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Image Processing, Pattern Recognition, and Semantic Understanding Techniques

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Natural User Interfaces in Medical Image Analysis

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

The lengthy first chapter reviews selected methods of initial image analysis, major classification techniques including a list of holistic and syntactic methods, and introduces to techniques of semantic image analysis. This chapter also contains several source codes of example implementations of selected image processing methods. Subsequent paragraphs will discuss in order the three most important groups of methods and algorithms used by modern image analysis systems in more detail. These groups of methods are as follows:

  • Image processing—groups techniques of image preprocessing, which usually allow the quality of the analyzed images to be improved or certain significant objects of interest for further analysis to be extracted from the entire complex image (e.g., during its classification).

  • Pattern classification—a group of methods which allow certain significant features of the entire image or its selected elements to be identified and used for classification, by indexing them as objects which are members of certain previously defined classes.

  • Image understanding—analysis methods aimed at determining the meaning of a given image by analyzing its semantics. Such techniques are very advanced and can be used only for images which contain meaning, e.g., various medical images.

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References

  1. Hachaj T, Ogiela MR (2012) Semantic description and recognition of human body poses and movement sequences with gesture description language. Commun Comput Inf Sci 353:1–8

    Article  Google Scholar 

  2. Hachaj T, Ogiela MR (2013) Computer karate trainer in tasks of personal and homeland security defense. Lect Notes Comput Sci 8128:430–441

    Article  Google Scholar 

  3. Hachaj T, Ogiela MR, Piekarczyk M (2013) Dependence of Kinect sensors number and position on gestures recognition with gesture description language semantic classifier. In: Ganzha M, Maciaszek L, Paprzycki M (eds) Proceedings of the 2013 federated conference on computer science and information systems (FedCSIS 2013), IEEE Catalog Number CFP1385 N-ART, IEEE Computer Society Press, Kraków, Poland, pp. 571–575. ISBN 978-1-4673-4471-5, 8–11 Sept 2013

    Google Scholar 

  4. Hachaj T, Ogiela MR, Piekarczyk M (2014) Real-time recognition of selected karate techniques using GDL approach. Adv Intell Syst Comput 233:99–106. doi:10.1007/978-3-319-01622-1_12

    Article  Google Scholar 

  5. Hachaj T, Ogiela MR (2014) Rule-based approach to recognizing human body poses and gestures in real time. Multimedia Syst 20:81–99. doi:10.1007/s00530-013-0332-2

    Article  Google Scholar 

  6. Bankman I (2009) Handbook of medical image processing and analysis. Elsevier, Burlington

    Google Scholar 

  7. Najarian K, Splinter R (2012) Biomedical signal and image processing. CRC Press, Boca Raton

    Google Scholar 

  8. Pavlidis T (2012) Algorithms for graphics and image processing. Springer, Berlin Heidelberg

    Google Scholar 

  9. Pratt WK (2014) Introduction to digital image processing. CRC Press, Boca Raton

    Google Scholar 

  10. Theis FJ, Meyer-Bäse A (2010) Biomedical signal analysis: contemporary methods and applications. The MIT Press, Cambridge

    Google Scholar 

  11. Bodzioch S, Ogiela MR (2009) New approach to gallbladder ultrasonic images analysis and lesions recognition. Comput Med Imaging Graph 33:154–170

    Google Scholar 

  12. Duda RO, Hart PE, Stork DG (2001) Pattern classifications. Wiley, New York

    Google Scholar 

  13. Suetens P (2009) Fundamentals of medical imaging. Cambridge University Press, New York

    Book  Google Scholar 

  14. Theodoridis S, Koutroumbas K (2009) Pattern recognition. Academic Press, Burlington

    Google Scholar 

  15. Davis LS (2001) Foundations of image understanding. Springer, New York

    Book  MATH  Google Scholar 

  16. Ogiela L (2008) Cognitive systems for medical pattern understanding and diagnosis. Lect Notes Artif Intell 5177:394–400

    Google Scholar 

  17. Ogiela L (2008) Syntactic approach to cognitive interpretation of medical patterns. Lect Notes Artif Intell 5314:456–462

    Google Scholar 

  18. Ogiela L (2009) UBIAS systems for the cognitive interpretation and analysis of medical images. Opto-Electron Rev 17(2):166–179

    Article  Google Scholar 

  19. Ogiela L (2010) Cognitive informatics in automatic pattern understanding and cognitive information systems. Studies in computational intelligence, Vol 323. Springer, Berlin, pp 209–226

    Google Scholar 

  20. Ogiela MR, Bodzioch S (2011) Computer analysis of gallbladder ultrasonic images towards recognition of pathological lesions. Opto-Electron Rev 19(2):155–168

    Article  Google Scholar 

  21. Ogiela L, Ogiela MR (2009) Cognitive techniques in visual data interpretation. Studies in computational intelligence 228, Springer, Berlin

    Google Scholar 

  22. Ogiela L, Ogiela MR (2012) Advances in cognitive information systems. Cognitive systems monographs 17. Springer, Berlin

    Google Scholar 

  23. Hachaj T (2012) Pattern classification methods for analysis and visualization of brain perfusion CT maps. Comput Intell Paradigms Adv Pattern Classif 386:145–170

    Article  Google Scholar 

  24. Hachaj T, Ogiela MR (2010) Automatic detection and lesion description in cerebral blood flow and cerebral blood volume perfusion maps. J Signal Process Syst Signal Image Video Technol 61(3):317–328. doi:10.1007/s11265-010-0454-0

    Article  Google Scholar 

  25. Hachaj T, Ogiela MR (2010) Augmented reality interface for visualization of volumetric medical data. Adv Intell Soft Comput 84:271–277 (Springer, Berlin Heidelberg)

    Google Scholar 

  26. Hachaj T, Ogiela MR (2011) Intelligent information system for interpretation of dynamic perfusion brain maps. Lect Notes Artif Intell 6591:406–415

    Google Scholar 

  27. Hachaj T, Ogiela MR (2011) CAD system for automatic analysis of CT perfusion maps. Opto-Electron Rev 19(1):95–103. doi:10.2478/s11772-010-0071-2

    Article  Google Scholar 

  28. Hachaj T, Ogiela MR (2011) A system for detecting and describing pathological changes using dynamic perfusion computer tomography brain maps. Comput Biol Med 41(6):402–410. doi:10.1016/j.compbiomed.2011.04.002

    Article  Google Scholar 

  29. Chomsky N (1988) Language and problems of knowledge, the Managua lectures. MIT Press, Cambridge

    Google Scholar 

  30. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423, 623–656

    Google Scholar 

  31. Hachaj T, Ogiela MR (2013) Application of neural networks in detection of abnormal brain perfusion regions. Neurocomputing 122:33–42. doi:10.1016/j.neucom.2013.04.030

    Article  Google Scholar 

  32. Albus JS, Meystel AM (2001) Engineering of mind: an introduction to the science of intelligent systems. Wiley, New York

    Google Scholar 

  33. Branquinho J (ed) (2001) The foundations of cognitive science. Clarendon, Oxford

    Google Scholar 

  34. Cohen H, Lefebvre C (eds) (2005) Handbook of categorization in cognitive science. Elsevier, The Netherlands

    Google Scholar 

  35. Ogiela MR, Ogiela U (2014) Secure information management using linguistic threshold approach. Advanced Information and Knowledge Processing. Springer, London

    Google Scholar 

  36. Hachaj T, Ogiela MR (2013) Real time area-based stereo matching algorithm for multimedia video devices. Opto-Electron Rev 21(4):367–375. doi:10.2478/s11772-013-0107-5

    Article  Google Scholar 

  37. Hachaj T (2014) Real time exploration and management of large medical volumetric datasets on small mobile devices—evaluation of remote volume rendering approach. Int J Inf Manage 34:336–343. doi:10.1016/j.ijinfomgt.2013.11.005

    Article  Google Scholar 

  38. Hachaj T, Ogiela MR (2011) Augmented reality approaches in intelligent health technologies and brain lesion detection. Lect Notes Comput Sci 6908:135–148

    Article  Google Scholar 

  39. Hachaj T, Ogiela MR (2012) Visualization of perfusion abnormalities with GPU-based volume rendering. Comput Graph UK 36(3):163–169. doi:10.1016/j.cag.2012.01.002

    Article  Google Scholar 

  40. Hachaj T, Ogiela MR (2012) Framework for cognitive analysis of dynamic perfusion computed tomography with visualization of large volumetric data. J Electron Imaging 21(4):Article Number 043017. doi: 10.1117/1.JEI.21.4.043017

  41. Hachaj T, Ogiela MR (2012) Segmentation and visualization of tubular structures in computed tomography angiography. Lect Notes in Artif Intell 7198:495–503

    Google Scholar 

  42. Hachaj T, Ogiela MR (2012) Evaluation of carotid artery segmentation with centerline detection and active contours without edges algorithm. Lect Notes Comput Sci 7465:469–479

    Google Scholar 

  43. Ogiela MR, Hachaj T (2012) The automatic two-step vessel lumen segmentation algorithm for carotid bifurcation analysis during perfusion examination. In: Watada J, Watanabe T, PhillipsWren G (eds) Intelligent decision technologies (IDT’2012), vol 2, smart innovation systems and technologies, vol 16, pp 485–493

    Google Scholar 

  44. Ogiela MR, Hachaj T (2013) Automatic segmentation of the carotid artery bifurcation region with a region-growing approach. J Electron Imaging 22(3):Article Number 033029. doi: 10.1117/1.JEI.22.3.033029

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Correspondence to Marek R. Ogiela .

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Ogiela, M.R., Hachaj, T. (2015). Image Processing, Pattern Recognition, and Semantic Understanding Techniques. In: Natural User Interfaces in Medical Image Analysis. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-07800-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-07800-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07799-4

  • Online ISBN: 978-3-319-07800-7

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