Automated measurement of single and total lung volume from CT.
OBJECTIVE
The goal of this work was to develop an automated method for calculating single (SLV) and total (TLV) lung volumes from CT images.


METHODS
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.


CONCLUSIONS
A knowledge-based approach to segmentation of the lungs in CT can be used to automatically estimate SLV and TLV.
Brown
M S
MS
Department of Radiological Sciences, UCLA School of Medicine, Los Angeles, CA 90095-1721, USA.
McNitt-Gray
M F
MF
Goldin
J G
JG
Greaser
L E
LE
Hayward
U M
UM
Sayre
J W
JW
Arid
M K
MK
Aberle
D R
DR
D001185:Artificial Intelligence; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging*; D008176:Lung Volume Measurements; D014057:Tomography, X-Ray Computed