Computing thickness of irregularly-shaped thin walls using a locally semi-implicit scheme with extrapolation to solve the Laplace equation: Application to the right ventricle.

Cardiac magnetic resonance Ghost node methods Laplace equation Right ventricle Wall thickness

Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
13 Dec 2023
Historique:
received: 28 07 2023
revised: 30 11 2023
accepted: 11 12 2023
medline: 19 12 2023
pubmed: 19 12 2023
entrez: 19 12 2023
Statut: aheadofprint

Résumé

Cardiac Magnetic Resonance (CMR) Imaging is currently considered the gold standard imaging modality in cardiology. However, it is accompanied by a tradeoff between spatial resolution and acquisition time. Providing accurate measures of thin walls relative to the image resolution may prove challenging. One such anatomical structure is the cardiac right ventricle. Methods for measuring thickness of wall-like anatomical structures often rely on the Laplace equation to provide point-to-point correspondences between both boundaries. This work presents limex, a novel method to solve the Laplace equation using ghost nodes and providing extrapolated values, which is tested on three different datasets: a mathematical phantom, a set of biventricular segmentations from CMR images of ten pigs and the database used at the RV Segmentation Challenge held at MICCAI'12. Thickness measurements using the proposed methodology are more accurate than state-of-the-art methods, especially with the coarsest image resolutions, yielding mean L

Identifiants

pubmed: 38113681
pii: S0010-4825(23)01320-3
doi: 10.1016/j.compbiomed.2023.107855
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

107855

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Susana Merino-Caviedes (S)

Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: smercav@lpi.tel.uva.es.

Marcos Martín-Fernández (M)

Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: marcma@tel.uva.es.

María Teresa Pérez Rodríguez (MT)

Escuela de Ingenierías Industriales, Universidad de Valladolid, Valladolid, Spain. Electronic address: terper@wmatem.eis.uva.es.

Miguel Ángel Martín-Fernández (MÁ)

Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: migmar@tel.uva.es.

David Filgueiras-Rama (D)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program, Madrid, Spain. Electronic address: david.filgueiras@cnic.es.

Federico Simmross-Wattenberg (F)

Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: fedsim@tel.uva.es.

Carlos Alberola-López (C)

Laboratorio de Procesado de Imagen, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain. Electronic address: caralb@tel.uva.es.

Classifications MeSH