Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM

Liyang Wei, Dinggang Shen, Dinesh Kumar, Ram Turlapati, Jasjit S. Suri

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

1 Citation (Scopus)

Abstract

DSA images suffer from challenges like system X-ray noise and artifacts due to patient movement. In this paper, we present a two-step strategy to improve DSA image quality. First, a hierarchical deformable registration algorithm is used to register the mask frame and the bolus frame before subtraction. Second, the resulted DSA image is further enhanced by background diffusion and nonlinear normalization for better visualization. Two major changes are made in the hierarchical deformable registration algorithm for DSA images: 1) B-Spline is used to represent the deformation field in order to produce the smooth deformation field; 2) two features are defined as the attribute vector for each point in the image, i.e., original image intensity and gradient. Also, for speeding up the 2D image registration, the hierarchical motion compensation algorithm is implemented by a multi-resolution framework. The proposed method has been evaluated on a database of 73 subjects by quantitatively measuring signal-to-noise (SNR) ratio. DSA embedded with proposed strategies demonstrates an improvement of 74.1% over conventional DSA in terms of SNR. Our system runs on Eigen's DSA workstation using C++ in Windows environment.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume6812
DOIs
Publication statusPublished - 2008 May 15
Externally publishedYes
EventImage Processing: Algorithms and Systems VI - San Jose, CA, United States
Duration: 2008 Jan 282008 Jan 29

Other

OtherImage Processing: Algorithms and Systems VI
CountryUnited States
CitySan Jose, CA
Period08/1/2808/1/29

Fingerprint

image enhancement
Motion compensation
Image enhancement
Image registration
Splines
Image quality
Masks
Signal to noise ratio
Visualization
X rays
workstations
registers
splines
subtraction
artifacts
signal to noise ratios
masks
gradients

Keywords

  • Diffusion
  • DSA
  • Hierarchical deformable registration
  • Nonlinear normalization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Wei, L., Shen, D., Kumar, D., Turlapati, R., & Suri, J. S. (2008). Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6812). [68120Z] https://doi.org/10.1117/12.765520

Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM. / Wei, Liyang; Shen, Dinggang; Kumar, Dinesh; Turlapati, Ram; Suri, Jasjit S.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6812 2008. 68120Z.

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

Wei, L, Shen, D, Kumar, D, Turlapati, R & Suri, JS 2008, Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 6812, 68120Z, Image Processing: Algorithms and Systems VI, San Jose, CA, United States, 08/1/28. https://doi.org/10.1117/12.765520
Wei L, Shen D, Kumar D, Turlapati R, Suri JS. Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6812. 2008. 68120Z https://doi.org/10.1117/12.765520
Wei, Liyang ; Shen, Dinggang ; Kumar, Dinesh ; Turlapati, Ram ; Suri, Jasjit S. / Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6812 2008.
@inproceedings{94c009dfe04e4ca399796c2f28461de9,
title = "Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM",
abstract = "DSA images suffer from challenges like system X-ray noise and artifacts due to patient movement. In this paper, we present a two-step strategy to improve DSA image quality. First, a hierarchical deformable registration algorithm is used to register the mask frame and the bolus frame before subtraction. Second, the resulted DSA image is further enhanced by background diffusion and nonlinear normalization for better visualization. Two major changes are made in the hierarchical deformable registration algorithm for DSA images: 1) B-Spline is used to represent the deformation field in order to produce the smooth deformation field; 2) two features are defined as the attribute vector for each point in the image, i.e., original image intensity and gradient. Also, for speeding up the 2D image registration, the hierarchical motion compensation algorithm is implemented by a multi-resolution framework. The proposed method has been evaluated on a database of 73 subjects by quantitatively measuring signal-to-noise (SNR) ratio. DSA embedded with proposed strategies demonstrates an improvement of 74.1{\%} over conventional DSA in terms of SNR. Our system runs on Eigen's DSA workstation using C++ in Windows environment.",
keywords = "Diffusion, DSA, Hierarchical deformable registration, Nonlinear normalization",
author = "Liyang Wei and Dinggang Shen and Dinesh Kumar and Ram Turlapati and Suri, {Jasjit S.}",
year = "2008",
month = "5",
day = "15",
doi = "10.1117/12.765520",
language = "English",
isbn = "9780819469847",
volume = "6812",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

}

TY - GEN

T1 - Effect of hierarchical deformable motion compensation on image enhancement for DSA acquired via C-ARM

AU - Wei, Liyang

AU - Shen, Dinggang

AU - Kumar, Dinesh

AU - Turlapati, Ram

AU - Suri, Jasjit S.

PY - 2008/5/15

Y1 - 2008/5/15

N2 - DSA images suffer from challenges like system X-ray noise and artifacts due to patient movement. In this paper, we present a two-step strategy to improve DSA image quality. First, a hierarchical deformable registration algorithm is used to register the mask frame and the bolus frame before subtraction. Second, the resulted DSA image is further enhanced by background diffusion and nonlinear normalization for better visualization. Two major changes are made in the hierarchical deformable registration algorithm for DSA images: 1) B-Spline is used to represent the deformation field in order to produce the smooth deformation field; 2) two features are defined as the attribute vector for each point in the image, i.e., original image intensity and gradient. Also, for speeding up the 2D image registration, the hierarchical motion compensation algorithm is implemented by a multi-resolution framework. The proposed method has been evaluated on a database of 73 subjects by quantitatively measuring signal-to-noise (SNR) ratio. DSA embedded with proposed strategies demonstrates an improvement of 74.1% over conventional DSA in terms of SNR. Our system runs on Eigen's DSA workstation using C++ in Windows environment.

AB - DSA images suffer from challenges like system X-ray noise and artifacts due to patient movement. In this paper, we present a two-step strategy to improve DSA image quality. First, a hierarchical deformable registration algorithm is used to register the mask frame and the bolus frame before subtraction. Second, the resulted DSA image is further enhanced by background diffusion and nonlinear normalization for better visualization. Two major changes are made in the hierarchical deformable registration algorithm for DSA images: 1) B-Spline is used to represent the deformation field in order to produce the smooth deformation field; 2) two features are defined as the attribute vector for each point in the image, i.e., original image intensity and gradient. Also, for speeding up the 2D image registration, the hierarchical motion compensation algorithm is implemented by a multi-resolution framework. The proposed method has been evaluated on a database of 73 subjects by quantitatively measuring signal-to-noise (SNR) ratio. DSA embedded with proposed strategies demonstrates an improvement of 74.1% over conventional DSA in terms of SNR. Our system runs on Eigen's DSA workstation using C++ in Windows environment.

KW - Diffusion

KW - DSA

KW - Hierarchical deformable registration

KW - Nonlinear normalization

UR - http://www.scopus.com/inward/record.url?scp=43249117165&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=43249117165&partnerID=8YFLogxK

U2 - 10.1117/12.765520

DO - 10.1117/12.765520

M3 - Conference contribution

AN - SCOPUS:43249117165

SN - 9780819469847

VL - 6812

BT - Proceedings of SPIE - The International Society for Optical Engineering

ER -