Avançar para navegação principal Avançar para pesquisar Avançar para conteúdo principal

Semi-automatic tool to identify heterogeneity zones in lge-cmr and incorporate the result into a 3d model of the left ventricle

  • Maria Narciso*
  • , António Ferreira
  • , Pedro Vieira
  • *Autor correspondente para este trabalho

Resultado de pesquisarevisão de pares

Resumo

Fatal scar-related arrhythmias are caused by an abnormal electrical wave propagation around non conductive scarred tissue and through viable channels of reduced conductivity. Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the gold-standard procedure used to differentiate the scarred tissue from the healthy, highlighting the dead cells. The border regions responsible for creating the feeble channels are visible as gray zones. Identifying and monitoring (as they may evolve) these areas may predict the risk of arrhythmias that may lead to cardiac arrest. The main goal of this project is the development of a system able to aid the user in the extraction of geometrical and physiological information from LGE images and the replication of myocardial heterogeneities onto a three-dimensional (3D) structure, built by the methods described by our team in another publication, able to undergo electro-physiologic simulations. The system components were developed in MATLAB R2019b the first is a semi-automatic tool, to identify and segment the myocardial scars and gray zones in every two-dimensional (2D) slice of a LGE CMR dataset. The second component takes these results and assembles different sections while setting different conductivity values for each. At this point, the resulting parts are incorporated into the functional 3D model of the left ventricle, and therefore the chosen values and regions can be validated and redefined until a satisfactory result is obtained. As preliminary results we present the first steps of building one functional Left ventricle (LV) model with scarred zones.

Idioma originalEnglish
Título da publicação do anfitriãoImage analysis and recognition
Subtítulo da publicação do anfitrião17th International Conference, ICIAR 2020, Póvoa de Varzim, Portugal, June 24–26, 2020, proceedings, part II
EditoresAurélio Campilho, Fakhri Karray, Zhou Wang
EditoraSpringer
Páginas238-246
Número de páginas9
Edição1
ISBN (eletrónico)9783030505165
ISBN (impresso)9783030505158
DOIs
Estado da publicaçãoPublicado - 2020
Publicado externamenteSim
Evento17th International Conference on Image Analysis and Recognition, ICIAR 2020 - Póvoa de Varzim
Duração: 24 jun. 202026 jun. 2020

Série de publicação

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12132 LNCS
ISSN (impresso)0302-9743
ISSN (eletrónico)1611-3349

Conferência

Conferência17th International Conference on Image Analysis and Recognition, ICIAR 2020
País/TerritórioPortugal
CidadePóvoa de Varzim
Período24/06/2026/06/20

Impressão digital

Mergulhe nos tópicos de investigação de “Semi-automatic tool to identify heterogeneity zones in lge-cmr and incorporate the result into a 3d model of the left ventricle“. Em conjunto formam uma impressão digital única.

Citação