Digital Image Processing

1. and Digital Image Processing Digital Subtraction Angiography

2. วัตถุประสงค์ • อธิบายขบวนการประมวลผลภาพดิจิตอลได้ • อธิบายวิธีการปรับคอนทราสของภาพดิจิตอลได้ • อธิบายการทำงานและควบคุม window ของภาพรังสีดิจิตอลได้ • อธิบายวิธีการทำ Subtraction ภาพด้วยวิธีต่างๆ ได้

5. 1 2

8. LUT Curve

9. Curve Selection of

16. Enhancing Visibility of Detail

20. Digital Subtraction Angiography DSA

21. Computed radiography

22. The need for subtraction

23. Subtraction for improvement in conspicuity

24. Mask image Live image Mask-Live (original) (original+ contrast media)

25. Mask image Live image Live-Mask

26. Image processing with Java ให้นักศึกษาใช้ โปรแกรมนี้ในการทำ Digital Subtraction ftp://rsbweb.nih.gov/pub/image-j/win32/

27. Subtraction methods 1. Depth 2. Energy 3. Time

28. Temporal subtraction(Time-dependent)

29. Temporal subtraction 1. Pre-contrast images (mask images) 2. Post-contrast images (live images) 3. Subtraction of mask from live images

30. 2. Energy subtraction Energy dependence of x-ray attenuation of difference tissue

31. Dual energy subtraction

32. Dual energy subtraction Compton/Photoelectric decomposition

33. 1. Provide selective cancellation 2. Fast , in millisecond, minimized motion interference 1. More complex 2. More sensitive to scatter radiation 3.Impossible to remove soft-tissue and bone simultaneously Advantage/ Disadvantage

34. Dual energy subtraction images Soft-tissue removed Bone removed

35. 3. Hybrid subtraction Temporal subtraction + Energy subtraction

37. Image processing 1. Spatial filtering 2. Pixel shifting operation 3. Temporal filtering 4. Intensity transformations 5. Window/Level techniques 6. Parametric imaging

38. Spatial filtering is a method of selectively enhancing or diminishing specific spatial frequency components in an image 1. Spatial filtering Diagram of two-dimensional digital spatial filtering

39. Methods Low-pass filtering High-pass filtering Median filtering Digital filtering(Convolution) Each pixel in the processed images is derived from a set of pixels in the original image as determined by the mask.

40. Low-pass digital spatial filtering(Smoothing)

41. High-pass digital spatial filtering (Edge enhancement)

42. Filtered images Original High-pass (Edge enhancement) Low-pass Smoothing

43. Median filtering Mask = Median value of the appropriate 9 pixels in the original image

44. Median filtering images Digital chest radiograph with unwanted dot artifacts After application of 3x1 medial filter to remove dots

45. 2. Pixel shifting operation • Rotation • Translation • Magnification • Minification

46. Pixel registration to reduce motion artifacts

47. 3. Temporal filtering 1. Time interval difference(TID) 2. Integration 3. Blurred mask temporal subtraction 4. Recursive filtering (real time methods) Generalized temporal filtering diagram

48. 3.1. Time -interval difference subtraction

49. 3.2. Integration Pre-contrast and post-contrast images are summated(integrated) to reduce noise

50. Single pre-contrast image Single post-contrast images 8 pre-contrast image 8 post-contrast image Image integration