Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images

Bowen Zhao; Gary E. Christensen; Joo Hyun Song; Yue Pan; Sarah E. Gerard; Joseph M. Reinhardt; Kaifang Du; Taylor Patton; John M. Bayouth; Geoffrey D. Hugo

doi:10.1109/CVPRW.2016.67

Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images

Bowen Zhao, Gary E. Christensen, Joo Hyun Song, Yue Pan, Sarah E. Gerard, Joseph M. Reinhardt, Kaifang Du, Taylor Patton, John M. Bayouth, Geoffrey D. Hugo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

We propose a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by the variations of fraction of tissue within voxels throughout the respiratory cycle. The proposed 4D SSTVD registration scheme considers the entire dynamic 4D data set simultaneously, using both spatial and temporal information. We employed a uniform 4D cubic B-spline parametrization of the transform and a temporally extended linear elasticity regularization of deformation field to ensure temporal smoothness and thus biological plausibility of estimated deformation. We used a multiresolution multi-grid registration framework with limitedmemory Broyden Fletcher Goldfarb Shanno (L-BFGS) optimization procedure for rapid convergence and limited memory consumption. We conducted experiments using synthetic 2D+t images and clinical 4DCT pulmonary data sets and evaluated accuracy and temporal smoothness of the proposed method via manually annotated landmarks.

Original language	English
Title of host publication	Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
Publisher	IEEE Computer Society
Pages	481-489
Number of pages	9
ISBN (Electronic)	9781467388504
DOIs	https://doi.org/10.1109/CVPRW.2016.67
State	Published - Dec 16 2016
Event	29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 - Las Vegas, United States Duration: Jun 26 2016 → Jul 1 2016

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016
Country/Territory	United States
City	Las Vegas
Period	06/26/16 → 07/1/16

Keywords

4D image registration
Groupwise image registration
Mass preservation
Radiation therapy
Sum of squared tissue volume difference
Temporal smoothness
Treatment planning

Access to Document

10.1109/CVPRW.2016.67

Cite this

Zhao, B., Christensen, G. E., Song, J. H., Pan, Y., Gerard, S. E., Reinhardt, J. M., Du, K., Patton, T., Bayouth, J. M., & Hugo, G. D. (2016). Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 (pp. 481-489). Article 7789557 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2016.67

Zhao, Bowen ; Christensen, Gary E. ; Song, Joo Hyun et al. / Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images. Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society, 2016. pp. 481-489 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

@inproceedings{9af80266d7f747b09a90ba64d2e74989,

title = "Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images",

abstract = "We propose a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by the variations of fraction of tissue within voxels throughout the respiratory cycle. The proposed 4D SSTVD registration scheme considers the entire dynamic 4D data set simultaneously, using both spatial and temporal information. We employed a uniform 4D cubic B-spline parametrization of the transform and a temporally extended linear elasticity regularization of deformation field to ensure temporal smoothness and thus biological plausibility of estimated deformation. We used a multiresolution multi-grid registration framework with limitedmemory Broyden Fletcher Goldfarb Shanno (L-BFGS) optimization procedure for rapid convergence and limited memory consumption. We conducted experiments using synthetic 2D+t images and clinical 4DCT pulmonary data sets and evaluated accuracy and temporal smoothness of the proposed method via manually annotated landmarks.",

keywords = "4D image registration, Groupwise image registration, Mass preservation, Radiation therapy, Sum of squared tissue volume difference, Temporal smoothness, Treatment planning",

author = "Bowen Zhao and Christensen, {Gary E.} and Song, {Joo Hyun} and Yue Pan and Gerard, {Sarah E.} and Reinhardt, {Joseph M.} and Kaifang Du and Taylor Patton and Bayouth, {John M.} and Hugo, {Geoffrey D.}",

note = "Funding Information: This work is supported in part by National Cancer Institute of the National Institute of Health (NIH) under award numbers R01CA166703 and R01CA166119. Publisher Copyright: {\textcopyright} 2016 IEEE.; 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016 ; Conference date: 26-06-2016 Through 01-07-2016",

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doi = "10.1109/CVPRW.2016.67",

language = "English",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

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Zhao, B, Christensen, GE, Song, JH, Pan, Y, Gerard, SE, Reinhardt, JM, Du, K, Patton, T, Bayouth, JM & Hugo, GD 2016, Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images. in Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016., 7789557, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, IEEE Computer Society, pp. 481-489, 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016, Las Vegas, United States, 06/26/16. https://doi.org/10.1109/CVPRW.2016.67

Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images. / Zhao, Bowen; Christensen, Gary E.; Song, Joo Hyun et al.
Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society, 2016. p. 481-489 7789557 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images

AU - Zhao, Bowen

AU - Christensen, Gary E.

AU - Song, Joo Hyun

AU - Pan, Yue

AU - Gerard, Sarah E.

AU - Reinhardt, Joseph M.

AU - Du, Kaifang

AU - Patton, Taylor

AU - Bayouth, John M.

AU - Hugo, Geoffrey D.

N1 - Funding Information: This work is supported in part by National Cancer Institute of the National Institute of Health (NIH) under award numbers R01CA166703 and R01CA166119. Publisher Copyright: © 2016 IEEE.

PY - 2016/12/16

Y1 - 2016/12/16

N2 - We propose a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by the variations of fraction of tissue within voxels throughout the respiratory cycle. The proposed 4D SSTVD registration scheme considers the entire dynamic 4D data set simultaneously, using both spatial and temporal information. We employed a uniform 4D cubic B-spline parametrization of the transform and a temporally extended linear elasticity regularization of deformation field to ensure temporal smoothness and thus biological plausibility of estimated deformation. We used a multiresolution multi-grid registration framework with limitedmemory Broyden Fletcher Goldfarb Shanno (L-BFGS) optimization procedure for rapid convergence and limited memory consumption. We conducted experiments using synthetic 2D+t images and clinical 4DCT pulmonary data sets and evaluated accuracy and temporal smoothness of the proposed method via manually annotated landmarks.

AB - We propose a 4D (three spatial dimensions plus time) tissue-volume preserving non-rigid image registration algorithm for pulmonary 4D computed tomography (4DCT) data sets to provide relevant information for radiation therapy and estimate pulmonary ventilation. The sum of squared tissue volume difference (SSTVD) similarity cost takes into account the CT intensity changes of spatially corresponding voxels, which is caused by the variations of fraction of tissue within voxels throughout the respiratory cycle. The proposed 4D SSTVD registration scheme considers the entire dynamic 4D data set simultaneously, using both spatial and temporal information. We employed a uniform 4D cubic B-spline parametrization of the transform and a temporally extended linear elasticity regularization of deformation field to ensure temporal smoothness and thus biological plausibility of estimated deformation. We used a multiresolution multi-grid registration framework with limitedmemory Broyden Fletcher Goldfarb Shanno (L-BFGS) optimization procedure for rapid convergence and limited memory consumption. We conducted experiments using synthetic 2D+t images and clinical 4DCT pulmonary data sets and evaluated accuracy and temporal smoothness of the proposed method via manually annotated landmarks.

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KW - Groupwise image registration

KW - Mass preservation

KW - Radiation therapy

KW - Sum of squared tissue volume difference

KW - Temporal smoothness

KW - Treatment planning

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DO - 10.1109/CVPRW.2016.67

M3 - Conference contribution

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BT - Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016

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Zhao B, Christensen GE, Song JH, Pan Y, Gerard SE, Reinhardt JM et al. Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2016. IEEE Computer Society. 2016. p. 481-489. 7789557. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW.2016.67

Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images

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Keywords

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