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Image Guided Navigation System for Minimally Invasive Surgery

Image Guided Navigation System for Minimally Invasive Surgery. Hua Zhong October 2007. Outline. Minimally Invasive Surgery Registration and Navigation System Overview Ultrasound Virtual Touch 4D Registration Non-rigid Registration Visualization. Minimally Invasive Surgery.

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Image Guided Navigation System for Minimally Invasive Surgery

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  1. Image Guided Navigation System for Minimally Invasive Surgery Hua Zhong October 2007

  2. Outline • Minimally Invasive Surgery • Registration and Navigation System Overview • Ultrasound Virtual Touch • 4D Registration • Non-rigid Registration • Visualization

  3. Minimally Invasive Surgery What is minimally invasive surgery Benefits & limitations

  4. Minimally Invasive Surgery Catheter

  5. Minimally Invasive Surgery

  6. Minimally Invasive Surgery

  7. Registration & Navigation Systems What are currently available systems How do they work Limitations

  8. Registration & Navigation Systems CT image segmented 3D model reconstructed from CT

  9. Registration & Navigation Systems

  10. Catheter Bed Magnetic Transmitter Catheter Tip Example system: Biosense Carto Merge System

  11. Registration & Navigation Systems • Limitations 1: radiation • Limitations 2: manually collect surface points • Limitations 3: low accuracy

  12. Ultrasound Virtual Touch Touch with ultrasound Ultrasound image plane thickness correction Registration with virtual touch points

  13. Ultrasound Virtual Touch

  14. Ultrasound Virtual Touch

  15. Ultrasound Virtual Touch • Position Sensor Video

  16. Ultrasound Virtual Touch • Virtual Touch Video

  17. Ultrasound Virtual Touch Virtual Touch 12000+ points ~3 minutes Manual physical touch 88 points ~20 minutes

  18. Ultrasound Virtual Touch

  19. Ultrasound Virtual Touch

  20. Ultrasound Image Thickness

  21. Ultrasound Image Thickness

  22. Ultrasound Image Thickness • Thickness of ultrasound image plane, also called beam width: 5-8mm • Size of left atrium: 70-100mm • First we need to measure the thickness

  23. Measure Image Thickness Richard, B.: Test object for measurement of section thickness at us. Radiology 211 (1999) 279-282 Skolnick, M.: Estimation of ultrasound beam width in the elevation (section thick-ness) plane. Radiology 180 (1991) 286-288 Band Width 45˚ Transducer

  24. Measure Image Thickness • Precise built of model • Precise motion of the plane or multiple planes • Can we reduce all those restrictions?

  25. Measure Image Thickness Transducer

  26. Measure Image Thickness β

  27. Measure Image Thickness Measure βin ultrasound images

  28. Measure Image Thickness W is the width of the white band in ultrasound image αis the angle of the sloped plane which can be measured α= 45˚ , β= 0˚ : Thickness = w

  29. Measure Image Thickness • Move the slope around • Measure thickness at various depth • Interpolate sample thickness to generate a continuous function: Thickness = f(depth)

  30. Measure Image Thickness

  31. Correct Error from Image Thickness 1. Position and orientation of the ultrasound image plane. 2. Thickness of the image at point o. 3. Local normal of the object surface. If we know these 3 things, we can correct the error!

  32. Correct Error from Image Thickness

  33. Correct Error from Image Thickness

  34. Correct Error from Image Thickness

  35. Correct Error from Image Thickness

  36. Correct Error from Image Thickness • Position and orientation of the ultrasound image plane. • Thickness of the image at point o. • Local normal of the object surface. Yes Yes ?

  37. Correct Error from Image Thickness Estimate local surface normal • By fitting local registration points • By pre-registration

  38. Correct Error from Image Thickness Estimate local surface normal Estimated surface normal will only be used to determine which of P1 or P2 is the real surface point. It doesn’t need to be very accurate.

  39. Correct Error from Image Thickness • Position and orientation of the ultrasound image plane. • Thickness of the image at point o. • Local normal of the object surface. Yes Yes Yes

  40. Correct Error from Image Thickness • Experiment Design: • Different group with various average intersecting angles

  41. Correct Error from Image Thickness • The error is dependent on intersecting angle: smaller the angle  larger the error b b o o o’ o’ a a Prager, R.W., Rohling, R.N., Gee, A.H., Berman, L.: Rapid calibration for 3-d freehand ultrasound. In: Ultrasound in Medicine and Biology. (1998) 24(6):855-869

  42. Correct Error from Image Thickness • Experiment Design: • Different group with various average intersecting angles • Register to the surface model without correction • Register to the surface model with correction • Separate evaluation point set

  43. Correct Error from Image Thickness • Expected result Un-correct points Registration Error Corrected points Intersecting angle

  44. Correct Error from Image Thickness

  45. Correct Error from Image Thickness • Registration error around 1.8-1.9mm • Average accuracy boost: 20.45% • Consistent accuracy across the spectrum

  46. Conclusion for “Virtual Touch” • Faster • More accurate • More consistent

  47. 4D Registration Time-space registration for heart model with full motion.

  48. 4D Registration 4D Heart Model Movie

  49. 4D Registration • Capture multiple 3D models during a cardiac cycle

  50. 4D Registration • Heart shape changes from cardiac cycle • Heart shape also change from breath cycle Lung Left atrium

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