Purpose: The goal of this work was to develop an automated method for calculating 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 image data that were identified by matching them to anatomical objects defined 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 can be used to automatically estimate SLV and TLV.