Automated measurement of single and total lung volume from CT

Purpose: The goal of this work was to develop an automated method for calcu lating single (SLV) and total (TLV) lung volumes from CT images. Method: Patients underwent volumetric CT scanning through the entire chest in a single breath-hold, as well as pulmonary function tests. An automated, knowledge-based system was developed to segment the lungs in the CT images . Image-processing routines were used to extract sets of voxels from the im age data that were identified by matching them to anatomical objects define d in a model. SLV and TLV were calculated by summing included voxels. Results: For 43 patients analyzed, TLV from CT and total lung capacity from body plethysmography were strongly correlated (r = 0.90). On average, the CT-derived volume of the left lung accounted for 47.2% of the total. Conclusion: A knowledge-based approach to segmentation of the lungs in CT c an be used to automatically estimate SLV and TLV.