Automatic liver segmentation technique for three-dimensional visualization of CT data.

PURPOSE: To develop a system for automatic segmentation of the liver from computed tomographic (CT) scans of the abdomen for three-dimensional volume-rendering displays. MATERIALS AND METHODS: An automated liver segmentation system was developed, which combined domain knowledge with analysis of a global histogram, morphologic operators, and the parametrically deformable contour model. Boundaries of the thresholded liver volume were modified section-by-section by exploiting information from adjacent sections. These boundaries were refined by optimization of the parametrically deformable contour model. Volume-rendered images were created by using the boundaries to exclude tissues outside the liver. The system was tested on CT data sets from 10 cases of potentially resectable hepatic neoplasm. RESULTS: Of the 401 sections in the 10 cases, 53 sections (13.2%) required user modifications during segmentation. The utility of the three-dimensional-rendered images with use of these liver boundaries was judged by a radiologist as being comparable to that of three-dimensional images created with manual editing. Twenty-eight of the sections were deemed imperfect by the radiologist and might need further modifications. CONCLUSION: An effective technique for automatic segmentation of the liver from CT images has been developed. This technique promises to save time and simplify the creation of three-dimensional liver images by minimizing operator intervention.