Adv. Artif. Neural Syst.最新文献_第8页

Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms 用pi变换和模糊直方图测量非高斯性

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/962105

C. Plant, S. T. Mai, Junming Shao, Fabian J Theis, A. Meyer-Bäse, Christian Böhm

引用次数: 0

Unsupervised Neural Techniques Applied to MR Brain Image Segmentation 无监督神经技术在MR脑图像分割中的应用

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/457590

A. Ortiz, J. Górriz, J. Ramírez, D. Salas-González

{"title":"Unsupervised Neural Techniques Applied to MR Brain Image Segmentation","authors":"A. Ortiz, J. Górriz, J. Ramírez, D. Salas-González","doi":"10.1155/2012/457590","DOIUrl":"https://doi.org/10.1155/2012/457590","url":null,"abstract":"The primary goal of brain image segmentation is to partition a given brain image into different regions representing anatomical structures. Magnetic resonance image (MRI) segmentation is especially interesting, since accurate segmentation in white matter, grey matter and cerebrospinal fluid provides a way to identify many brain disorders such as dementia, schizophrenia or Alzheimer's disease (AD). Then, image segmentation results in a very interesting tool for neuroanatomical analyses. In this paper we show three alternatives to MR brain image segmentation algorithms, with the Self-Organizing Map (SOM) as the core of the algorithms. The procedures devised do not use any a priori knowledge about voxel class assignment, and results in fully-unsupervised methods for MRI segmentation, making it possible to automatically discover different tissue classes. Our algorithm has been tested using the images from the Internet Brain Image Repository (IBSR) outperforming existing methods, providing values for the average overlap metric of 0.7 for the white and grey matter and 0.45 for the cerebrospinal fluid. Furthermore, it also provides good results for high-resolution MR images provided by the NuclearMedicine Service of the \"Virgen de las Nieves\" Hospital (Granada, Spain).","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"69 1","pages":"457590:1-457590:7"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91192554","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: 29

Hemodialysis Key Features Mining and Patients Clustering Technologies 血液透析关键特征挖掘与患者聚类技术

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/835903

T. Lu, Chun-Ya Tseng

{"title":"Hemodialysis Key Features Mining and Patients Clustering Technologies","authors":"T. Lu, Chun-Ya Tseng","doi":"10.1155/2012/835903","DOIUrl":"https://doi.org/10.1155/2012/835903","url":null,"abstract":"The kidneys are very vital organs. Failing kidneys lose their ability to filter out waste products, resulting in kidney disease. To extend or save the lives of patients with impaired kidney function, kidney replacement is typically utilized, such as hemodialysis. This work uses an entropy function to identify key features related to hemodialysis. By identifying these key features, one can determine whether a patient requires hemodialysis. This work uses these key features as dimensions in cluster analysis. The key features can effectively determine whether a patient requires hemodialysis. The proposed data mining scheme finds association rules of each cluster. Hidden rules for causing any kidney disease can therefore be identified. The contributions and key points of this paper are as follows. (1) This paper finds some key features that can be used to predict the patient who may has high probability to perform hemodialysis. (2) The proposed scheme applies k-means clustering algorithm with the key features to category the patients. (3) A data mining technique is used to find the association rules from each cluster. (4) The mined rules can be used to determine whether a patient requires hemodialysis.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"102 1","pages":"835903:1-835903:11"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83014773","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

Modelling Biological Systems with Competitive Coherence 具有竞争一致性的生物系统建模

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/703878

V. Norris, M. Engel, M. Demarty

引用次数: 17

Combining Neural Methods and Knowledge-Based Methods in Accident Management 神经方法与知识方法在事故管理中的结合

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/534683

M. Sirola, Jaakko Talonen

{"title":"Combining Neural Methods and Knowledge-Based Methods in Accident Management","authors":"M. Sirola, Jaakko Talonen","doi":"10.1155/2012/534683","DOIUrl":"https://doi.org/10.1155/2012/534683","url":null,"abstract":"Accident management became a popular research issue in the early 1990s. Computerized decision support was studied from many points of view. Early fault detection and information visualization are important key issues in accident management also today. In this paper we make a brief review on this research history mostly from the last two decades including the severe accident management. The author's studies are reflected to the state of the art. The self-organizing map method is combined with other more or less traditional methods. Neural methods used together with knowledge-based methods constitute a methodological base for the presented decision support prototypes. Two application examples with modern decision support visualizations are introduced more in detail. A case example of detecting a pressure drift on the boiling water reactor by multivariate methods including innovative visualizations is studied in detail. Promising results in early fault detection are achieved. The operators are provided by added information value to be able to detect anomalies in an early stage already. We provide the plant staff with a methodological tool set, which can be combined in various ways depending on the special needs in each case.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"49 1","pages":"534683:1-534683:6"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73599008","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: 6

Evaluation of a Nonrigid Motion Compensation Technique Based on Spatiotemporal Features for Small Lesion Detection in Breast MRI 基于时空特征的非刚性运动补偿技术在乳腺MRI小病灶检测中的应用

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/808602

Frank Steinbrücker, A. Meyer-Bäse, T. Schlossbauer, D. Cremers

{"title":"Evaluation of a Nonrigid Motion Compensation Technique Based on Spatiotemporal Features for Small Lesion Detection in Breast MRI","authors":"Frank Steinbrücker, A. Meyer-Bäse, T. Schlossbauer, D. Cremers","doi":"10.1155/2012/808602","DOIUrl":"https://doi.org/10.1155/2012/808602","url":null,"abstract":"Motion-induced artifacts represent a major problem in detection and diagnosis of breast cancer in dynamic contrast-enhanced magnetic resonance imaging. The goal of this paper is to evaluate the performance of a new nonrigid motion correction algorithm based on the optical flow method. For each of the small lesions, we extracted morphological and dynamical features describing both global and local shape, and kinetics behavior. In this paper, we compare the performance of each extracted feature set under consideration of several 2D or 3D motion compensation parameters for the differential diagnosis of enhancing lesions in breast MRI. Based on several simulation results, we determined the optimal motion compensation parameters. Our results have shown that motion compensation can improve the classification results. The results suggest that the computerized analysis system based on the non-rigid motion compensation technique and spatiotemporal features has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"120 1","pages":"808602:1-808602:10"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79422989","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: 1

Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis 计算机辅助诊断乳腺MRI时空特征对良恶性小病变的鉴别

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/919281

Frank Steinbrücker, A. Meyer-Bäse, C. Plant, T. Schlossbauer, U. Meyer-Bäse

引用次数: 0

A Radial Basis Function Spike Model for Indirect Learning via Integrate-and-Fire Sampling and Reconstruction Techniques 基于积分-点火采样和重建技术的间接学习径向基函数尖峰模型

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/713581

Xu Zhang, Greg Foderaro, C. Henriquez, A. VanDongen, S. Ferrari

{"title":"A Radial Basis Function Spike Model for Indirect Learning via Integrate-and-Fire Sampling and Reconstruction Techniques","authors":"Xu Zhang, Greg Foderaro, C. Henriquez, A. VanDongen, S. Ferrari","doi":"10.1155/2012/713581","DOIUrl":"https://doi.org/10.1155/2012/713581","url":null,"abstract":"This paper presents a deterministic and adaptive spike model derived from radial basis functions and a leaky integrate-and-fire sampler developed for training spiking neural networks without direct weight manipulation. Several algorithms have been proposed for training spiking neural networks through biologically-plausible learning mechanisms, such as spike-timing dependent synaptic plasticity and Hebbian plasticity. These algorithms typically rely on the ability to update the synaptic strengths, or weights, directly, through a weight update rule in which the weight increment can be decided and implemented based on the training equations. However, in several potential applications of adaptive spiking neural networks, including neuroprosthetic devices and CMOS/memristor nanoscale neuromorphic chips, the weights cannot be manipulated directly and, instead, tend to change over time by virtue of the pre- and postsynaptic neural activity. This paper presents an indirect learning method that induces changes in the synaptic weights by modulating spike-timing-dependent plasticity by means of controlled input spike trains. In place of the weights, the algorithmmanipulates the input spike trains used to stimulate the input neurons by determining a sequence of spike timings that minimize a desired objective function and, indirectly, induce the desired synaptic plasticity in the network.","PeriodicalId":7288,"journal":{"name":"Adv. Artif. Neural Syst.","volume":"22 1","pages":"713581:1-713581:16"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75367330","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: 13

Hopfield Neural Networks with Unbounded Monotone Activation Functions 具有无界单调激活函数的Hopfield神经网络

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/571358

N. Tatar

引用次数: 11

Methodological Triangulation Using Neural Networks for Business Research 利用神经网络进行商业研究的方法学三角测量

Adv. Artif. Neural Syst. Pub Date : 2012-01-01 DOI: 10.1155/2012/517234

S. Walczak

引用次数: 17