Interactive segmentation with curve-based template deformation for spatiotemporal computed tomography of swallowing motion.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 25 03 2024
accepted: 09 08 2024
medline: 22 10 2024
pubmed: 21 10 2024
entrez: 21 10 2024
Statut: epublish

Résumé

Repeating X-ray computed tomography (CT) measurements over a short period of time allows for obtaining a spatiotemporal four-dimensional (4D) volume image. This study presents an interactive method for segmenting a 4DCT image by fitting a template model to a target organ. The template consists of a three-dimensional (3D) mesh model and free-form-deformation (FFD) cage enclosing the mesh. The user deforms the template by placing multiple curve constraints that specify the boundary shape of the template in 3D space. We also present curve constraints shared over all time frames and interpolated along the time axis to facilitate efficient curve specification. Our method formulates the template deformation using the FFD cage modification, allowing the user to switch between our curve-based method and traditional FFD at any time. To illustrate the feasibility of our method, we show segmentation results in which we could accurately segment three organs from a 4DCT image capturing a swallowing motion. To evaluate the usability of our method, we conducted a user study comparing our curve-based method with the cage-based FFD. We found that the participants finished segmentation in approximately 20% interaction time periods on average with our method.

Identifiants

pubmed: 39432481
doi: 10.1371/journal.pone.0309379
pii: PONE-D-24-09547
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0309379

Informations de copyright

Copyright: © 2024 Kimura et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

NO authors have competing interests.

Auteurs

Yuki Kimura (Y)

Shibaura Institute of Technology, Koto-ku, Japan.

Takashi Ijiri (T)

Shibaura Institute of Technology, Koto-ku, Japan.

Yoko Inamoto (Y)

Fujita Health University, Toyoake-shi, Japan.

Takuya Hashimoto (T)

Tokyo University of Science, Katsushika-ku, Japan.

Yukihiro Michiwaki (Y)

Toho University, Ota-ku, Japan.

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