International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 163 - Issue 10 |
Published: Apr 2017 |
Authors: Hetvi Pasad, Himani Shetty, Ayushi Malde, Poonam Bhogale |
![]() |
Hetvi Pasad, Himani Shetty, Ayushi Malde, Poonam Bhogale . CAD for Hepatic Tumor Detection in CT Images. International Journal of Computer Applications. 163, 10 (Apr 2017), 14-18. DOI=10.5120/ijca2017913692
@article{ 10.5120/ijca2017913692, author = { Hetvi Pasad,Himani Shetty,Ayushi Malde,Poonam Bhogale }, title = { CAD for Hepatic Tumor Detection in CT Images }, journal = { International Journal of Computer Applications }, year = { 2017 }, volume = { 163 }, number = { 10 }, pages = { 14-18 }, doi = { 10.5120/ijca2017913692 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A Hetvi Pasad %A Himani Shetty %A Ayushi Malde %A Poonam Bhogale %T CAD for Hepatic Tumor Detection in CT Images%T %J International Journal of Computer Applications %V 163 %N 10 %P 14-18 %R 10.5120/ijca2017913692 %I Foundation of Computer Science (FCS), NY, USA
In the abdominal CT scan, the liver region is not clearly discerned from the adjacent organs such as muscle, spleen, and pancreas. The objective of the proposed system is to devise a novel method for tumor identification which helps the medical experts for further diagnosis. The region of interest, namely the liver, is first separated by combining ROIpoly and thresholding methods. On obtaining the liver region, the tumor if present, is extracted using Gray Level Co-occurrence Matrix (GLCM) and Fuzzy C Means (FCM). Further, we have also compared the results obtained from both the methods.