Neural-Network-Based Segmentation of Liver Structure in CT Images for 3-D Visualization

概要

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This paper describes an automated segmentation method of liver structure from abdominal CT images using an artificial neural network (NN), together with a prior information about liver location and area in the abdomen cross section and with digital imaging processing techniques. This approach based on the NN is to classify each pixel on an image into one of three categories: boundary, liver, and non-liver. Supervised training technique is used in our experiments. The training data set is obtained from any one of the given set of images by creating gray level histograms for the three categories. The histograms are considered as the respective feature values. Prior to NN classification, preprocessing is employed to locally enhance the contrast of the region of interest. To evaluate the performance of our method, NN-determined boundaries are compared with those traced by two human experts. Our preliminary results show that the proposed method has potential utility in automated segmentation of liver structure and other organ in the human body.
Medical Imaging and Information Sciencesの論文