Abstract
The display of computerized tomographic (CT) data requires data compression because of the limited shades of grey which the eye can differentiate. This may lead to information loss which can be minimized by a more efficient utilization of the available levels of grey than that afforded by conventional linear windows. Automated histogram equalization for grey level assignment has not been satisfactory because of the underlying assumption that the information content at any given CT level is proportional to the number of pixels at that level. For four different anatomic regions; the lumber spine, abdomen, brain and chest, an empiric graph of the clinical information content vs CT levels was integrated to yield the shape of a graph assigning shades of grey vs CT level i.e. a non-linear window. This non-linear window curve was utilized in the same manner as the linear window, namely the window center and width were under the direct control of the observer through the window center and width knobs. Each non-linear window was implemented on images of its anatomic region and interactively optimized on the screen till a maximal display of information was obtained. These optimal non-linear windows compared favorably with linear windows in most cases. This method provides the means to display more information on a CT image with no extra processing time, additional equipment or special training.
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