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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...

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Autores principales: Rabanaque, David, Regalado, Maria, Benítez, Raul, Rabanaque, Sonia, Agut, Thais, Carreras, Nuria, Mata, Christian
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
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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.
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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
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