Open AccessLiver Segmentation Techniques of CT Images for Clinical Diagnosis
Author(s) -
Anusha Linda Kostka. J. E*,
S. Vinila Jinny
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a4157.119119
Subject(s) - segmentation , artificial intelligence , computer science , robustness (evolution) , scale space segmentation , computer vision , image segmentation , pattern recognition (psychology) , feature (linguistics) , segmentation based object categorization , biology , biochemistry , linguistics , philosophy , gene
Liver Segmentation has become one of the most efficient and systematic tasks in the case of medical applications. Recently, the segmentation of liver has found its part in the research areas also. It has become a common feature to hinder the accurate and the proper segmentation of the liver intensities and its neighbor organs in the human body. Different techniques of liver segmentation can be performed with CT images, MRI images and PET. Among these CT images have a wide application in the detection, identification and segmentation of the liver deficiencies. Manual segmentation of the liver seems to be more time consuming yielding less precision and robustness. Nowadays, many techniques have been developed for the segmentation of liver that are more efficient, fast with accurate as well as better results than the traditional methods.