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Automated measurement of single and total lung volume from CT
M S Brown1, M F McNitt-Gray, J G Goldin
1Department of Radiological Sciences, UCLA School of Medicine, Los Angeles, CA 90095-1721, USA.
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.