Call for Papers
About the Journal
Editorial Board
Publication Ethics
Instructions for Authors
Announcements
Current Issue
Back Issues
Search for Articles
Categories
Back Issues
 

JCSE, vol. 17, no. 3, pp.117-126, September, 2023

DOI: http://dx.doi.org/10.5626/JCSE.2023.17.3.117

Segmentation and Rigid Registration of Liver Dynamic Computed Tomography Images for Diagnostic Assessment of Fatty Liver Disease

Kyoyeong Koo, Jeongjin Lee, Jiwon Hwang, Taeyong Park, Heeryeol Jeong, Seungwoo Khang, Jongmyoung Lee, Hyuk Kwon, Seungwon Na, Sunyoung Lee, Kyoung Won Kim, and Kyung Won Kim
School of Computer Science and Engineering, Soongsil University, Seoul, Korea Hanwha Vision Co., Ltd., Seongnam, Korea Department of Biomedical Informatics, Hallym University Medical Center, Anyang, Korea School of Computer Science and Engineering, Soongsil University, Seoul, Korea SKIA Inc., Seoul, Korea Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

Abstract: This study presents a method for diagnosing fatty liver disease by using time-difference liver computed tomography (CT) images of the same patient to perform segmentation and rigid registration on liver regions, excluding the vascular regions. The proposed method comprises three main steps. First, the liver region is segmented in the precontrast phase, and the liver and liver vessel regions are segmented in the portal phase. Second, rigid registration is performed between the liver regions to align the liver positions affected by the patient's posture or breathing. Finally, fatty liver diagnosis is performed with the average Hounsfield unit (HU) value calculated using only the area removed from the vessel area segmented in the portal phase after registration in the precontrast liver area. The mean distance error between the points corresponding to the liver boundary was 3.136 mm and the mean error between the anatomic landmarks was 4.166 mm. A fatty liver diagnosis was confirmed in a total of 18 cases, and the results were identical to the histology results. This technique may be valuable in clinically diagnosing fatty liver using liver CT imaging, which is widely available and more commonly used than abdominal magnetic resonance.

Keyword: Fatty liver; Liver CT imaging; Segmentation; Rigid registration; Diagnosis

Full Paper:   42 Downloads, 409 View

 
 
ⓒ Copyright 2010 KIISE – All Rights Reserved.    
Korean Institute of Information Scientists and Engineers (KIISE)   #401 Meorijae Bldg., 984-1 Bangbae 3-dong, Seo-cho-gu, Seoul 137-849, Korea
Phone: +82-2-588-9240    Fax: +82-2-521-1352    Homepage: http://jcse.kiise.org    Email: office@kiise.org