Patient specific dynamic geometric models from sequential volumetric time series image data

B. M. Cameron, R. A. Robb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Generating patient specific dynamic models is complicated by the complexity of the motion intrinsic and extrinsic to the anatomic structures being modeled. Using a physics-based sequentially deforming algorithm, an anatomically accurate dynamic four-dimensional model can be created from a sequence of 3-D volumetric time series data sets [1]. While such algorithms may accurately track the cyclic non-linear motion of the heart, they generally fail to accurately track extrinsic structural and non-cyclic motion. To accurately model these motions, we have modified a physics-based deformation algorithm to use a meta-surface defining the temporal and spatial maxima of the anatomic structure as the base reference surface. A mass-spring physics-based deformable model, which can expand or shrink with the local intrinsic motion, is applied to the metasurface, deforming this base reference surface to the volumetric data at each time point. As the meta-surface encompasses the temporal maxima of the structure, any extrinsic motion is inherently encoded into the base reference surface and allows the computation of the time point surfaces to be performed in parallel. The resultant 4-D model can be interactively transformed and viewed from different angles, showing the spatial and temporal motion of the anatomic structure. Using texture maps and per-vertex coloring, additional data such as physiological and/or biomechanical variables (e.g., mapping electrical activation sequences onto contracting myocardial surfaces) can be associated with the dynamic model, producing a 5-D model. For acquisition systems that may capture only limited time series data (e.g., only images at end-diastole/end- systole or inhalation/exhalation), this algorithm can provide useful interpolated surfaces between the time points. Such models help minimize the number of time points required to usefully depict the motion of anatomic structures for quantitative assessment of regional dynamics.

Original languageEnglish (US)
Title of host publicationMedicine Meets Virtual Reality 12 - Building a Better You
Subtitle of host publicationThe Next Tools for Medical Education, Diagnosis and Care
PublisherIOS Press
Pages40-45
Number of pages6
ISBN (Print)1586034049, 9781586034047
DOIs
StatePublished - Jan 1 2004
Event4th Medicine Meets Virtual Reality Proceedings 1996, MMVR 1996 - Newport Beach, CA, United States
Duration: Jan 15 2004Jan 16 2004

Publication series

NameStudies in Health Technology and Informatics
Volume98
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other4th Medicine Meets Virtual Reality Proceedings 1996, MMVR 1996
CountryUnited States
CityNewport Beach, CA
Period1/15/041/16/04

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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    Cameron, B. M., & Robb, R. A. (2004). Patient specific dynamic geometric models from sequential volumetric time series image data. In Medicine Meets Virtual Reality 12 - Building a Better You: The Next Tools for Medical Education, Diagnosis and Care (pp. 40-45). (Studies in Health Technology and Informatics; Vol. 98). IOS Press. https://doi.org/10.3233/978-1-60750-942-4-40