Box-counting Method in Quantitative Analysis of Images of the Brain

Nebojsa Milosevic; Antionio Ieva; Herbert Jelinek; Nemanja Rajkovic

doi:10.1109/CSCS.2017.53

Box-counting Method in Quantitative Analysis of Images of the Brain

Nebojsa Milosevic, Antionio Ieva, Herbert Jelinek, Nemanja Rajkovic

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

-The introduction of fractal geometry in the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, particularly fractal analysis provides a quantitative tool for the study of morphology of brain cells and the brain structure itself. The box-counting method of fractal analysis, its modification are presented on 2D image of neurons from the monkey brain. The use of MATLAB software, particularly when the 2D or 3D image of the brain have to be quantified with boxcounting procedure is also presented. This paper offers a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences with the clinical applications.

Original language	English
Title of host publication	Proceedings of the 2017 21st International Conference on Control Systems and Computer Science
Place of Publication	USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	343-349
Number of pages	7
ISBN (Electronic)	2379-0482
DOIs	https://doi.org/10.1109/CSCS.2017.53
Publication status	Published - 2017
Event	The 21st International Conference on Control Systems and Computer Science: CSCS21 - University Politehnica of Bucharest, Bucharest, Romania Duration: 29 May 2017 → 31 May 2017 http://cscs21.hpc.pub.ro/

Conference

Conference	The 21st International Conference on Control Systems and Computer Science
Country	Romania
City	Bucharest
Period	29/05/17 → 31/05/17
Internet address	http://cscs21.hpc.pub.ro/

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title = "Box-counting Method in Quantitative Analysis of Images of the Brain",

abstract = "-The introduction of fractal geometry in the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, particularly fractal analysis provides a quantitative tool for the study of morphology of brain cells and the brain structure itself. The box-counting method of fractal analysis, its modification are presented on 2D image of neurons from the monkey brain. The use of MATLAB software, particularly when the 2D or 3D image of the brain have to be quantified with boxcounting procedure is also presented. This paper offers a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences with the clinical applications. ",

author = "Nebojsa Milosevic and Antionio Ieva and Herbert Jelinek and Nemanja Rajkovic",

year = "2017",

doi = "10.1109/CSCS.2017.53",

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booktitle = "Proceedings of the 2017 21st International Conference on Control Systems and Computer Science",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "The 21st International Conference on Control Systems and Computer Science : CSCS21 ; Conference date: 29-05-2017 Through 31-05-2017",

url = "http://cscs21.hpc.pub.ro/",

}

Milosevic, N, Ieva, A, Jelinek, H & Rajkovic, N 2017, Box-counting Method in Quantitative Analysis of Images of the Brain. in Proceedings of the 2017 21st International Conference on Control Systems and Computer Science. IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 343-349, The 21st International Conference on Control Systems and Computer Science, Bucharest, Romania, 29/05/17. https://doi.org/10.1109/CSCS.2017.53

Box-counting Method in Quantitative Analysis of Images of the Brain. / Milosevic, Nebojsa; Ieva, Antionio; Jelinek, Herbert; Rajkovic, Nemanja.

Proceedings of the 2017 21st International Conference on Control Systems and Computer Science. USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 343-349.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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N2 - -The introduction of fractal geometry in the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, particularly fractal analysis provides a quantitative tool for the study of morphology of brain cells and the brain structure itself. The box-counting method of fractal analysis, its modification are presented on 2D image of neurons from the monkey brain. The use of MATLAB software, particularly when the 2D or 3D image of the brain have to be quantified with boxcounting procedure is also presented. This paper offers a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences with the clinical applications.

AB - -The introduction of fractal geometry in the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, particularly fractal analysis provides a quantitative tool for the study of morphology of brain cells and the brain structure itself. The box-counting method of fractal analysis, its modification are presented on 2D image of neurons from the monkey brain. The use of MATLAB software, particularly when the 2D or 3D image of the brain have to be quantified with boxcounting procedure is also presented. This paper offers a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences with the clinical applications.

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