Research On The Method And Application Of The Correction Of Respiratory Motion Artifact In PET/CT Imaging

PET/CT imaging plays a key role in tumor diagnosis and radiationtreatment planning. However, respiratory motion results in severe motionartifact in thoracic and abdomen PET images due to the long scanning time.Respiratory motion artifact significantly degrades PET images by reducingspatial resolution, tumor-to-background contrast；it also affects quantitationaccuracy, reduces the measured activity level of standard uptake value,causesthe tumor volume to be overestimated and thus increases the planned targetvolume. Existing approaches to reduce the blurring artifact involve acquiringimage in gated mode and using complicated registration-based orreconstruction-based motion correction algorithms. These methods requiremulti-frame acquisitions, detailed understanding of the geometry of scanner andthe response characteristics of each detector, higher CT dose and specializedreconstruction algorithms, thus is expensive in terms of time consuming,memory and health care.In view of the fact that respiratory gating device and its matched motioncorrection algorithms is too expensive to be widely used in domestic clinicalpractice, we proposed a post-reconstruction motion artifact correctionframework for un-gated PET/CT imaging using image restoration techniques.The advantage of proposed method is that it is independent of any particularimaging device and is easy to implement with less computing burden. We justuse the reconstructed image to estimate the original non blurred image throughmotion estimation and motion correction. In motion estimation, we proposed aminmax intensity directional derivative analysis and average auto-correlationanalysis to estimate or identify two PSF parameters: motion direction andmotion extent, respectively, weighted average and local interpolation were alsoused to reduce the stochastic error and improve estimation precision; in motioncorrection, we proposed a modified Richardson-Lucy deconvolution algorithmin conjunction with à trous wavelet residual de-noising to restore the motion blurred image according to estimated motion parameters. The wavelet denoisingmodification is aimed to suppress the deconvolution induced noise amplificationeffect and ringing artifact, moreover, an edge-preservation filteringpreprocessing was also employed to further improve the quality of deconvolutedimage. Simulation and mobile phantom data was used to test and evaluate theproposed methods before applied to clinical lung tumor PET images.We proposed a statistical study based on respiratory motion artifactcorrection results of39cases lung tumor PET data. We statistically showed therelationship between respiratory motion artifact and influences such asbreathing magnitude, tumor size, tumor location, patient height and gender etcthrough multi-regression analysis. We also tested the ability of resultedregression equations to estimate or predict the extent of motion artifact.To further improve the quality of motion corrected PET image, weproposed a new PET/CT image fusion strategy based on à trous wavelettransform. Combined with respiratory motion artifact correction, the method isable to produce a PET/CT fused image with a significantly enhancededge-sharpness and anatomical structure meanwhile preserve the quantitativeinformation of tumor target. Resulted image is therefore able to improve thelung tumor diagnosis but also can be used in tumor target delineation andactivity quantitative analysis.