Box-counting method in quantitative analysis of images of the brain

Nebojsa T. Milosevic; Antionio Di Ieva; Herbert Jelinek; Nemanja Rajkovic

doi:10.1109/CSCS.2017.53

Box-counting method in quantitative analysis of images of the brain

Nebojsa T. Milosevic, Antionio Di Ieva, Herbert Jelinek, Nemanja Rajkovic

Faculty of Medicine, Health and Human Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

2 Citations (Scopus)

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 box-counting 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	2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings
Editors	Dumitrache, AM Florea, F Pop, A Dumitrascu
Place of Publication	Piscataway, NJ, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	343-349
Number of pages	7
ISBN (Electronic)	9781538618394
ISBN (Print)	9781538618400
DOIs	https://doi.org/10.1109/CSCS.2017.53
Publication status	Published - 5 Jul 2017
Event	21st International Conference on Control Systems and Computer Science, CSCS 2017 - Bucharest Duration: 29 May 2017 → 31 May 2017

Conference

Conference	21st International Conference on Control Systems and Computer Science, CSCS 2017
City	Bucharest
Period	29/05/17 → 31/05/17

Keywords

Box-counting
Brain
Computation
Fractal
MATLAB
Modelling
Neuroanatomy

Access to Document

10.1109/CSCS.2017.53

Cite this

Milosevic, N. T., Di Ieva, A., Jelinek, H., & Rajkovic, N. (2017). Box-counting method in quantitative analysis of images of the brain. In Dumitrache, AM. Florea, F. Pop, & A. Dumitrascu (Eds.), 2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings (pp. 343-349). [7968581] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CSCS.2017.53

Milosevic, Nebojsa T. ; Di Ieva, Antionio ; Jelinek, Herbert ; Rajkovic, Nemanja. / Box-counting method in quantitative analysis of images of the brain. 2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings. editor / Dumitrache ; AM Florea ; F Pop ; A Dumitrascu. Piscataway, NJ, USA : Institute of Electrical and Electronics Engineers (IEEE), 2017. pp. 343-349

@inproceedings{c72bfb1c716b4d7394209ad8a7fa3346,

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 box-counting 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.",

keywords = "Box-counting, Brain, Computation, Fractal, MATLAB, Modelling, Neuroanatomy",

author = "Milosevic, {Nebojsa T.} and {Di Ieva}, Antionio and Herbert Jelinek and Nemanja Rajkovic",

year = "2017",

month = jul,

day = "5",

doi = "10.1109/CSCS.2017.53",

language = "English",

isbn = "9781538618400",

pages = "343--349",

editor = "Dumitrache and AM Florea and F Pop and A Dumitrascu",

booktitle = "2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings",

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

address = "United States",

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

}

Milosevic, NT, Di Ieva, A, Jelinek, H & Rajkovic, N 2017, Box-counting method in quantitative analysis of images of the brain. in Dumitrache, AM Florea, F Pop & A Dumitrascu (eds), 2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings., 7968581, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, pp. 343-349, 21st International Conference on Control Systems and Computer Science, CSCS 2017, Bucharest, 29/05/17. https://doi.org/10.1109/CSCS.2017.53

Box-counting method in quantitative analysis of images of the brain. / Milosevic, Nebojsa T.; Di Ieva, Antionio; Jelinek, Herbert; Rajkovic, Nemanja.

2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings. ed. / Dumitrache; AM Florea; F Pop; A Dumitrascu. Piscataway, NJ, USA : Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 343-349 7968581.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Box-counting method in quantitative analysis of images of the brain

AU - Milosevic, Nebojsa T.

AU - Di Ieva, Antionio

AU - Jelinek, Herbert

AU - Rajkovic, Nemanja

PY - 2017/7/5

Y1 - 2017/7/5

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 box-counting 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 box-counting 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.

KW - Box-counting

KW - Brain

KW - Computation

KW - Fractal

KW - MATLAB

KW - Modelling

KW - Neuroanatomy

UR - http://www.scopus.com/inward/record.url?scp=85027496082&partnerID=8YFLogxK

U2 - 10.1109/CSCS.2017.53

DO - 10.1109/CSCS.2017.53

M3 - Conference proceeding contribution

AN - SCOPUS:85027496082

SN - 9781538618400

SP - 343

EP - 349

BT - 2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings

A2 - Dumitrache, null

A2 - Florea, AM

A2 - Pop, F

A2 - Dumitrascu, A

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ, USA

T2 - 21st International Conference on Control Systems and Computer Science, CSCS 2017

Y2 - 29 May 2017 through 31 May 2017

ER -

Milosevic NT, Di Ieva A, Jelinek H, Rajkovic N. Box-counting method in quantitative analysis of images of the brain. In Dumitrache, Florea AM, Pop F, Dumitrascu A, editors, 2017 21st International Conference on Control Systems and Computer Science (CSCS) : proceedings. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE). 2017. p. 343-349. 7968581 https://doi.org/10.1109/CSCS.2017.53

Box-counting method in quantitative analysis of images of the brain

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this