CalibrateDSX: The Importance of Image Smoothing and Downsampling
...work in progress...
DRR-based tracking of bones in X-ray images relies heavily on the brightness of the bones' edges in the edge-detected images. Smoothing and/or resizing the images during correction increases their signal-to-noise ratio, resulting in brighter edges. Some amount of smoothing or resizing is almost always needed to maximize the trackability of the bones.
Example: Knee
These images were captured at the Biodynamics Lab at the University of Pittsburgh. They are 14-bit grayscale with a resolution of 1824x1800 pixels.
Left: Original image Right: Edge-detected
Left: Smoothed (5x5 kernel, sigma = 2.0) Right: Resized (scaled by 0.5 to 912x900)
Smoothed (5x5 kernel, sigma = 2.0) and resized (scaled by 0.5 to 912x900)
Example: Cervical Spine
These images were captured at the Biodynamics Lab at the University of Pittsburgh. They are 14-bit grayscale with a resolution of 1824x1800 pixels.
Left: Original image Right: Edge-detected
Left: Smoothed (5x5 kernel, sigma = 2.0) Right: Resized (scaled by 0.5 to 912x900)
Smoothed (5x5 kernel, sigma = 2.0) and resized (scaled by 0.5 to 912x900)
Example: LumbarSpine
These images were captured at the Biodynamics Lab at the University of Pittsburgh. They are 14-bit grayscale with a resolution of 1824x1800 pixels.
Left: Original image Right: Edge-detected
Left: Smoothed (7x7 kernel, sigma = 4.0) Right: Resized (scaled by 0.33 to 608x600)
Smoothed (7x7 kernel, sigma = 4.0) and resized (scaled by 0.33 to 608x600)
