International Journal of Applied Mathematics and Computer Sciences最新文献

Recognition of atherosclerotic plaques and their extended dimensioning with computerized tomography angiography imaging 动脉粥样硬化斑块的识别及其计算机断层血管成像的扩展尺寸

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0003

T. Markiewicz, M. Dziekiewicz, M. Maruszynski, R. Boguslawska-Walecka, W. Kozlowski

{"title":"Recognition of atherosclerotic plaques and their extended dimensioning with computerized tomography angiography imaging","authors":"T. Markiewicz, M. Dziekiewicz, M. Maruszynski, R. Boguslawska-Walecka, W. Kozlowski","doi":"10.2478/amcs-2014-0003","DOIUrl":"https://doi.org/10.2478/amcs-2014-0003","url":null,"abstract":"Abstract In this paper the authors raise the issue of automatic discrimination of atherosclerotic plaques within an artery lumen based on numerical and statistical thresholding of Computerized Tomography Angiographic (CTA) images and their advanced dimensioning as a support for preoperative vessel assessment. For the study, a set of tomograms of the aorta, as well as the ilio-femoral and femoral arteries were examined. In each case a sequence of about 130-480 images of the artery cutoff planes were analyzed prior to their segmentation based on morphological image transformation. A crucial step in the staging of atherosclerotic alteration is recognition of the plaque in the CTA image. To solve this problem, statistical and linear fitting methods, including the least-squares approximation by polynomial and spline polynomial functions, as well as the error fitting function were used. Also, new descriptors of atherosclerotic changes, such as the lumen decrease factor, the circumference occupancy factor, and the convex plaque area factor, are proposed as a means of facilitating preoperative vessel examination. Finally, ways to reduce the computational time are discussed. The proposed methods can be very useful for automatic quantification of atherosclerotic changes visualized by CTA imaging.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122762684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

An optimal sliding mode congestion controller for connection-oriented communication networks with lossy links 具有有损链路的面向连接的通信网络的最优滑模拥塞控制器

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0007

A. Bartoszewicz, P. Leśniewski

引用次数: 9

On attaining the prescribed quality of a controlled fourth order system 关于获得受控四阶系统的规定质量

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0006

V. Kapustyan, V. Maksimov

引用次数: 3

Approximation of a linear dynamic process model using the frequency approach and a non-quadratic measure of the model error 用频率方法逼近线性动态过程模型和模型误差的非二次测度

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0008

K. Janiszowski

引用次数: 4

Survival analysis on data streams: Analyzing temporal events in dynamically changing environments 数据流的生存分析:在动态变化的环境中分析时间事件

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0015

Ammar Shaker, E. Hüllermeier

引用次数: 8

Center-based l1–clustering method 基于中心的l1聚类方法

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0012

K. Sabo

引用次数: 15

A differential evolution approach to dimensionality reduction for classification needs 基于分类需求的降维差分进化方法

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0009

G. Martinović, Drazen Bajer, Bruno Zoric

{"title":"A differential evolution approach to dimensionality reduction for classification needs","authors":"G. Martinović, Drazen Bajer, Bruno Zoric","doi":"10.2478/amcs-2014-0009","DOIUrl":"https://doi.org/10.2478/amcs-2014-0009","url":null,"abstract":"Abstract The feature selection problem often occurs in pattern recognition and, more specifically, classification. Although these patterns could contain a large number of features, some of them could prove to be irrelevant, redundant or even detrimental to classification accuracy. Thus, it is important to remove these kinds of features, which in turn leads to problem dimensionality reduction and could eventually improve the classification accuracy. In this paper an approach to dimensionality reduction based on differential evolution which represents a wrapper and explores the solution space is presented. The solutions, subsets of the whole feature set, are evaluated using the k-nearest neighbour algorithm. High quality solutions found during execution of the differential evolution fill the archive. A final solution is obtained by conducting k-fold crossvalidation on the archive solutions and selecting the best one. Experimental analysis is conducted on several standard test sets. The classification accuracy of the k-nearest neighbour algorithm using the full feature set and the accuracy of the same algorithm using only the subset provided by the proposed approach and some other optimization algorithms which were used as wrappers are compared. The analysis shows that the proposed approach successfully determines good feature subsets which may increase the classification accuracy.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133637419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 28

Nuclei segmentation for computer-aided diagnosis of breast cancer 计算机辅助诊断乳腺癌的细胞核分割

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0002

Marek Kowal, P. Filipczuk

{"title":"Nuclei segmentation for computer-aided diagnosis of breast cancer","authors":"Marek Kowal, P. Filipczuk","doi":"10.2478/amcs-2014-0002","DOIUrl":"https://doi.org/10.2478/amcs-2014-0002","url":null,"abstract":"Abstract Breast cancer is the most common cancer among women. The effectiveness of treatment depends on early detection of the disease. Computer-aided diagnosis plays an increasingly important role in this field. Particularly, digital pathology has recently become of interest to a growing number of scientists. This work reports on advances in computer-aided breast cancer diagnosis based on the analysis of cytological images of fine needle biopsies. The task at hand is to classify those as either benign or malignant. We propose a robust segmentation procedure giving satisfactory nuclei separation even when they are densely clustered in the image. Firstly, we determine centers of the nuclei using conditional erosion. The erosion is performed on a binary mask obtained with the use of adaptive thresholding in grayscale and clustering in a color space. Then, we use the multi-label fast marching algorithm initialized with the centers to obtain the final segmentation. A set of 84 features extracted from the nuclei is used in the classification by three different classifiers. The approach was tested on 450 microscopic images of fine needle biopsies obtained from patients of the Regional Hospital in Zielona Góra, Poland. The classification accuracy presented in this paper reaches 100%, which shows that a medical decision support system based on our method would provide accurate diagnostic information.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116062311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 40

An analytical iterative statistical algorithm for image reconstruction from projections 投影图像重建的解析迭代统计算法

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0001

R. Cierniak

引用次数: 15

Approximation of phenol concentration using novel hybrid computational intelligence methods 用新型混合计算智能方法逼近苯酚浓度

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2014-03-01 DOI: 10.2478/amcs-2014-0013

Pawel Plawiak, R. Tadeusiewicz

引用次数: 41