چکیده (انگلیسی):

Computed Tomography-Angiography (CTA) images of the abdomen, followed by precise segmentation and
subsequent computation of shape based features of liver play an important role in hepatic surgery,
patient/donor diagnosis during liver transplantation and at various treatment stages. Nevertheless, the issues
like intensity similarity and Partial Volume Effect (PVE) between the neighboring organs; left the task of
liver segmentation critical. The accurate segmentation of liver helps the surgeons to perfectly classify the
patients based on their liver anatomy which in turn helps them in the treatment decision phase. In this
study, we propose an effective Advanced Region Growing (ARG) algorithm for segmentation of liver
from CTA images. The performance of the proposed technique was tested with several CTA images
acquired across a wide range of patients. The proposed ARG algorithm identifies the liver regions on
the images based on the statistical features (intensity distribution) and orientation value. The proposed
technique addressed the aforementioned issues and been evaluated both quantitatively and
qualitatively. For quantitative analysis proposed method was compared with manual segmentation
(gold standard). The method was also compared with standard region growing.