Evidence map›Paper›PMID 37504822›Full record

ArticleJournal of imaging2023

Semi-Automatic GUI Platform to Characterize Brain Development in Preterm Children Using Ultrasound Images.

David Rabanaque, Maria Regalado, Raul Benítez, Sonia Rabanaque, Thais Agut, Nuria Carreras, Christian Mata

Abstract read
In one paragraph

Article in Journal of imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

David RabanaqueBarcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.ORCID 0009-0005-6271-9517
Maria RegaladoBarcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.ORCID 0009-0003-8742-3486
Raul BenítezBarcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.ORCID 0000-0002-8782-9406
Sonia RabanaqueBarcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.ORCID 0009-0002-3354-7398
Thais AgutInstitut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain.ORCID 0000-0002-5673-0016
Nuria CarrerasInstitut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu Barcelona, 08950 Esplugues de Llobregat, Spain.ORCID 0000-0002-8770-2755
Christian MataBarcelona East School of Engineering, Universitat Politècnica de Catalunya, 08019 Barcelona, Spain.ORCID 0000-0003-4768-5062

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

brain segmentationcerebral ultrasounddockerGUI semi-automatic platformpretermsulci

Identifiers

PMID37504822
PMCPMC10381479

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.