Segmentation Research of Abdominal Liver CT Images for Cancer and Other Disease Lesion Detection

Biomedical images are to be analyzed accurately for disease detection and diagnosis. Image segmentation is one of the most important and widely used methods in image processing and computer-based image analysis. In this chapter, various image-processing techniques are briefly explained and directly implemented for separating benign and malignant liver tumors. Different classical and relatively new techniques are used for segmenting biomedical images and the results are shown. Here an effort is made to bring out clinical information from liver images of computed tomography based on image processing and computer-aided diagnosis. Finally, liver tumor classification has been performed using texture-based image analysis techniques. Encouraging results are obtained with considerable classification accuracy (97.3%) and negligible misclassification rate.