Tracking Objects of Interest from CT/MR Data using Dynamic 3D Ultrasound http://ssim.eng.wayne.edu/ssimi/cares/classes/g

1. Tracking Objects of Interest from CT/MR Data using Dynamic 3D Ultrasoundhttp://ssim.eng.wayne.edu/ssimi/cares/classes/group7/group7.html Group 6: Michael Shetliffe Mohammad Yaqub Mohammed Alam

2. Outline • Problem Statement • Background & Significance • Overall Aims • Methods • Ultrasound • MRI • Registration • Results • Problems • Solutions • Competition • Future Work • Conclusion

3. ProblemStatement

4. Problem • There is a criticalneedto update information based on changes occurring during surgery. • Changes: • Shift • Deformation • Vascular movement

5. Overview of Proposal • The overall objective of this proposal is to show feasibility and develop a cost-effective and efficient approach to monitor and predict deformation during surgery, allowing accurate, and real-time intra-operative information to be provided reliably to the surgeon. • The central hypothesis is that deformation can be followed intra-operatively using ultrasound technology.

6. Background & Significance • Approaches to update the pre-op data: • Intra-operative MR • Obtain updated (lower-resolution) MR data • Costly, significant setup time, OR compatibility considerations • Finite Element modeling of surrounding tissues • Challenges of parameter estimation • Parameter variation with physiologic changes • Long computation times • Use 3D Ultrasound • Convenient, safe, cheap

7. Overall Aims Image Acquisition US CT MR Segmentation Registration Evaluate the effectiveness, accuracy, and usefulness of any techniques that were used Testing the method

8. Image Acquisition – 3D Ultrasound

9. What is Ultrasound ? • High-energy sound waves (ultrasound) are bounced off internal tissues or organs and make echoes. (2-13 MHz) • Pros: • Non invasive • Real time imaging • Cons: • Cannot image bony structures • Poor native resolution • Image depends on time to echo (pixel position) and echo strength (pixel intensity)

10. Ultrasound Images (Breast) Spurious Artifacts Objects of Interest Characteristic US Noise Bench Surface Reflection

11. 3D Ultrasound – Background • 3D Ultrasound: • Tracks 2D ultrasound probe to build 3D volume from ultrasound “slices” • Can use conventional, portable ultrasound equipment to obtain 3D volumes • Still relies on ultrasonic backscattering from tissue structures  intrinsically noisy Image Processing becomes especially important

12. 3D Ultrasound - System “Stradx” Software 2D Screen Frames Frames / sec & Probe Motion 2D Ultrasound Probe 3D Position Slices in 3D Space Polaris Tracking System

13. 3D Ultrasound - Output • Output from Stradx: • .sx file: Text-based file containing 3D positions, orientations, sizes, times, etc. of individual 2D slices • .sxi file: Binary file of 8-bit pixel values • What we need: • 3D image data in “conventional” format (e.g. dicom, Analyze) that can be read into other systems for processing • (Prior to starting this project, it was thought that this was what we would have.)

14. 3D Ultrasound - Output • Examples: 1-Pass Probe Motion

15. 3D Ultrasound - Output • Examples: 2-pass had problems with “inter-pass” alignment 2-Pass Probe Motion

16. 3D Ultrasound - Post Processing

17. 3D Ultrasound - Conversion • 2 Additional Tools (Provided as part of the Stradx distribution): • SelectSX: (adjust for data too “dense”) • StackSX: (create evenly spaced, uniformly aligned slices)

18. 3D Ultrasound - Conversion • Read new .sx file as “Raw” 8-bit data into a medical imaging tool (xmedcon, osirix, 3d-slicer) Region of Interest moves within resliced image between slices.

19. 3D Ultrasound - Conversion At this point, we can treat our US data as a standard set of images, and export to other convenient formats Slice separation distance determined from .sx file position data.

20. 3D Ultrasound – Post-Processing • Basic Objectives: • Reduce background noise • Segment (or at least highlight) object(s) of interest • Approach: • Stradx has some inbuilt segmentation/registration capabilities – not used • Used MATLAB to investigate feasible techniques that could later be integrated into a stand-alone system.

21. 3D Ultrasound – Post-Processing Noise Reduction Techniques: Original Image Median Filter Gaussian Blur

22. 3D Ultrasound – Post-Processing Noise Reduction Techniques: Original Image Median Filter Gaussian Blur

23. 3D Ultrasound – Post-Processing Noise Reduction Techniques: Original Image Median Filter Gaussian Blur

24. 3D Ultrasound – Summary • In this portion of work we have: • Acquired updated ultrasound image data that better meets our requirements for working with objects of interest. • Converted the image data to formats that can be easily used in a wide variety of medical imaging systems. • Processed the ultrasound image data to enable higher quality results from subsequent registration with other modalities.

25. Image Acquisition -MRI / CT

26. What is MRI? • MRI stands for Magnetic Resonance Imaging. • The MR images used to image internal structures of the body, particularly the soft tissues. • We used GE 4 tesla MRI machine to get some MR images for the phantom we have. MR brain image

27. GE MRI machine

28. What is CT? • CT stands for Computed Tomography. • CT image is a specialized form of x-ray imaging. • It shows bony structures. • We used CT images in our project. • It did not give good results. CT brain image

29. MRI/CT Images (Breast) MR T-1 Images MR T-2 Images CT Images No internal information No big difference because the phantom is MR incompatible

30. Image SegmentationMRI

31. MRI Segmentation • No quantitative phantom information. • Introduce artificial shift of objects of interest. • We did the movement using a manual linear interpolation method. • Segmentation • Object matching • Thresholding

32. Example Original MRI slice Manually shifted object of interest

33. Example (cont.) Original segmented object of interest inside an MR image Automatically segmented object of interest inside the shifted MR image

34. Image Registration

35. Registration • Registering different modalities: • Original MR to shifted MR • Original MR to CT • Original MR to Ultrasound • Manual landmark. • An automated registration - mutual information. • Need more human interaction.

36. Example Original fixed modality Moving modality (The Shifted object of interest)

37. Example (cont.) Original object of interest shifted object of interest A slice that contains the registered data Showing both the original & the shifted points

38. Example (cont.) MR image with three objects Ultrasound image with three objects Need for deformable registration method

39. Problems, Proposed Solutions and Future Work

40. Problems • Phantom • Echo-sensitive material • Water Content • MRI Compatible • Atlas • Ultrasound • Quality of Images • System Calibration • Registration

41. Proposed Solutions - Phantoms • Multi modality Phantoms - $ 2000.00

42. Proposed Solutions - Ultrasound • Better Ultrasound Transducer

43. Proposed Solutions - Registration Existing Research

44. Competitors • Ultrasound Probes - Philips, Siemens, GE • Registration Techniques – Related research available • Overall Intraoperative Tracking System using Ultrasound – GE • Overall Intraoperative Tracking System using Ultrasound +preop MRI - ????

45. Future Work • Research areas • Better post processing of US images • Newer registration techniques • Faster and effective calibration methods • Bring all individual modules to work as a single system • Testing and evaluation techniques

46. Conclusion A very feasible and highly applicable research area. • Cost effective when compared to I-MRI • Relatively “real time” data • Accuracy from fusion with pre-op MR • Improved surgical outcome • Works in current clinical settings • Adaptable to other surgical procedures involving: • Brain • Breast • Prostate • Others …

47. Thank You!http://ssim.eng.wayne.edu/ssimi/cares/classes/group7/group7.html