Conference Paper

Respiratory Motion Correction in 4D PET/CT: Comparison of Implementation Methodologies for Incorporation of Elastic Transformations in the Reconstruction System Matrix

Lab. du Traitement de l'Inf. Medicale, Univ. de Bretagne occidentale, Brest
DOI: 10.1109/NSSMIC.2006.354388 Conference: Nuclear Science Symposium Conference Record, 2006. IEEE, Volume: 4
Source: IEEE Xplore

ABSTRACT Respiratory motion in emission tomography leads to reduced image quality. Proposed correction methodology has been concentrating on the use of respiratory synchronised acquisitions leading to gated frames. Such frames however are of low signal to noise ratio as a result of containing reduced statistics. Therefore a method accounting for respiratory motion effects without affecting the statistical quality of the reconstructed images is necessary. In this work we describe the implementation of an elastic transformation within a list-mode based reconstruction for the correction of respiratory motion over the thorax. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List mode data based PET simulated frames were subsequently produced by combining the NCAT datasets with a Monte Carlo simulation. Transformation parameters accounting for respiratory motion were estimated according to an elastic registration of the NCAT dynamic CT images and were subsequently applied during the image reconstruction of the original emission list mode data. The One-pass list mode EM (OPL-EM) algorithm was modified to integrate the elastic transformation in the sensitivity matrix. Three different implementations have been investigated (no interpolation, trilinear interpolation, b-spline functions incorporation). The corrected images were compared with uncorrected respiratory motion average images. Results demonstrate that the use of elastic transformations in the reconstruction system matrix lead to uniform improvement across the lung field for different lesion sizes. The use of a trilinear interpolation or the incorporation of the b-spline functions lead to times of execution equivalent to standard image reconstruction. However, trilinear interpolation leads to artefacts in areas such as the diaphragm where the largest elastic deformations are occurring.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Respiratory motion reduces overall qualitative and quantitative accuracy in emission tomography imaging. The impact of respiratory motion has been further highlighted in the use of multi-modality imaging devices, where differences in respiratory conditions between the acquisition of anatomical and functional datasets can lead to significant artefacts. Current state of the art in accounting for such effects is the use of respiratory-gated acquisitions. Although such acquisitions may lead to a certain reduction in respiratory motion effects, the improvement is reduced as a result of using only part of the available data to reconstruct the individual gated frames. Approaches to correct the differences in the respiratory motion between the individual gated frames, in order to allow their combination, can be divided in two categories, namely, image or raw data based. The image-based approaches make use of registration algorithms to realign the gated images and, subsequently, sum them together; while the raw data approaches, based on the incorporation of transformations, account for differences in the respiratory motion between individual frames, either prior or during the reconstruction of all of the acquired data. Previous research in this field has demonstrated that a non-rigid local-based model leads to better results compared with an affine model in accounting for respiratory motion between gated frames. In addition, a superior image contrast can be obtained by incorporating the necessary transformation in the reconstruction process in comparison to an image-based approach.
    Medecine Nucleaire 04/2007; 31(4):153-159. DOI:10.1016/j.mednuc.2007.02.002 · 0.16 Impact Factor

Full-text (2 Sources)

Available from
Jun 1, 2014