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Automatic tilt series alignment

Automatic tilt series alignment. C.O.S. Sorzano, C. Messaoudi, M. Eibauer, R. Hegerl, R. Marabini, S. Nickell, S. Marco, J.M. Carazo. Biocomputing Unit, National Center of Biotechnology (CSIC), Spain Max-Planck Institute for Biophysics, Germany Institute Curie, France. Problem statement.

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Automatic tilt series alignment

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  1. Automatic tilt series alignment C.O.S. Sorzano, C. Messaoudi, M. Eibauer, R. Hegerl, R. Marabini, S. Nickell, S. Marco, J.M. Carazo. Biocomputing Unit, National Center of Biotechnology (CSIC), Spain Max-Planck Institute for Biophysics, Germany Institute Curie, France

  2. Problem statement

  3. Manual alignment IMOD

  4. Manual alignment IMOD

  5. Choose landmark chains Estimate 3D landmarks and tilt axis Discard wrong chains Automatic image alignment xmipp_angular_assign_for_tilt_series

  6. Automatic image alignment xmipp_angular_assign_for_tilt_series • Choose landmark chains • Estimate affine transformations between image pairs • Track small local regions along the tilt series as much as possible (use the affine transformation as first approximation and locally refine through correlation) No need for gold particles!!

  7. Automatic image alignment xmipp_angular_assign_for_tilt_series • Choose landmark chains • Estimate affine transformations between image pairs • Track critical points (local minima after noise supression)

  8. Automatic image alignment xmipp_angular_assign_for_tilt_series • Choose landmark chains • Estimate 3D landmarks and tilt axis Iterative solution • Discard wrong chains • Discard through residuals

  9. Results Slices through the automatically reconstructed volume Slices through the manually reconstructed volume

  10. Performance 8 processors: • 512x512x91= 10 minutes • 650x650x121= 15 minutes • 1300x1300x121= 2 hours Reprojection error between 0.5 and 1.5 pixels

  11. Availability

  12. Availability: Xmipp and TomoJ

  13. Conclusions • Tilt series alignment can be achieved by many short automatically detected chains • Many is between 500 and 10.000 • Short is: • Grid: between 5 to 20 images • Critical points: between 10 to 30 images • Few parameters: • Grid: correlation threshold between patches • Critical points: number of seeds in each image • Fast depending on size • The absolute position of the tilt axis cannot be uniquely determined by the projection geometry • Future: Batch mode reconstruction (X-rays, EM)

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