A pleural effusion is a condition where there is a buildup of abnormal fluid within the pleural space. This paper presents an automated method to evaluate the severity of pleural effusion using regular chest CT images. First the lungs are segmented using region growing, mathematical morphology and anatomical knowledge. Then the visceral and parietal layers of the pleura are extracted based on anatomical landmarks, curve fitting and active contour models. Finally, the pleural space is segmented and the pleural effusion is quantified. Our method was tested on 15 chest CT studies. The automated segmentation is validated against manual tracing and radiologist's qualitative grading. The Pearson correlation between computer evaluation and radiologist's grading is 0.956 (P=10(-7)). The Dice coefficient between the automated and manual segmentation is 0.74±0.07, which is comparable to the variation between two different manual tracings.