Information Technology in Medical Diagnostics

 
 
CRC Press
  • erschienen am 20. Juli 2017
  • |
  • 220 Seiten
 
E-Book | PDF mit Adobe-DRM | Systemvoraussetzungen
978-1-351-57895-0 (ISBN)
 

For many centuries, people have tried to learn about the state of their health. Initially, in the pre-technological period, they had to rely only on their senses. Then there were simple tools to help the human senses. The discovery of X-rays, which allowed people to look "inside" the body, turned out to be a major breakthrough. Contemporary medical diagnostics is increasingly being assisted by information technology that allows, for example, thorough image tissue analysis or pathology differentiation. They also allow very early preventive diagnostics. Influenced by information technology, "classic" diagnostic techniques change and new ones arise.

Information Technology in Medical Diagnostics presents selected and extended conference papers from Polish, Ukrainian and Kazakh scientists. They address problems of the application of new methods of image processing for analysis of medical images, new methods of classification of medical data as well as new medical imaging methods. Some of the presented technologies are inspired by the functioning of living organisms.

Information Technology in Medical Diagnostics is of interest not only to academics and engineers, but also to professionals involved in biomedical engineering, and seeking for solutions for issues that cannot be solved with the help of "traditional" technologies.

  • Englisch
  • London
  • |
  • Großbritannien
Taylor & Francis Ltd
  • Für höhere Schule und Studium
  • 38,76 MB
978-1-351-57895-0 (9781351578950)
weitere Ausgaben werden ermittelt

Waldemar Wójcik was born in Poland, 1949. He is Director of the Institute of Electronics and Information Technology, former longtime dean of the Faculty of Electrical Engineering and Computer Science at Lublin University of Technology. Doctor Honoris Causa of five universities in Ukraine and Kazakhstan. He obtained his Ph.D. in 1985 at the Lublin University of Technology, and D.Sc. in 2002 at the National University Lviv Polytechnic, Ukraine. In 2009 he obtained a title of professor granted by the President of Poland. In his research he mainly deals with process control, optoelectronics, digital data analysis and also heat processes or solid state physics. Particular attention is paid to the use optoelectronic technology in the monitoring and diagnostics of thermal processes. He is a member of Optoelectronics Section of the Committee of Electronics and Telecommunications of the Polish Academy of Sciences; Metrology Section of the committee of Metrology and Scientific Equipment of the Polish Academy of Sciences and many other scientific organisations of Poland as well as Europe and Asia. In total, he has published 53 books, over 400 papers, and authored several patents. He is also a member of the editorial board of numerous international and national scientific and technical journals.

Andrzej Smolarz (Ph.D., D.Sc. Eng.) graduated from Lublin University of Technology Faculty of Electrical Engineering. During 28 years of professional work he has reached the position of associated professor at his Alma Mater in the Institute of Electronics and Information Technology. He has also worked as a research Fellow at The Laboratory of Research in Fluid Dynamics and Combustion Technologies (LIFTEC by its Spanish acronym) a joint center between the Spanish Scientific Research Council (CSIC) and University of Zaragoza. His research field of interest covers wide variety of optical methods in industrial diagnostics and control as well as applications of artificial intelligence methods in industrial diagnostics. Author of more than 100 publications in this research area.

1 Recognition of textured objects using optimal inverse resonant filtration
1.1 Introduction
1.2 Object recognition problem statement as the problem of optimal filtration
1.3 Harmonic model of textured image
1.4 Design of optimal inverse resonant filter
1.5 Creation of functions basis for eigen harmonic decomposition
1.6 Implementation and experimental analysis of the IRF
1.7 Conclusions

2 Approximation of bidirectional reflectance distribution function for highly efficient shading
2.1 Introduction
2.2 Analysis of existing approaches to BRDF approximation and problem formulation
2.3 Approximation of BRDF by the 3-degree polynomial
2.4 Approximation of BRDF by using logarithmic function
2.5 BRDF approximation models based on new cosine-degree functions with simple hardware implementation
2.6 A method for accelerated computation of color intensities for scan-line fills of three-dimensional graphics objects
2.7 Conclusions

3 Modified method of parallel-hierarchical network teaching based on population coding
3.1 Introduction
3.2 The G-transformation
3.3 Information about the frame parameters
3.4 Estimation of efficiency
3.5 Experiment
3.6 Conclusions

4 Methods and systems of 2D polarization multi-matrix tomography of birefringent biological tissues and fluids
4.1 Introduction
4.2 Materials and methods of 2D polarization Mueller-matrix tomography
4.3 Metrological characteristics of measurement errors distributions in the system of Mueller-matrix mapping of biological layers
4.4 Diagnostic possibilities of orientation and phase Mueller-matrix tomography of polycrystal networks of blood plasma
4.5 Conclusions

5 Subpixel edge detection and localisation based on low-frequency filtering
5.1 Introduction
5.2 Methods
5.3 Experiment
5.4 Methods for edge detection based on low-frequency filtering and analysis of previous research
5.5 Diagram of the edge detection method
5.6 Conclusions

6 Magnetocardiographic technology for human heart investigation
6.1 Introduction
6.2 Technology of magnetocardiographic study
6.3 Principles and stages of magnetocardiosignal analysis
6.4 Automatic analysis of the MCG
6.5 Conclusions

7 Processing laser beam images using parallel-hierarchical FPGA-based transformations
7.1 Introduction
7.2 Theoretical foundations of organising parallel-hierarchical networks on the basis of functional sets
7.3 Direct parallel-hierarchical transformation
7.4 Implementation of parallel-hierarchical networks for processing laser beam spot images
7.5 Results
7.6 Conclusions

8 The conjugated null space method of blind deconvolution
8.1 Introduction
8.2 The conjugated NS method of PSF estimation
8.3 Deconvolution optimisation
8.4 Method implementation and test examples
8.5 Conclusion

9 Biologically motivated approach to multistage image processing
9.1 Introduction
9.2 Methods
9.3 Results
9.4 Discussion and conclusion

10 Combined models of artificial immune systems
10.1 Artificial immune systems
10.2 Hybridisation of artificial immune systems
10.3 Canonical algorithms of artificial immune systems
10.4 The combined model of negative and clonal selection
10.5 Combined immune network and negative selection model for solving of anomaly detection problems
10.6 Using hybrid negative selection algorithm with artificial immune networks for industrial diagnostics
10.7 Conclusions

Dewey Decimal Classfication (DDC)

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