1. -1- Massachusetts General Hospital National Alliance for Medical Image Computing Using Plastimatch for Landmark-Based Registration Nadya Shusharina Department of Radiation Oncology Massachusetts General Hospital 3D Slicer Training Compendium Tutorial Version 1.0, Jan 27, 2011

2. -2- Massachusetts General Hospital National Alliance for Medical Image Computing Learning Objective This tutorial is a step-by-step guide, and includes: 1) Downloading the Plastimatch extension to 3D Slicer 2) Loading the sample images 3) Visualizing the example data 4) Creating fiducial lists 5) Running LANDWARP Landmark deformable registration 6) Advanced Registartion Options The plastimatch web site is: http://plastimatch.org

3. -3- Massachusetts General Hospital National Alliance for Medical Image Computing Prerequisites This tutorial assumes that you have already downloaded the sample data. You can get the data from here: http://forge.abcd.harvard.edu/gf/download/frsrelease/85/1596/synthetic_img.zip

4. -4- Massachusetts General Hospital National Alliance for Medical Image Computing Part 1: Downloading the Plastimatch Extension

5. -5- Massachusetts General Hospital National Alliance for Medical Image Computing (This part of the tutorial might not work correctly, pending the Slicer 3.6 release)

6. -6- Massachusetts General Hospital National Alliance for Medical Image Computing Start up 3D Slicer Choose “Extension Manager” from the “View” menu

7. -7- Massachusetts General Hospital National Alliance for Medical Image Computing Click “Next”

8. -8- Massachusetts General Hospital National Alliance for Medical Image Computing Find the plastimatch plugin, and click “Select” Then, click “Download and Install”

9. -9- Massachusetts General Hospital National Alliance for Medical Image Computing The “Status” should become green Click “Next”

10. -10- Massachusetts General Hospital National Alliance for Medical Image Computing Restart 3D Slicer

11. -11- Massachusetts General Hospital National Alliance for Medical Image Computing Part 2: Loading the example data

12. -12- Massachusetts General Hospital National Alliance for Medical Image Computing Start up 3D Slicer

13. -13- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “Add data” from the menu

14. -14- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “Add files” in dialog box

15. -15- Massachusetts General Hospital National Alliance for Medical Image Computing Select (highlight) example files: fix.mha and mov.mha Then click “Open”

16. -16- Massachusetts General Hospital National Alliance for Medical Image Computing Click “Apply”

17. -17- Massachusetts General Hospital National Alliance for Medical Image Computing The images are now loaded

18. -18- Massachusetts General Hospital National Alliance for Medical Image Computing Part 3: Visualizing the example data

19. -19- Massachusetts General Hospital National Alliance for Medical Image Computing We can now see the alignment of the images. To see it better, we need to increase the viewpoint size. Click on the layout chooser button

20. -20- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “Red slice only”

21. -21- Massachusetts General Hospital National Alliance for Medical Image Computing Much better! We want to look at how well the images are aligned before we start 3D Slicer can view a “foreground” (F) and “background” (B) image at the same time. After loading, (F) is set to “None” in all views.

22. -22- Massachusetts General Hospital National Alliance for Medical Image Computing Click, and select “fix” as the foreground image and “mov” as the background.

23. -23- Massachusetts General Hospital National Alliance for Medical Image Computing Use the “Manipulate Slice Views” slider to blend between foreground and background

24. -24- Massachusetts General Hospital National Alliance for Medical Image Computing We can now see the alignment of the images.

25. -25- Massachusetts General Hospital National Alliance for Medical Image Computing Part 4: Creating Fiducial Lists

26. -26- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “Fiducials” from the Modules menu

27. -27- Massachusetts General Hospital National Alliance for Medical Image Computing Clic on Fiducial List and Create New FiducialList Rename it as “fixed” Repeat one more time to obtain “moving” list

28. -28- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “fixed” list. Slide to the foreground image. Clic on “Create-and-place” fiducials.

29. -29- Massachusetts General Hospital National Alliance for Medical Image Computing Create fiducials by clicking on lattice corners

30. -30- Massachusetts General Hospital National Alliance for Medical Image Computing Slide to the background image. Make “fixed” fiducials invisible.

31. -31- Massachusetts General Hospital National Alliance for Medical Image Computing Choose “moving” list. Create “moving” fiducials IN THE SAME ORDER as “fixed” fiducials.

32. -32- Massachusetts General Hospital National Alliance for Medical Image Computing Part 5: Running LANDWARP Landmark deformable registration

33. -33- Massachusetts General Hospital National Alliance for Medical Image Computing Go back to the module selector. Choose “LANDWARP Landmark deformable registartion” from “Plastimatch” section

34. -34- Massachusetts General Hospital National Alliance for Medical Image Computing Set “Fixed Volume” to “fix” Set “Moving Volume” to “mov” Set “Output Volume” to “Create New Volume” Set “Fixed Fiducials” to “fixed” Set “Moving Fiducials” to“moving” Use default RBF radius, Stiffness and Default Pixel Value Click “Apply”

35. -35- Massachusetts General Hospital National Alliance for Medical Image Computing Check the status in the status bar The registration takes 10 to 15 seconds

36. -36- Massachusetts General Hospital National Alliance for Medical Image Computing When the registration is complete, the warped image is automatically displayed

37. -37- Massachusetts General Hospital National Alliance for Medical Image Computing You have to set the foreground view again to see the registration quality Your results should look like this.

38. -38- Massachusetts General Hospital National Alliance for Medical Image Computing Part 6: Advanced Registartion Options

39. -39- Massachusetts General Hospital National Alliance for Medical Image Computing By default, registration does not include regularization of the vector field, i.e. “Stiffness” is set to “0” But for some images regularization is a need.

40. -40- Massachusetts General Hospital National Alliance for Medical Image Computing Go back to File Menu and load images square_fix.mha, square_mov_mha and fiducials square_fixed.fcsv, square_moving.fcsv

41. -41- Massachusetts General Hospital National Alliance for Medical Image Computing Blended foreground and background images look like this You can look at them one at a time by sliding the slice view manipulator To see fiducials right-click on any of them in the list

42. -42- Massachusetts General Hospital National Alliance for Medical Image Computing Result for LANDWARP default settings looks like this

43. -43- Massachusetts General Hospital National Alliance for Medical Image Computing Setting “Stiffness” to 0.3 improves the result significantly

44. -44- Massachusetts General Hospital National Alliance for Medical Image Computing Increasing the “Stiffness” improves smoothness, but Declines accuracy of landmark matching NOTE THAT

45. -45- Massachusetts General Hospital National Alliance for Medical Image Computing Conclusion Congratulations! You have completed the tutorial. Please send corrections or suggestions to: Nadya Shusharina nshusharina@partners.org@partners.org Or visit the web page at: http://plastimatch.org

46. -46- Massachusetts General Hospital National Alliance for Medical Image Computing National Alliance for Medical Image Computing NIH U54EB005149 Acknowledgements National Institutes of Health NIH / NCI 6-PO1 CA 21239 Federal share of program income earned by MGH on C06CA059267 Progetto Rocca Foundation A collaboration between MIT and Politecnico di Milano