Image segmentation and registration algorithm to collect thoracic skeleton semilandmarks for characterization of age and sex-based thoracic morphology variation

Ashley A. Weaver, Callistus M. Nguyen, Samantha L. Schoell, Joseph A Maldjian, Joel D. Stitzel

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Thoracic anthropometry variations with age and sex have been reported and likely relate to thoracic injury risk and outcome. The objective of this study was to collect a large volume of homologous semilandmark data from the thoracic skeleton for the purpose of quantifying thoracic morphology variations for males and females of ages 0-100 years. A semi-automated image segmentation and registration algorithm was applied to collect homologous thoracic skeleton semilandmarks from 343 normal computed tomography (CT) scans. Rigid, affine, and symmetric diffeomorphic transformations were used to register semilandmarks from an atlas to homologous locations in the subject-specific coordinate system. Homologous semilandmarks were successfully collected from 92% (7077) of the ribs and 100% (187) of the sternums included in the study. Between 2700 and 11,000 semilandmarks were collected from each rib and sternum and over 55 million total semilandmarks were collected from all subjects. The extensive landmark data collected more fully characterizes thoracic skeleton morphology across ages and sexes. Characterization of thoracic morphology with age and sex may help explain variations in thoracic injury risk and has important implications for vulnerable populations such as pediatrics and the elderly.

Original languageEnglish (US)
Pages (from-to)41-48
Number of pages8
JournalComputers in Biology and Medicine
Volume67
DOIs
StatePublished - Dec 1 2015

Keywords

  • Anthropometry
  • Computed tomography
  • Medical imaging
  • Morphology
  • Registration
  • Ribs
  • Segmentation
  • Sternum

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications

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