Title :
Automatic Detection and Classification of Liver Lesions from CT-scan Images
Author :
Ria Benny;Tessamma Thomas
Author_Institution :
Dept. of Electron., Cochin Univ. of Sci. &
Abstract :
This paper discusses about a method adopted to develop a computer-aided diagnostic system to achieve automatic detection and classification of liver lesions. The procedure followed consists of first segmenting the CT scan image so as to accurately extract out the lesion region alone from the rest of the abdominal details. This Region Of Interest(ROI) is now used up for extracting out first order and second order statistical feature values, which aids in the correct classification of lesions. The lesions can be classified into five types: normal liver, cysts, abscesses, benign growth (hemangioma, focal nodular hyperplasia, hepatocellular adenoma etc) and malignant growth (Hepatocellular Carcinoma, metastases etc), and this paper discusses a robust method for correctly identifying and classifying these lesions of the liver.
Keywords :
"Lesions","Liver","Feature extraction","Image segmentation","Computed tomography","Cancer"
Conference_Titel :
Advances in Computing and Communications (ICACC), 2015 Fifth International Conference on
Print_ISBN :
978-1-4673-6993-0
DOI :
10.1109/ICACC.2015.46