Liver Tumor Volume Estimation By Semi-Automatic Segmentation Method

Abstract

Liver cancer is one of the most popular cancer diseases and causes a large amount of death every year. In order to make decisions such as liver resections, doctors will need to know the tumor volume, and further, the functional liver volume. Thus, an important task in radiology is the determination of tumor volume. Accurate segmentation of liver tumor from an abdominal image is one of the most important steps in 3D representation for liver volume measurement, liver transplant, and treatment planning[1]. Since manual segmenation is inconvenient, time consuming and depends on the individual operator to a large extent, automatic segmentation is much more preferred. In this paper, an active contour model is used to segment tumors from CT abdominal images. Initial boundary is manually placed by operators outside the tumor region. The snake deforms to the tumor boundary with the minimization of energy function. We then calculate the tumor volume using the series of segmented tumor slices. Results show that this method is quite efficient in tumor volume estimation compared with the WHO criteria, which measures the tumor by multiplying the longest perpendicular diameters.

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