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Automated Segmentation and Interpolation in Sinograms for Metal Artifact Suppression in CT Wouter JH Veldkamp, PhD Raoul MS Joemai, BSc Aart J. van der Molen, MD Jacob Geleijns, PhD Department of Radiology, Leiden University Medical Center, The Netherlands
[object Object],Introduction
Traditional image based approach ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],1. W.A.Kalender, R.Hebel, and J.Ebersberger, "Reduction of Ct Artifacts Caused by Metallic Implants," Radiology 164, 576-577 (1987).
Traditional image based approach For instance: W.A.Kalender, R.Hebel, and J.Ebersberger, "Reduction of Ct Artifacts Caused by Metallic Implants," Radiology 164, 576-577 (1987). original sinogram segmented sinogram interpol . sinogram back-projection uncorrected corrected Exclusion by interpolation segmented back-projection forward-projection
Overview of the research: raw data based approach ,[object Object],[object Object],[object Object],[object Object],[object Object]
Overview of the research ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],2. Kachelriess, M., Thesis/Dissertation, Friedrich-Alexander-Universität Erlangen-Nurnberg, 1998.
Raw data based approach Original sinogram mask Interpol. sinogram Back-projection Back-projection uncorrected corrected High pass filter  & thresholding MRF Canny filter Interpolation Selecting ROI
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],3. N.Karssemeijer, "A Stochastic-Model for Automated Detection of Calcifications in Digital Mammograms," Lecture Notes in Computer Science 511, 227-238 (1991). 4. W.J.H.Veldkamp and N.Karssemeijer, "Accurate seg mentation and contrast measurement of microcalcifications in mammograms: A phantom study," Medical Physics 25, 1102-1110 (1998). Raw data based approach
[object Object],a b c d e f g h 5. T.W.Ridler and S.Calvard, "Picture Thresholding Using An Iterative Selection Method," Ieee Transactions on Systems Man and Cybernetics 8, 630-632 (1978). Mean foreground estimation: 2-D order-statistic filtering Mean background estimation: rough interpol. using mask (a) Raw data based approach
The following empirically determined parameter values are used in the MRF model for segmentation of metal implants. Raw data based approach Parameter values 900 150 7 0 Background ( l=0 ) 300 0 0 0 Foreground ( l=1 ) δ γ β α
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],6. M.Yazdia, L.Gingras, and L.Beaulieu, "An adaptive approach to metal artifact reduction in helical computed tomography for radiation therapy treatment planning: Experimental and clinical studies," International Journal of Radiation Oncology Biology Physics 62, 1224-1231 (2005). 7. J.H.Elder and R.M.Goldberg, "Image editing in the contour domain," Ieee Transactions on Pattern Analysis and Machine Intelligence 23, 291-296 (2001). 8. J.D.Wood and P.F.Fisher, "Assessing Interpolation Accuracy in Elevation Models," Ieee Computer Graphics and Applications 13, 48-56 (1993). Interpolation and signal addition
Overview of interpolation approaches ,[object Object],[object Object],[object Object],[object Object],Detector elements Viewing angle
Signal addition a pragmatic method was applied Original signal Interpolated signal Interpolated signal + fraction of original signal
Phantom ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
a b c d e 3 1 2 4 5 Metal artifact reduction in phantom images. Fig. a shows the uncorrected scan and the ROIs.  Among other things the effect of different interpolation methods is shown.  Fig. b shows a detail of the corrected image using the per view interpolation, Fig. c shows the same detail corresponding to the smooth interpolation and Fig. d corresponds to the shortest distance interpolation method. Finally, in Fig. e a result without adding the scaled projections to the interpolated values is shown (using smooth interpolation). Note that the streaking pattern is no longer evident in the images, but the region of reduced density between the objects is still present in the images and more evident in Fig. b (per view interpolation).  Results
Results Mean CT number and the standard deviation, both measured in HU, for pixels belonging to different inserts (ROIs) in the phantom are determined as a measure of distortion. Values are based on measurements in 40 consecutive reconstructed slices.  88 +/- 56 117 +/- 33 -53 +/- 27 -52 +/- 36 862 +/- 48 Smooth interpolation without signal 90 +/- 56 119 +/- 34 -54 +/- 28 -52 +/- 36 865 +/- 48 Smooth interpolation 99 +/- 51 118 +/- 34 -52 +/- 28 -53 +/- 37 867 +/- 48  Shortest distance interpolation 76 +/- 57  118 +/- 34  -67 +/- 28 -49 +/- 36 841 +/- 47 Per view interpolation 101 +/- 98 116 +/- 72 -64 +/- 85 -52 +/- 63 889 +/- 82 No artifact suppression With titanium 117 +/- 36 117 +/- 36 -62 +/- 30 -59 +/- 36 902 +/- 49 Without titanium Original raw data 5: PMMA 4: PMMA 3: PVC 2: PVC 1: Teflon Phantom configuration / Correction method Raw data type Region of interest
Patients ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Results Patient with hip implant. At the left slices of the original scan data are shown. At the right corresponding slices are shown that correspond to corrected raw data (smooth interpolation). The window center and window width were respectively 150 and 700 HU for all slices. Four different slices are shown consecutively.
Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
Results ,[object Object],[object Object],[object Object],3.2 2.0 Assessment of large anatomical structures 4.0 3.2 Neighboring bone loss 4.0 2.4 Prosthesis Assessment of 3.8 1.8 Small vasc. str. 4.0 1.8 Lymph nodes Visibility of small anatomical structures Supressed Original Average score Visibility and assessment
[object Object],[object Object],[object Object],[object Object],Conclusions en discussion
Conclusions en discussion ,[object Object],[object Object],[object Object]
THE END For further information contact:

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Metal artifact reduction

  • 1. Automated Segmentation and Interpolation in Sinograms for Metal Artifact Suppression in CT Wouter JH Veldkamp, PhD Raoul MS Joemai, BSc Aart J. van der Molen, MD Jacob Geleijns, PhD Department of Radiology, Leiden University Medical Center, The Netherlands
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  • 4. Traditional image based approach For instance: W.A.Kalender, R.Hebel, and J.Ebersberger, "Reduction of Ct Artifacts Caused by Metallic Implants," Radiology 164, 576-577 (1987). original sinogram segmented sinogram interpol . sinogram back-projection uncorrected corrected Exclusion by interpolation segmented back-projection forward-projection
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  • 7. Raw data based approach Original sinogram mask Interpol. sinogram Back-projection Back-projection uncorrected corrected High pass filter & thresholding MRF Canny filter Interpolation Selecting ROI
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  • 10. The following empirically determined parameter values are used in the MRF model for segmentation of metal implants. Raw data based approach Parameter values 900 150 7 0 Background ( l=0 ) 300 0 0 0 Foreground ( l=1 ) δ γ β α
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  • 13. Signal addition a pragmatic method was applied Original signal Interpolated signal Interpolated signal + fraction of original signal
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  • 15. a b c d e 3 1 2 4 5 Metal artifact reduction in phantom images. Fig. a shows the uncorrected scan and the ROIs. Among other things the effect of different interpolation methods is shown. Fig. b shows a detail of the corrected image using the per view interpolation, Fig. c shows the same detail corresponding to the smooth interpolation and Fig. d corresponds to the shortest distance interpolation method. Finally, in Fig. e a result without adding the scaled projections to the interpolated values is shown (using smooth interpolation). Note that the streaking pattern is no longer evident in the images, but the region of reduced density between the objects is still present in the images and more evident in Fig. b (per view interpolation). Results
  • 16. Results Mean CT number and the standard deviation, both measured in HU, for pixels belonging to different inserts (ROIs) in the phantom are determined as a measure of distortion. Values are based on measurements in 40 consecutive reconstructed slices. 88 +/- 56 117 +/- 33 -53 +/- 27 -52 +/- 36 862 +/- 48 Smooth interpolation without signal 90 +/- 56 119 +/- 34 -54 +/- 28 -52 +/- 36 865 +/- 48 Smooth interpolation 99 +/- 51 118 +/- 34 -52 +/- 28 -53 +/- 37 867 +/- 48 Shortest distance interpolation 76 +/- 57 118 +/- 34 -67 +/- 28 -49 +/- 36 841 +/- 47 Per view interpolation 101 +/- 98 116 +/- 72 -64 +/- 85 -52 +/- 63 889 +/- 82 No artifact suppression With titanium 117 +/- 36 117 +/- 36 -62 +/- 30 -59 +/- 36 902 +/- 49 Without titanium Original raw data 5: PMMA 4: PMMA 3: PVC 2: PVC 1: Teflon Phantom configuration / Correction method Raw data type Region of interest
  • 17.
  • 18. Results Patient with hip implant. At the left slices of the original scan data are shown. At the right corresponding slices are shown that correspond to corrected raw data (smooth interpolation). The window center and window width were respectively 150 and 700 HU for all slices. Four different slices are shown consecutively.
  • 19. Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
  • 20. Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
  • 21. Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
  • 22. Results Results of four other patients with different implants. At left original slices are shown and at the right slices from corrected raw data are shown (smooth interpolation). For left and right images identical window center and window width was chosen.
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  • 26. THE END For further information contact: