An improved color segmentation algorithm for the analysis of liver anomalies in CT/PET images
Vimtha G. Sekhar, Subbiahpillai Neelakantapillai Kumar, Alfred Lenin Fred, Sebastin Varghese · 2016
This paper is an application of medical image processing. Multimodality medical images are widely used nowadays for disease diagnosis. The CT/PET medical images are used in this paper for the segmentation of liver anomalies. The preprocessing was done by median filter and the segmentation was performed by binary tree quantization algorithm. The binary tree quantization algorithm produces better results than conventional K-means segmentation algorithm. The algorithms was developed in Matlab 2010 and tested on real time CT/PET images of patients with Hepatic Cellular Carcinoma.