Presented here is a modification of a previously developed, computed, semiautomated system for quantifying the amount of CSF and tissue on brain CT scans. The technique automatically strips skull from brain and applies a two-dimensional high-pass filter to reduce spectral-shift artifact. The resultant images are presented along with the raw images, section by section, on a screen for fluid-tissue differentiation by a human scorer. This is accomplished by adjusting a one-bit display of the filtered image until a satisfactory separation threshold is found. Data can be summed within or across sections to provide measures of CSF volume in specific regions of interest such as the ventricles and sulci. A major advantage is the improved accuracy of sulcal measurement. This method has been applied to scans of 57 community volunteers, 20-84 years old. High correlations have been established between rankings performed by an experienced clinician and automated rankings (r = 0.88 with rankings based on ventricular size, and r = 0.83 with rankings based on sulcal size). Furthermore, significant correlations were found between computed measures of ventricular size and age and between sulcal widening and age.