1 / 79

CSci 6971: Image Registration Lecture 9: Registration Components February 10, 2004

CSci 6971: Image Registration Lecture 9: Registration Components February 10, 2004. Prof. Chuck Stewart, RPI Dr. Luis Ibanez, Kitware. Registration Components. Basic Registration Framework. Image Registration Framework. Fixed Image. Metric. Moving Image. Interpolator. Optimizer.

skyler
Download Presentation

CSci 6971: Image Registration Lecture 9: Registration Components February 10, 2004

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CSci 6971: Image Registration Lecture 9: Registration ComponentsFebruary 10, 2004 Prof. Chuck Stewart, RPI Dr. Luis Ibanez, Kitware

  2. Registration Components Basic Registration Framework Lecture 9

  3. Image Registration Framework FixedImage Metric MovingImage Interpolator Optimizer Transform Parameters Lecture 9

  4. Other Image Metrics Mean Reciprocal Square Differences Lecture 9

  5. 1 Match( A , B ) += ( 1 + λ∙Difference( index ) 2 ) Mean Reciprocal Squared Differences For each pixel in A Image A Image B Difference( index ) = A( index ) – B( index ) Lecture 9

  6. j j i i Moving Image Grid Fixed Image Grid y’ y Space Transform x’ x Moving ImagePhysical Coordinates Fixed ImagePhysical Coordinates For each pixel in the Fixed Image Lecture 9

  7. Mean Reciprocal Squared Differences #include "itkImage.h" #include "itkMeanReciprocalSquareDifferenceImageToImageMetric.h" #include "itkLinearInterpolateImageFunction.h" #include "itkTranslationTransform.h" typedef itk::Image< char, 2 > ImageType; ImageType::ConstPointerfixedImage = GetFixedImage(); ImageType::ConstPointermovingImage = GetMovingImage(); typedef itk::LinearInterpolateImageFunction<ImageType, double >InterpolatorType; InterpolatorType::Pointerinterpolator = InterpolatorType::New(); typedef itk::TranslationTransform< double, 2 > TransformType; TransformType::Pointertransform = TransformType::New(); Lecture 9

  8. Mean Reciprocal Squared Differences typedef itk::MeanReciprocalSquareDifferenceImageToImageMetric< ImageType,ImageType > MetricType; MetricType::Pointermetric = MetricType::New(); metric->SetInterpolator( interpolator ); metric->SetTransform( transform ); metric->SetFixedImage( fixedImage ); metric->SetMovingImage( movingImage ); MetricType::TransformParametersTypetranslation( Dimension ); translation[0] = 12; translation[1] = 27; double value = metric->GetValue( translation ); Lecture 9

  9. Evaluating many matches y y Transform x x Fixed Image Moving Image Lecture 9

  10. Plotting the Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  11. Plotting the Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  12. Evaluating many matches y y Transform (-15,-25) mm x x Fixed Image Moving Image Lecture 9

  13. Plotting the Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  14. Plotting the Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  15. Watch over your optimizer Example:Optimizer registering an image with itself starting at (-15mm, -25mm) Lecture 9

  16. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 1.0 mm Lecture 9

  17. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 2.0 mm Lecture 9

  18. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 5.0 mm Lecture 9

  19. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 10.0 mm Lecture 9

  20. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 20.0 mm Lecture 9

  21. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 40.0 mm Lecture 9

  22. Quiz #1 If the Metric is NoisyWhere is the noise coming from ? Lecture 9

  23. Smoothing the Image Lecture 9

  24. Evaluating many matches y y Transform x x Fixed Image Moving Image Lecture 9

  25. Plotting the Smoothed Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  26. Plotting the Smoothed Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  27. Watch over your optimizer Example:Optimizer registering an image with itself starting at (-15mm, -25mm) Lecture 9

  28. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 1.0 mm Lecture 9

  29. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 2.0 mm Lecture 9

  30. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 5.0 mm Lecture 9

  31. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 10.0 mm Lecture 9

  32. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 20.0 mm Lecture 9

  33. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 40.0 mm Lecture 9

  34. Evaluating many matches y y Transform (-15,-25) mm x x Fixed Image Moving Image Lecture 9

  35. Plotting the Smoothed Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  36. Plotting the Smoothed Metric Mean Reciprocal Squared Differences Transform Parametric Space Lecture 9

  37. Watch over your optimizer Example:Optimizer registering an image shifted by (-15mm, -25mm)The optimizer starts at (0mm,0mm) Lecture 9

  38. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 1.0 mm Lecture 9

  39. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 2.0 mm Lecture 9

  40. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 5.0 mm Lecture 9

  41. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 10.0 mm Lecture 9

  42. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 20.0 mm Lecture 9

  43. Plotting the Optimizer’s Path Mean Reciprocal Squared Differences Step Length = 40.0 mm Lecture 9

  44. Other Image Metrics Multi – ModalityRegistration Lecture 9

  45. Multiple Image Modalities Number of pairs Lecture 9

  46. Multiple Image Modalities More possible pairs Lecture 9

  47. Intuitive Notion of Joint Entropy The More Pairs ExistThe Larger the Joint Entropy Lecture 9

  48. Mutual Information Reduction of Number of PairsReduction of Joint Entropy Lecture 9

  49. Mutual Information Mutual Information =Joint Entropy ( Image A, Image B )- Entropy Image A- Entropy Image B Lecture 9

  50. Mattes Mutual Information #include "itkImage.h" #include "itkMattesMutualInformationImageToImageMetric.h" #include "itkLinearInterpolateImageFunction.h" #include "itkTranslationTransform.h" typedef itk::Image< char, 2 > ImageType; ImageType::ConstPointerfixedImage = GetFixedImage(); ImageType::ConstPointermovingImage = GetMovingImage(); typedef itk::LinearInterpolateImageFunction<ImageType, double >InterpolatorType; InterpolatorType::Pointerinterpolator = InterpolatorType::New(); typedef itk::TranslationTransform< double, 2 > TransformType; TransformType::Pointertransform = TransformType::New(); Lecture 9

More Related