The rescale intercept and slope are applied to transform the pixel values of the image into values that are meaningful to the application.
For instance, the original pixel values could store a device specific value that has a meaning only when used by the device that generated it: applying the rescale slope/intercept to pixel value converts the original values into optical density or other known measurement units (e.g. hounsfield).
When the transformation is not linear, then a LUT (lookup table) is applied.
After the modality transform has been applied (rescale slope/intercept or LUT) then the window width/center specify which pixels should be visible: all the pixels outside the values specified by the window are displayed as black or white.
For instance, if the window center is 100 and the window width is 20 then all the pixels with a value smaller than 90 are displayed as black and all the pixels with a value bigger than 110 are displayed as white.
This allow to display only portions of the images (for instance just the bones or just the tissues).
Hounsfield scale: http://en.wikipedia.org/wiki/Hounsfield_scale
How to apply the rescale slope/intercept:
final_value = original_value * rescale_slope + rescale_intercept
How to calculate the pixels to display using the window center/width:
- lowest_visible_value = window_center - window_width / 2
- highest_visible_value = window_center + window_width / 2
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