Four-dimensional deformable image registration using trajectory modeling

Edward Castillo, Richard Castillo, Josue Martinez, Maithili Shenoy, Thomas Guerrero

Research output: Contribution to journalArticlepeer-review

218 Scopus citations

Abstract

A four-dimensional deformable image registration (4D DIR) algorithm, referred to as 4D local trajectory modeling (4DLTM), is presented and applied to thoracic 4D computed tomography (4DCT) image sets. The theoretical framework on which this algorithm is built exploits the incremental continuity present in 4DCT component images to calculate a dense set of parameterized voxel trajectories through space as functions of time. The spatial accuracy of the 4DLTM algorithm is compared with an alternative registration approach in which component phase to phase (CPP) DIR is utilized to determine the full displacement between maximum inhale and exhale images. A publically available DIR reference database (http://www.dir-lab.com) is utilized for the spatial accuracy assessment. The database consists of ten 4DCT image sets and corresponding manually identified landmark points between the maximum phases. A subset of points are propagated through the expiratory 4DCT component images. Cubic polynomials were found to provide sufficient flexibility and spatial accuracy for describing the point trajectories through the expiratory phases. The resulting average spatial error between the maximum phases was 1.25 mm for the 4DLTM and 1.44 mm for the CPP. The 4DLTM method captures the long-range motion between 4DCT extremes with high spatial accuracy.

Original languageEnglish (US)
Pages (from-to)305-327
Number of pages23
JournalPhysics in Medicine and Biology
Volume55
Issue number1
DOIs
StatePublished - Jan 7 2010
Externally publishedYes

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'Four-dimensional deformable image registration using trajectory modeling'. Together they form a unique fingerprint.

Cite this