guideline. In this paper, an extended reference point approach is considered in the proposed hybrid MCDM model that resolves the classic reference point limitations and improves the FMULTIMOORA ranking procedure. Computational results indicate that Metformin is confirmed as the first-line medication and Sulfonylurea as the second-line add-on therapy. The Glucagon-like peptide-1 receptor agonist, Dipeptidyl peptidase-4 inhibitor, and Insulin are placed 3rd, 4th, and 5th, respectively. A sensitivity analysis is conducted to validate the model performance by comparing its result with studies in the literature, other fuzzy MCDM techniques and an interval MULTIMOORA method based on an observational dataset. The close correspondence between the final rankings of anti-diabetic agents resulted from the proposed hybrid model and other methodologies provide significant implications for endocrinologists to refer.     

关键知情人对河南省社区卫生服务机构反应性的评价研究

目的:了解河南省社区卫生服务机构反应性水平。方法:采用制定的《河南省社区卫生反应性调查表(关键知情人)》问卷,调查社区卫生服务机构关键知情人。采用多输入优序图列法确定河南省社区卫生服务机构反应性各维度权重,采用模糊综合评价法评价反应性水平,采用反应性不平等指数测量反应性分布。结果:共调查有效关键知情人431位。问卷各维度Cronbachα系数均大于0.623,总量表Cronbachα系数为0.850;重测信度的各维度相关系数均大于0.907。反应性水平与分布指数分别为8.33和0.2744,各维度重要性排序为:及时关注尊严基础设施交流保密性社会支持选择性自主性。关键知情人认为脆弱人群在社区卫生机构有时或经常受到不公平对待的比例约为50%。结论:关键知情人认为河南省社区卫生服务机构的反应性水平总体较高,反应性分布比较均衡。但认为在基础设施、对患者的隐私保护、与患者的交流沟通等方面存在很大不足。     

Fuzzy model identification of dengue epidemic in Colombia based on multiresolution analysis

ObjectiveThis article presents a model of a dengue and severe dengue epidemic in Colombia based on the cases reported between 1995 and 2011.MethodologyWe present a methodological approach that combines multiresolution analysis and fuzzy systems to represent cases of dengue and severe dengue in Colombia. The performance of this proposal was compared with that obtained by applying traditional fuzzy modeling techniques on the same data set. This comparison was obtained by two performance measures that evaluate the similarity between the original data and the approximate signal: the mean square error and the variance accounted for. Finally, the predictive ability of the proposed technique was evaluated to forecast the number of dengue and severe dengue cases in a horizon of three years (2012–2015). These estimates were validated with a data set that was not included into the training stage of the model.ResultsThe proposed technique allowed the creation of a model that adequately represented the dynamic of a dengue and severe dengue epidemic in Colombia. This technique achieves a significantly superior performance to that obtained with traditional fuzzy modeling techniques: the similarity between the original data and the approximate signal increases from 21.13% to 90.06% and from 18.90% to 76.83% in the case of dengue and severe dengue, respectively. Finally, the developed models generate plausible predictions that resemble validation data. The difference between the cumulative cases reported from January 2012 until July 2013 and those predicted by the model for the same period was 24.99% for dengue and only 4.22% for severe dengue.ConclusionsThe fuzzy model identification technique based on multiresolution analysis produced a proper representation of dengue and severe dengue cases for Colombia despite the complexity and uncertainty that characterize this biological system. Additionally, the obtained models generate plausible predictions that can be used by surveillance authorities to support decision-making oriented to designing and developing control strategies.     

Quantification of coronary arterial stenoses in CTA using fuzzy distance transform

Quantification of coronary arterial stenoses is useful for the diagnosis of several coronary heart diseases. Being noninvasive, economical and informative, computed tomographic angiography (CTA) has become a common modality for monitoring disease status and treatment effects. Here, we present a new method for detecting and quantifying coronary arterial stenosis in CTA using fuzzy distance transform (FDT) approach and a new coherence analysis of observed data for computing expected local diameter. FDT allows computing local depth at each image point in the presence of partial voluming and thus, eliminates the need for binarization, commonly, associated with inclusion of additional errors. In the current method, coronary arterial stenoses are detected and their severities are quantified by analyzing FDT values along the medial axis of an arterial tree obtained by its skeletonization. A new skeletal pruning algorithm has been developed toward improving the quality of medial axes and thereby, enhancing the accuracy of stenosis detection and quantification. Further, we have developed a new method to estimate “expected diameter” along a given arterial branch using a new coherence analysis of observed diameter values along the branch. The overall method is completed in the following steps - (1) fuzzy segmentation of coronary artery in CTA, (2) FDT computation of coronary arteries, (3) medial axis computation, (4) estimation of observed and expected diameters along arteries and (5) detection of stenoses and quantification of arterial blockage. The performance of this method has been quantitatively evaluated on a realistic coronary artery phantom dataset with randomly simulated stenoses and the results have been compared with a binary distance transform based and a conventional binary algorithm. The method has also been applied on a clinical CTA dataset from thirteen heart patients and the results have been compared with an expert's quantitative assessment of stenoses. Results of the phantom experiment indicate that the new method (error: 0.53%) is significantly more accurate as compared to both binary distance transform based (error 2.11%) and conventional binary (error 3.71%) methods. Also, the results of the clinical study indicate that the new FDT-based method (kappa coefficient = 87.9%) is highly in agreement with the expert's assessments and, in this respect, outperforms the other two methods (kappa coefficients = 75.2% and 69.5%).     

Superposition of Episodic Memories: Overdistribution and Quantum Models

Memory exhibits episodic superposition, an analog of the quantum superposition of physical states: Before a cue for a presented or unpresented item is administered on a memory test, the item has the simultaneous potential to occupy all members of a mutually exclusive set of episodic states, though it occupies only one of those states after the cue is administered. This phenomenon can be modeled with a nonadditive probability model called overdistribution (OD), which implements fuzzy‐trace theory's distinction between verbatim and gist representations. We show that it can also be modeled based on quantum probability theory. A quantum episodic memory (QEM) model is developed, which is derived from quantum probability theory but also implements the process conceptions of global matching memory models. OD and QEM have different strengths, and the current challenge is to identify contrasting empirical predictions that can be used to pit them against each other.     

Nintendo® Wii Fit based sleepiness tester detects impairment of postural steadiness due to 24 h of wakefulness

A field-usable sleepiness tester could reduce sleepiness related accidents. 15 subjects’ postural steadiness was measured with a Nintendo^® Wii Fit balance board every hour for 24 h. Body sway was quantified with complexity index, C_I, and the correlation between C_I and alertness predicted by a three-process model of sleepiness was calculated. The C_I group average was 8.9 ± 1.3 for alert and 7.9 ± 1.4 for sleep deprived subjects (p < 0.001, ρ = 0.94). The Wii Fit board detects the impairment of postural steadiness. This may allow large scale sleepiness testing outside the laboratory setting.     

A Quantum Probability Perspective on Borderline Vagueness

The term “vagueness” describes a property of natural concepts, which normally have fuzzy boundaries, admit borderline cases, and are susceptible to Zeno's sorites paradox. We will discuss the psychology of vagueness, especially experiments investigating the judgment of borderline cases and contradictions. In the theoretical part, we will propose a probabilistic model that describes the quantitative characteristics of the experimental finding and extends Alxatib's and Pelletier's ( 2011 ) theoretical analysis. The model is based on a Hopfield network for predicting truth values. Powerful as this classical perspective is, we show that it falls short of providing an adequate coverage of the relevant empirical results. In the final part, we will argue that a substantial modification of the analysis put forward by Alxatib and Pelletier and its probabilistic pendant is needed. The proposed modification replaces the standard notion of probabilities by quantum probabilities. The crucial phenomenon of borderline contradictions can be explained then as a quantum interference phenomenon.     

模糊评价法分析护士对中心药房药品配送模式的满意度

目的:了解护士对中心药房药品配送模式的满意度,提高中心药房为临床配送药品的服务水平。方法:随机向149名病房护士发放调查问卷,采用模糊评价法确定因素集、评价集和权重集,构建评判矩阵,对收集的有效问卷就配送模式中3个一级指标(药师服务、配送情况、临床影响)、10个二级指标的满意度进行测评,并对测评结果进行分析。结果与结论:护士对上述3个方面的评价和整体评价均为优秀(评分均达到93分,满分100分),主要不满意表现在对病房药品科学管理水平方面;建议中心药房应进一步加强统筹管理、拓宽服务项目、提升专业服务水平等。模糊评价法可将因素定量化并从多个因素进行综合性评价,将其运用于满意度评价较为合理。