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Three-dimensional semiautomatic liver segmentation method for non-contrast computed tomography based on a correlation
Satoshi Yamaguchi1, Koji Satake2, Yoshio Yamaji2
1Department of Biomaterials Science, Osaka University Graduate School of Dentistry, 1-8 Yamadaoka, Suita, Osaka 565-0871, Japan.
Background:
We sought to evaluate a new regional segmentation method for use with three-dimensional (3D) non-contrast abdominal CT images and to report the preliminary results.
Methods:
The proposed method was evaluated in ten cases. Manually segmented areas were used as the gold standard for evaluation. To compare the standard and the extracted liver regions, the degree of coincidence R% was redefined by transforming a volumetric overlap error. We also evaluated the influence of varying the density window size in terms of setting the starting points.
Results:
We confirmed in ten cases that our method could segment the liver region more precisely than the conventional method. A size of window 15 voxels was optimal as the starting point in all cases.
Conclusions:
We demonstrated the accuracy of a 3D semiautomatic liver segmentation method for non-contrast CT. This method promises to offer radiologists a time-efficient segmentation aid.
