Four-dimensional deformable image registration using trajectory modeling

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

Research output: Contribution to journalArticle

135 Citations (Scopus)

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
Pages (from-to)305-327
Number of pages23
JournalPhysics in Medicine and Biology
Volume55
Issue number1
DOIs
Publication statusPublished - 07-01-2010
Externally publishedYes

Fingerprint

Four-Dimensional Computed Tomography
Databases
Articular Range of Motion
Thorax

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

Cite this

Castillo, E., Castillo, R., Martinez, J., Shenoy, M., & Guerrero, T. (2010). Four-dimensional deformable image registration using trajectory modeling. Physics in Medicine and Biology, 55(1), 305-327. https://doi.org/10.1088/0031-9155/55/1/018
Castillo, Edward ; Castillo, Richard ; Martinez, Josue ; Shenoy, Maithili ; Guerrero, Thomas. / Four-dimensional deformable image registration using trajectory modeling. In: Physics in Medicine and Biology. 2010 ; Vol. 55, No. 1. pp. 305-327.
@article{e6a803db26d045849d343b18899a6f71,
title = "Four-dimensional deformable image registration using trajectory modeling",
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.",
author = "Edward Castillo and Richard Castillo and Josue Martinez and Maithili Shenoy and Thomas Guerrero",
year = "2010",
month = "1",
day = "7",
doi = "10.1088/0031-9155/55/1/018",
language = "English",
volume = "55",
pages = "305--327",
journal = "Physics in Medicine and Biology",
issn = "0031-9155",
publisher = "IOP Publishing Ltd.",
number = "1",

}

Castillo, E, Castillo, R, Martinez, J, Shenoy, M & Guerrero, T 2010, 'Four-dimensional deformable image registration using trajectory modeling', Physics in Medicine and Biology, vol. 55, no. 1, pp. 305-327. https://doi.org/10.1088/0031-9155/55/1/018

Four-dimensional deformable image registration using trajectory modeling. / Castillo, Edward; Castillo, Richard; Martinez, Josue; Shenoy, Maithili; Guerrero, Thomas.

In: Physics in Medicine and Biology, Vol. 55, No. 1, 07.01.2010, p. 305-327.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Four-dimensional deformable image registration using trajectory modeling

AU - Castillo, Edward

AU - Castillo, Richard

AU - Martinez, Josue

AU - Shenoy, Maithili

AU - Guerrero, Thomas

PY - 2010/1/7

Y1 - 2010/1/7

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=77649213379&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77649213379&partnerID=8YFLogxK

U2 - 10.1088/0031-9155/55/1/018

DO - 10.1088/0031-9155/55/1/018

M3 - Article

VL - 55

SP - 305

EP - 327

JO - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

IS - 1

ER -