Paper Title
Automated Segmentation Of Liver And Tumourand Feature Extraction From Abdominal Ct Images Using Region Growing Method

Accurate liver and tumour segmentation on computed Tomography is a challenging task, due to the high-intensity similarity between liver tissues and nearby organs of liver, different shapes of the liver, and presence of severe pathologies. This paper presents automated method to segment liver and tumour from abdominal CT scans and liver tumour features to classify into two benign and malignant tumour. First, the CT images are pre-processed by Gaussian filter to remove noise from the image. Then the liver is segmented using region growing method and then post-processing is done by morphological operations. The tumour is segmented from Liver image by performing thresholding operations. In this method, the tumour burden is computed to monitor the evolution of disease. After tumour burden analysis, tumour feature is calculated to classify into benign and malignant tumour