Obesity has become widespread in America and has been associated as a risk factor for many illnesses. Adipose tissue (AT) content, especially visceral AT (VAT), is an important indicator for risks of many disorders, including heart disease and diabetes. Measuring adipose tissue (AT) with traditional means is often unreliable and inaccurate. CT provides a means to measure AT accurately and consistently. We present a fully automated method to segment and measure abdominal AT in CT. Our method integrates image preprocessing which attempts to correct for image artifacts and inhomogeneities. We use fuzzy cmeans to cluster AT regions and active contour models to separate subcutaneous and visceral AT. We tested our method on 50 abdominal CT scans and evaluated the correlations between several measurements.