Two methods for isolating the lung area of a CT scan for density information.

Extracting density information from irregularly shaped tissue areas of CT scans requires automated methods when many scans are involved. We describe two computer methods that automatically isolate the lung area of a CT scan. Each starts from a single, operator specified point in the lung. The first method follows the steep density gradient boundary between lung and adjacent tissues; this tracking method is useful for estimating the overall density and total area of lung in a scan because all pixels within the lung area are available for statistical sampling. The second method finds all contiguous pixels of lung that are within the CT number range of air to water and are not a part of strong density gradient edges; this method is useful for estimating density and area of the lung parenchyma. Structures within the lung area that are surrounded by strong density gradient edges, such as large blood vessels, airways and nodules, are excluded from the lung sample while lung areas with diffuse borders, such as an area of mild or moderate edema, are retained. Both methods were tested on scans from an animal model of pulmonary edema and were found to be effective in isolating normal and diseased lungs. These methods are also suitable for isolating other organ areas of CT scans that are bounded by density gradient edges.