A flexible approach to motion correction in nuclear medicine

Wells, Kevin; Goswami, Budhaditya; Rahni, Ashrani Aizzuddin Abd; Jones, J. Adam; Alnowami, Majdi R.; Lewis, Emma; Guy, Matthew

doi:10.1109/nssmic.2009.5402030

Cited by 11 publications

(17 citation statements)

References 2 publications

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“…The sampling rate of the system was user-selected to 10 frame/sec. The markers for this system were arranged on each volunteer's anterior surface in a four-by-four grid [9], [10]. Table I illustrates the result obtained from scanning the aforementioned volunteer cohort.…”

Section: B Data Acquisitionmentioning

confidence: 99%

Inter- and intra-subject variation of abdominal vs. thoracic respiratory motion using kernel density estimation

Alnowami

Lewis

Wells

et al. 2010

IEEE Nuclear Science Symposuim &Amp; Medical Imaging Conference

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Abstract-In nuclear medicine, there is a significant research focus in developing a new approach in monitoring, tracking and compensating respiratory motion during image acquisition. We address this by attempting to model the respiratory cycle pattern and finding a method that describes the configuration of the anterior surface which then correlates with the internal position/configuration of the internal organ as a foundation for motion compensation. This paper presents novel work in parameterizing external respiratory motion using a method based on the variation of abdominal vs. thoracic surface markers to investigate inter-and intra-subject variation. The dominant mode of variation of the Abdominal and Thoracic surfaces during respiration using Principle Component Analysis (PCA) is studied. This demonstrates that pattern of TS vs AS motion appears temporally at a global level stable. Thus Although breathing style is consistent within a given subject, we there observe temporal changes in the amplitude and density of the PDF in intra-subject data.

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Section: B Data Acquisitionmentioning

confidence: 99%

Inter- and intra-subject variation of abdominal vs. thoracic respiratory motion using kernel density estimation

Alnowami

Lewis

Wells

et al. 2010

IEEE Nuclear Science Symposuim &Amp; Medical Imaging Conference

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“…This paper continues the development of a motion correction framework that has been proposed in Wells et al, 2009 2 . In this framework, respiratory motion correction is proposed to be applied continuously, enabling the use of all potential data, for example, list mode data in NM before image reconstruction.…”

Section: Introductionmentioning

confidence: 73%

“…Iterative model update constitute an additional application specific adaptation method that mainly seek to improve the distribution of the stochastic components of the transition and measurement models which are represented respectively by v k-1 and w k in (1) and (2). The models are updated by incorporating observations and initial estimates of all test datasets into a subsequent training stage to re-estimate the transition and measurement models.…”

Section: Iterative Model Updatementioning

confidence: 99%

“…Figure 3 illustrates the model update step. During subsequent iterations of the PF approach, the PF is run without adaptation methods (2) and (3) as the updated models now have probability distributions which better reflect the variations across the test datasets. The effect this has on the adaptability of the transition and measurement models will be discussed in Section 4 along with its effect on motion estimation.…”

Section: Iterative Model Updatementioning

confidence: 99%

“…In this framework, respiratory motion correction is proposed to be applied continuously, enabling the use of all potential data, for example, list mode data in NM before image reconstruction. This has been deemed most appropriate considering the complex nature of respiratory motion 2,3 . A probabilistic view of the problem has also been incorporated into the proposed framework to acknowledge the inherent uncertainties and this forms the basis of the particle filter (PF) approach.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2011

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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.

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A virtual dissection based registration to model patient-specific respiratory motion

Jones

Lewis

Guy

et al. 2009

2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC)

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Abstract-This work is directed at reducing patient induced blurring in SPECT imaging due to breathing motion. As image resolution improves this breathing motion is becoming increasingly significant.Method: The NCAT phantom and an associated medical image processing package (RMDP) are used to obtain a breathing cycle of images (both CT and corresponding SPECT) and a full organ segmentation. A process termed 'virtual dissection' is undertaken which sees individual organs extracted from the main images and independently registered (ICP). These individual registrations are reconciled, combined and used to obtain improved final images.Results: The results of the objective validation techniques are presented together with a comparison of processed and unprocessed images.Conclusion: Within the scope of the synthetic data used and for organs for which the assumption of near-rigid motion holds well the technique works. In the case of the ribs and lungs further development is needed

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A flexible approach to motion correction in nuclear medicine

Cited by 11 publications

References 2 publications

Inter- and intra-subject variation of abdominal vs. thoracic respiratory motion using kernel density estimation

Inter- and intra-subject variation of abdominal vs. thoracic respiratory motion using kernel density estimation

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

A virtual dissection based registration to model patient-specific respiratory motion

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