Cargando…
Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images
The third trimester of pregnancy is the most critical period for human brain development, during which significant changes occur in the morphology of the brain. The development of sulci and gyri allows for a considerable increase in the brain surface. In preterm newborns, these changes occur in an e...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10381479/ https://www.ncbi.nlm.nih.gov/pubmed/37504822 http://dx.doi.org/10.3390/jimaging9070145 |
_version_ | 1785080454387335168 |
---|---|
author | Rabanaque, David Regalado, Maria Benítez, Raul Rabanaque, Sonia Agut, Thais Carreras, Nuria Mata, Christian |
author_facet | Rabanaque, David Regalado, Maria Benítez, Raul Rabanaque, Sonia Agut, Thais Carreras, Nuria Mata, Christian |
author_sort | Rabanaque, David |
collection | PubMed |
description | The third trimester of pregnancy is the most critical period for human brain development, during which significant changes occur in the morphology of the brain. The development of sulci and gyri allows for a considerable increase in the brain surface. In preterm newborns, these changes occur in an extrauterine environment that may cause a disruption of the normal brain maturation process. We hypothesize that a normalized atlas of brain maturation with cerebral ultrasound images from birth to term equivalent age will help clinicians assess these changes. This work proposes a semi-automatic Graphical User Interface (GUI) platform for segmenting the main cerebral sulci in the clinical setting from ultrasound images. This platform has been obtained from images of a cerebral ultrasound neonatal database images provided by two clinical researchers from the Hospital Sant Joan de Déu in Barcelona, Spain. The primary objective is to provide a user-friendly design platform for clinicians for running and visualizing an atlas of images validated by medical experts. This GUI offers different segmentation approaches and pre-processing tools and is user-friendly and designed for running, visualizing images, and segmenting the principal sulci. The presented results are discussed in detail in this paper, providing an exhaustive analysis of the proposed approach’s effectiveness. |
format | Online Article Text |
id | pubmed-10381479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103814792023-07-29 Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images Rabanaque, David Regalado, Maria Benítez, Raul Rabanaque, Sonia Agut, Thais Carreras, Nuria Mata, Christian J Imaging Article The third trimester of pregnancy is the most critical period for human brain development, during which significant changes occur in the morphology of the brain. The development of sulci and gyri allows for a considerable increase in the brain surface. In preterm newborns, these changes occur in an extrauterine environment that may cause a disruption of the normal brain maturation process. We hypothesize that a normalized atlas of brain maturation with cerebral ultrasound images from birth to term equivalent age will help clinicians assess these changes. This work proposes a semi-automatic Graphical User Interface (GUI) platform for segmenting the main cerebral sulci in the clinical setting from ultrasound images. This platform has been obtained from images of a cerebral ultrasound neonatal database images provided by two clinical researchers from the Hospital Sant Joan de Déu in Barcelona, Spain. The primary objective is to provide a user-friendly design platform for clinicians for running and visualizing an atlas of images validated by medical experts. This GUI offers different segmentation approaches and pre-processing tools and is user-friendly and designed for running, visualizing images, and segmenting the principal sulci. The presented results are discussed in detail in this paper, providing an exhaustive analysis of the proposed approach’s effectiveness. MDPI 2023-07-18 /pmc/articles/PMC10381479/ /pubmed/37504822 http://dx.doi.org/10.3390/jimaging9070145 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rabanaque, David Regalado, Maria Benítez, Raul Rabanaque, Sonia Agut, Thais Carreras, Nuria Mata, Christian Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title | Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title_full | Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title_fullStr | Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title_full_unstemmed | Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title_short | Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images |
title_sort | semi-automatic gui platform to characterize brain development in preterm children using ultrasound images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10381479/ https://www.ncbi.nlm.nih.gov/pubmed/37504822 http://dx.doi.org/10.3390/jimaging9070145 |
work_keys_str_mv | AT rabanaquedavid semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT regaladomaria semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT benitezraul semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT rabanaquesonia semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT agutthais semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT carrerasnuria semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages AT matachristian semiautomaticguiplatformtocharacterizebraindevelopmentinpretermchildrenusingultrasoundimages |