An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging

Ashrani Aizzuddin Abd Rahni, Kevin Wells, Emma Lewis, Matthew Guy, Budhaditya Goswami

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

2 Citations (Scopus)

Abstract

The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications.

Original languageEnglish
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7962
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventMedical Imaging 2011: Image Processing - Lake Buena Vista, FL
Duration: 14 Feb 201116 Feb 2011

Other

OtherMedical Imaging 2011: Image Processing
CityLake Buena Vista, FL
Period14/2/1116/2/11

Fingerprint

Nuclear medicine
nuclear medicine
Nuclear Medicine
Motion estimation
Imaging techniques
filters
estimating
respiration
organs
scanners
Uncertainty
iteration
acquisition
Respiration
education
spatial resolution
cycles
estimates
configurations

Keywords

  • Iterative Model Update
  • Nuclear Medicine Imaging
  • Particle Filter
  • Respiratory Motion Correction

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Abd Rahni, A. A., Wells, K., Lewis, E., Guy, M., & Goswami, B. (2011). An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 7962). [79624C] https://doi.org/10.1117/12.878086

An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging. / Abd Rahni, Ashrani Aizzuddin; Wells, Kevin; Lewis, Emma; Guy, Matthew; Goswami, Budhaditya.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7962 2011. 79624C.

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

Abd Rahni, AA, Wells, K, Lewis, E, Guy, M & Goswami, B 2011, An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 7962, 79624C, Medical Imaging 2011: Image Processing, Lake Buena Vista, FL, 14/2/11. https://doi.org/10.1117/12.878086
Abd Rahni AA, Wells K, Lewis E, Guy M, Goswami B. An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7962. 2011. 79624C https://doi.org/10.1117/12.878086
Abd Rahni, Ashrani Aizzuddin ; Wells, Kevin ; Lewis, Emma ; Guy, Matthew ; Goswami, Budhaditya. / An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7962 2011.
@inproceedings{0933f497466c4ebf8c5abdf43976e8a0,
title = "An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging",
abstract = "The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications.",
keywords = "Iterative Model Update, Nuclear Medicine Imaging, Particle Filter, Respiratory Motion Correction",
author = "{Abd Rahni}, {Ashrani Aizzuddin} and Kevin Wells and Emma Lewis and Matthew Guy and Budhaditya Goswami",
year = "2011",
doi = "10.1117/12.878086",
language = "English",
isbn = "9780819485045",
volume = "7962",
booktitle = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

}

TY - GEN

T1 - An iterative particle filter approach for respiratory motion estimation in nuclear medicine imaging

AU - Abd Rahni, Ashrani Aizzuddin

AU - Wells, Kevin

AU - Lewis, Emma

AU - Guy, Matthew

AU - Goswami, Budhaditya

PY - 2011

Y1 - 2011

N2 - The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications.

AB - The continual improvement in spatial resolution of Nuclear Medicine (NM) scanners has made accurate compensation of patient motion increasingly important. A major source of corrupting motion in NM acquisition is due to respiration. Therefore a particle filter (PF) approach has been proposed as a powerful method for motion correction in NM. The probabilistic view of the system in the PF is seen as an advantage that considers the complexity and uncertainties in estimating respiratory motion. Previous tests using XCAT has shown the possibility of estimating unseen organ configuration using training data that only consist of a single respiratory cycle. This paper augments application specific adaptation methods that have been implemented for better PF estimates with an iterative model update step. Results show that errors are further reduced to an extent up to a small number of iterations and such improvements will be advantageous for the PF to cope with more realistic and complex applications.

KW - Iterative Model Update

KW - Nuclear Medicine Imaging

KW - Particle Filter

KW - Respiratory Motion Correction

UR - http://www.scopus.com/inward/record.url?scp=79957998108&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79957998108&partnerID=8YFLogxK

U2 - 10.1117/12.878086

DO - 10.1117/12.878086

M3 - Conference contribution

AN - SCOPUS:79957998108

SN - 9780819485045

VL - 7962

BT - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

ER -