Cargando…

Parameter set for computer-assisted texture analysis of fetal brain

BACKGROUND: Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images....

Descripción completa

Detalles Bibliográficos
Autores principales: Gentillon, Hugues, Stefańczyk, Ludomir, Strzelecki, Michał, Respondek-Liberska, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124296/
https://www.ncbi.nlm.nih.gov/pubmed/27887658
http://dx.doi.org/10.1186/s13104-016-2300-3
_version_ 1782469838943289344
author Gentillon, Hugues
Stefańczyk, Ludomir
Strzelecki, Michał
Respondek-Liberska, Maria
author_facet Gentillon, Hugues
Stefańczyk, Ludomir
Strzelecki, Michał
Respondek-Liberska, Maria
author_sort Gentillon, Hugues
collection PubMed
description BACKGROUND: Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images. We proposed a wavelet-based parameter and two novel histogram-based parameters for Fisher texture analysis in three-dimensional space. RESULTS: Wavenhl, focus index, and dispersion index revealed better quality for 3 T. Though both 1.5 and 3 T images were 16-bit DICOM encoded, nearly 16 and 12 usable bits were measured in 3 and 1.5 T images, respectively. The four-bit padding observed in 1.5 T K-space encoding mimics noise by adding illusionistic details, which are not really part of the image. In contrast, zero-bit padding in 3 T provides space for storing more details and increases the likelihood of noise but as well as edges, which in turn are very crucial for differentiation of closely related anatomical structures. CONCLUSIONS: Both encoding modes are possible with both units, but higher 3 T resolution is the main difference. It contributes to higher perceived and available dynamic range. Apart from surprisingly larger Fisher coefficient, no significant difference was observed when testing was conducted with down-converted 8-bit BMP images. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-016-2300-3) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5124296
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-51242962016-12-08 Parameter set for computer-assisted texture analysis of fetal brain Gentillon, Hugues Stefańczyk, Ludomir Strzelecki, Michał Respondek-Liberska, Maria BMC Res Notes Research Article BACKGROUND: Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images. We proposed a wavelet-based parameter and two novel histogram-based parameters for Fisher texture analysis in three-dimensional space. RESULTS: Wavenhl, focus index, and dispersion index revealed better quality for 3 T. Though both 1.5 and 3 T images were 16-bit DICOM encoded, nearly 16 and 12 usable bits were measured in 3 and 1.5 T images, respectively. The four-bit padding observed in 1.5 T K-space encoding mimics noise by adding illusionistic details, which are not really part of the image. In contrast, zero-bit padding in 3 T provides space for storing more details and increases the likelihood of noise but as well as edges, which in turn are very crucial for differentiation of closely related anatomical structures. CONCLUSIONS: Both encoding modes are possible with both units, but higher 3 T resolution is the main difference. It contributes to higher perceived and available dynamic range. Apart from surprisingly larger Fisher coefficient, no significant difference was observed when testing was conducted with down-converted 8-bit BMP images. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-016-2300-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-25 /pmc/articles/PMC5124296/ /pubmed/27887658 http://dx.doi.org/10.1186/s13104-016-2300-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Gentillon, Hugues
Stefańczyk, Ludomir
Strzelecki, Michał
Respondek-Liberska, Maria
Parameter set for computer-assisted texture analysis of fetal brain
title Parameter set for computer-assisted texture analysis of fetal brain
title_full Parameter set for computer-assisted texture analysis of fetal brain
title_fullStr Parameter set for computer-assisted texture analysis of fetal brain
title_full_unstemmed Parameter set for computer-assisted texture analysis of fetal brain
title_short Parameter set for computer-assisted texture analysis of fetal brain
title_sort parameter set for computer-assisted texture analysis of fetal brain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124296/
https://www.ncbi.nlm.nih.gov/pubmed/27887658
http://dx.doi.org/10.1186/s13104-016-2300-3
work_keys_str_mv AT gentillonhugues parametersetforcomputerassistedtextureanalysisoffetalbrain
AT stefanczykludomir parametersetforcomputerassistedtextureanalysisoffetalbrain
AT strzeleckimichał parametersetforcomputerassistedtextureanalysisoffetalbrain
AT respondekliberskamaria parametersetforcomputerassistedtextureanalysisoffetalbrain