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

PLoS One. 2024 Oct 21;19(10):e0309379. doi: 10.1371/journal.pone.0309379. eCollection 2024.

Abstract

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.

MeSH terms

  • Algorithms
  • Deglutition* / physiology
  • Four-Dimensional Computed Tomography* / methods
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Imaging, Three-Dimensional / methods
  • Tomography, X-Ray Computed / methods

Grants and funding

This work was funded by Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research B (22H03945). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.