biomedicalsignalprocessingandmodelingcomplexityof...

Hindawi Publishing CorporationComputational and Mathematical Methods in MedicineVolume 2012, Article ID 298634, 2 pagesdoi:10.1155/2012/298634

Editorial

Biomedical Signal Processing and Modeling Complexity ofLiving Systems

Carlo Cattani,1 Radu Badea,2 Shengyong Chen,3 and Maria Crisan4

1 Department of Mathematics, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy2 Department of Clinical Imaging Ultrasound, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania3 College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China4 Department of Histology, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania

Correspondence should be addressed to Carlo Cattani, [email protected]

Received 22 November 2012; Accepted 22 November 2012

Copyright © 2012 Carlo Cattani et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Living systems are often maintained by information flowsand, as such, they present interesting mathematical problemsfor example, in the modeling and analysis of spatial struc-tures, self-organization, environmental interaction, behav-ior, and development. Biomedical signals extract informa-tion from the complex phenomena being measured, whichare typically a time series having both a regular and randomcomponents. Solutions attempt to map general principles,which are used to model how the living systems work. Manyresearchers have been studying these problems because oftheir interesting mathematical features and because of theirscientific importance. The focus of this special issue is themathematical analysis and modeling of time series in livingsystems and biomedical signals. It is mostly interested inthe related new development of both theoretical study andpractical implementation, either with modeling, complexity,statistics, or signal transformation in living systems.

The papers selected for this special issue represent a goodpanel in recent challenges. The topics of the research papersand review papers are connected with the living systemsand biomedical signals, including modeling dynamical com-plexity in living systems, for example, network dynamics,mass action, dynamical systems theory, methods for analysisand characterization of dynamical complexity, biomedicalsignal analysis such as mathematical pattern analysis ofbiological signals, generative mechanisms of biological signalpatterning, implementation of signal analysis algorithms,linking biological structure to biological signal generation,and intracellular signal processing, as well as related modelsand applications, such as systems theory, biological organi-zation, and biomedical information processing.

This special issue contains 31 papers. In the category ofmodeling dynamical complexity, L. Sena et al. present a fuzzymodel to interpret data of drive performances from patientswith sleep deprivation. S. Chen et al. review the modeling ofbiological intelligence for supply chain management systemoptimization (MPE/769702). M. Li presents approximatingideal filters by systems of fractional order. L. T. Ko et al.present nested quantization index modulation for reversiblewatermarking and its application to healthcare informationmanagement systems. C. Cattani studies on the existenceof wavelet symmetries in Archaea DNA. A. Ciancio and C.Cattani present separable transition density in the hybridmodel for tumor-immune competition. Q. Guan et al.present solid dynamic models for analysis of stress and strainin human hearts. G. Xiong et al. present theorems andapplication of local activity of CNN with five state variablesand one port. L. Fanea et al. present theoretical compartmentmodeling of DCE-MRI data based on the transport acrossphysiological barriers in the brain. M. Crisan et al. present amulticriteria optimization model for the study of the efficacyof skin antiaging therapy.

In the category of methods for analysis of dynamicalcomplexity, L. Xu et al. present high resolution remotelysensed small target detection by imitating fly visual per-ception mechanism. J. Zhang et al. present target contourrecovering for tracking people in complex environments. M.Li and W. Zhao present a report on CPNs for asymptoticidentity in min-plus algebra. M. Xu and C. Wei presentremotely sensed image classification by complex networkeigenvalue and connected-degree. J. Wen et al. present abatch rival penalized expectation-maximization algorithm

2 Computational and Mathematical Methods in Medicine

for Gaussian mixture clustering with automatic modelselection. M. Strbac and D. Popovic show a software tool forthe prosthetic foot modeling and stiffness optimization. T.Carletti and A. Filisetti present the stochastic evolution of aprotocell: the Gillespie algorithm in a dynamically varyingvolume.

In the category of biomedical signal analysis, S. Chenand X. Li review the annual progress of functional magneticresonance imaging for imaging neural activity in the humanbrain. H. C. Hsin et al. present an adaptive coding passscanning algorithm for optimal rate control in biomedicalimages. I. Chiorean et al. present a medicoeconomic indexfor photo-induced skin cancers. C. Vicas et al. present theinfluence of expert dependent variability over the perfor-mance of noninvasive fibrosis assessment at patients withchronic hepatitis C, by the means of texture analysis. G.Nut et al. present a finite element method applied to aproblem of blood flow in vessels. S. Chen et al. summarizerecent advances in morphological cell image analysis. C.Yao et al. present motion analysis of live objects by super-resolution fluorescence microscopy. H. Castillejos et al.present wavelet transform fuzzy algorithms for dermoscopicimage segmentation. D. A. Mitrea et al. present abdominaltumor characterization and recognition using superior ordercooccurrence matrices, based on ultrasound images. Q. Guanet al. present a method for modeling and representationof human hearts for volumetric measurement. X. Li et al.present characteristics of evoked potential multiple EEGrecordings in patients with chronic pain by means of parallelfactor analysis. A. I. Mitrea et al. present iterative methodsfor obtaining energy-minimizing parametric snakes, withapplication to medical imaging. K. Lu et al. present nonlocalmeans based denoising for medical images. K. T. Q. Dang etal. present detecting epileptic seizure from scalp EEG usingLyapunov spectrum.

Of 67 submissions, 31 papers are selected in this specialissue. Of course, the topics and papers are not an exhaustiverepresentation of the area of biomedical signal processingand modeling complexity of living systems. It can beseen that although some solutions and models becomeavailable, most problems remain open and research is highlyactive in this field. In the near future, we expect morecontributions that will address all of the key aspects raisedabove. Nonetheless, the special issue represents the recentconcerns in the community and we have the pleasure ofsharing them with the readers.

Acknowledgments

We would like to thank the authors for their excellentcontributions and the reviewers for their help in improvingofthe papers.

Carlo CattaniRadu Badea

Shengyong ChenMaria Crisan

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