Related Experiment Video
Updated: Jun 10, 2026

Successful Orthotopic Liver Transplantation in Mice Utilizing Microcomputed Tomography Angiography
Published on: September 22, 2023
Application of a medical image processing system in liver transplantation
Chi-Hua Fang1, Xiao-Feng Li, Zhou Li
1Department of Hepatobiliary Surgery, Zhujiang Hospital of Southern Medical University, Guangzhou, China. fangch_dr@126.com
Background:
At present, imaging is used not only to show the form of images, but also to make three-dimensional (3D) reconstructions and visual simulations based on original data to guide clinical surgery. This study aimed to assess the use of a medical image-processing system in liver transplantation surgery.
Methods:
The data of abdominal 64-slice spiral CT scan were collected from 200 healthy volunteers and 37 liver cancer patients in terms of hepatic arterial phase, portal phase, and hepatic venous phase. A 3D model of abdominal blood vessels including the abdominal aorta system, portal vein system, and inferior vena cava system was reconstructed by an abdominal image processing system to identify vascular variations. Then, a 3D model of the liver was reconstructed in terms of hepatic segmentation and liver volume was calculated. The FreeForm modeling system with a PHANTOM force feedback device was used to simulate the real liver transplantation environment, in which the total process of liver transplantation was completed.
Results:
The reconstructed model of the abdominal blood vessels and the liver was clearly demonstrated to be three-dimensionally consistent with the anatomy of the liver, in which the variations of abdominal blood vessels were identified and liver segmentation was performed digitally. In the model, liver transplantation was simulated subsequently, and different modus operandi were selected successfully.
Conclusion:
The digitized medical image processing system may be valuable for liver transplantation.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
08:41Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
Published on: March 24, 2023