Multidimensional medical data visualization methods based on generalized graphic images

Olga Grigor evna Berestneva, Vitaly Alekseevich Volovodenko, Olga Mikhaylovna Gerget, Konstantin Sharopin, Irina Anatol evna Osadchaya

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

The work devoted to the problem of analysis and interpretation of multi-dimensional medical data based on the generalized graphic images. The existing methods and approaches, including those proposed by the authors were considered. The main problem of data visualization is the problem of obtaining a visual image that is uniquely relevant to the data set. The authors propose an approach that allows to perform visualization of the major linear structures: segment, polyline, simplex in multidimensional spaces. Presentation of multivariate observations in a two-dimensional image (the curve) ensures that to the close by the values observation will correspond visually similar image-curves; for very different by the values observations its image-curves will be noticeably different. The results of applying this approach to the problems of practical medicine were proposed: analysis of the pregnant women physiological state dynamics, identifying hidden patterns in the structure of the physiological parameters for patients with various forms of asthma.

Original languageEnglish
Pages (from-to)18-23
Number of pages6
JournalWorld Applied Sciences Journal
Volume24
Issue number24
DOIs
Publication statusPublished - 1 Jan 2013

Fingerprint

Data visualization
Medicine
Visualization

Keywords

  • Cognitive graphics
  • Generalized graphic images
  • Multi-dimensional medical data
  • Visualization techniques

ASJC Scopus subject areas

  • General

Cite this

Multidimensional medical data visualization methods based on generalized graphic images. / Berestneva, Olga Grigor evna; Volovodenko, Vitaly Alekseevich; Gerget, Olga Mikhaylovna; Sharopin, Konstantin; Osadchaya, Irina Anatol evna.

In: World Applied Sciences Journal, Vol. 24, No. 24, 01.01.2013, p. 18-23.

Research output: Contribution to journalArticle

Berestneva, Olga Grigor evna ; Volovodenko, Vitaly Alekseevich ; Gerget, Olga Mikhaylovna ; Sharopin, Konstantin ; Osadchaya, Irina Anatol evna. / Multidimensional medical data visualization methods based on generalized graphic images. In: World Applied Sciences Journal. 2013 ; Vol. 24, No. 24. pp. 18-23.
@article{8c809c8c33fb44ebbf899c3e078a61a8,
title = "Multidimensional medical data visualization methods based on generalized graphic images",
abstract = "The work devoted to the problem of analysis and interpretation of multi-dimensional medical data based on the generalized graphic images. The existing methods and approaches, including those proposed by the authors were considered. The main problem of data visualization is the problem of obtaining a visual image that is uniquely relevant to the data set. The authors propose an approach that allows to perform visualization of the major linear structures: segment, polyline, simplex in multidimensional spaces. Presentation of multivariate observations in a two-dimensional image (the curve) ensures that to the close by the values observation will correspond visually similar image-curves; for very different by the values observations its image-curves will be noticeably different. The results of applying this approach to the problems of practical medicine were proposed: analysis of the pregnant women physiological state dynamics, identifying hidden patterns in the structure of the physiological parameters for patients with various forms of asthma.",
keywords = "Cognitive graphics, Generalized graphic images, Multi-dimensional medical data, Visualization techniques",
author = "Berestneva, {Olga Grigor evna} and Volovodenko, {Vitaly Alekseevich} and Gerget, {Olga Mikhaylovna} and Konstantin Sharopin and Osadchaya, {Irina Anatol evna}",
year = "2013",
month = "1",
day = "1",
doi = "10.5829/idosi.wasj.2013.24.itmies.80004",
language = "English",
volume = "24",
pages = "18--23",
journal = "World Applied Sciences Journal",
issn = "1818-4952",
publisher = "International Digital Organization for Scientific Information",
number = "24",

}

TY - JOUR

T1 - Multidimensional medical data visualization methods based on generalized graphic images

AU - Berestneva, Olga Grigor evna

AU - Volovodenko, Vitaly Alekseevich

AU - Gerget, Olga Mikhaylovna

AU - Sharopin, Konstantin

AU - Osadchaya, Irina Anatol evna

PY - 2013/1/1

Y1 - 2013/1/1

N2 - The work devoted to the problem of analysis and interpretation of multi-dimensional medical data based on the generalized graphic images. The existing methods and approaches, including those proposed by the authors were considered. The main problem of data visualization is the problem of obtaining a visual image that is uniquely relevant to the data set. The authors propose an approach that allows to perform visualization of the major linear structures: segment, polyline, simplex in multidimensional spaces. Presentation of multivariate observations in a two-dimensional image (the curve) ensures that to the close by the values observation will correspond visually similar image-curves; for very different by the values observations its image-curves will be noticeably different. The results of applying this approach to the problems of practical medicine were proposed: analysis of the pregnant women physiological state dynamics, identifying hidden patterns in the structure of the physiological parameters for patients with various forms of asthma.

AB - The work devoted to the problem of analysis and interpretation of multi-dimensional medical data based on the generalized graphic images. The existing methods and approaches, including those proposed by the authors were considered. The main problem of data visualization is the problem of obtaining a visual image that is uniquely relevant to the data set. The authors propose an approach that allows to perform visualization of the major linear structures: segment, polyline, simplex in multidimensional spaces. Presentation of multivariate observations in a two-dimensional image (the curve) ensures that to the close by the values observation will correspond visually similar image-curves; for very different by the values observations its image-curves will be noticeably different. The results of applying this approach to the problems of practical medicine were proposed: analysis of the pregnant women physiological state dynamics, identifying hidden patterns in the structure of the physiological parameters for patients with various forms of asthma.

KW - Cognitive graphics

KW - Generalized graphic images

KW - Multi-dimensional medical data

KW - Visualization techniques

UR - http://www.scopus.com/inward/record.url?scp=84887635998&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887635998&partnerID=8YFLogxK

U2 - 10.5829/idosi.wasj.2013.24.itmies.80004

DO - 10.5829/idosi.wasj.2013.24.itmies.80004

M3 - Article

VL - 24

SP - 18

EP - 23

JO - World Applied Sciences Journal

JF - World Applied Sciences Journal

SN - 1818-4952

IS - 24

ER -