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Enhancing Detail Visibility in Digital Subtraction Angiography: Methods and Techniques

Learn about digital image processing, adjusting contrast, controlling window settings, and various methods for image subtraction in DSA. Explore LUT, curve selection, computed radiography, and the importance of subtraction for improving image clarity.

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Enhancing Detail Visibility in Digital Subtraction Angiography: Methods and Techniques

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  1. and Digital Image Processing Digital Subtraction Angiography

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

  3. 1 2

  4. LUT Curve

  5. Curve Selection of

  6. Enhancing Visibility of Detail

  7. Digital Subtraction Angiography DSA

  8. Computed radiography

  9. The need for subtraction

  10. Subtraction for improvement in conspicuity

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

  12. Mask image Live image Live-Mask

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

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

  15. Temporal subtraction(Time-dependent)

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

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

  18. Dual energy subtraction

  19. Dual energy subtraction Compton/Photoelectric decomposition

  20. 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

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

  22. 3. Hybrid subtraction Temporal subtraction + Energy subtraction

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

  24. 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

  25. 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.

  26. Low-pass digital spatial filtering(Smoothing)

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

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

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

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

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

  32. Pixel registration to reduce motion artifacts

  33. 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

  34. 3.1. Time -interval difference subtraction

  35. 3.2. Integration Pre-contrast and post-contrast images are summated(integrated) to reduce noise

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

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