Automatic detection method of hepatocellular carcinomas using the non-rigid registration method of multi-phase liver
Jeongjin Lee1, Kyoung Won Kim2, So Yeon Kim2
1School of Computer Science and Engineering, Soongsil University, Dongjak-Gu, Seoul, Korea.
Background:
Multi-phase CT images are obtained sequentially after the injection of contrast agents so that there is a large amount of local deformation between images due to the respiratory and heart motion. Therefore, a non-rigid registration technique is required in order to establish the anatomical correspondence between the multi-phase CT images for liver CAD (computer-aided diagnosis).
Objective:
In this paper, we propose the automatic detection method of hepatocellular carcinomas using the non-rigid registration method of multi-phase CT images.
Methods:
Global movements between multi-phase CT images are aligned by rigid registration based on normalized mutual information. Local deformations between multi-phase CT images are modeled by non-rigid registration based on B-spline deformable model. After the registration of multi-phase CT images, hepatocellular carcinomas are automatically detected by analyzing the original and subtraction information of the registered multi-phase CT images.
Results:
We applied our method to twenty five multi-phase CT datasets. Experimental results showed that the multi-phase CT images were accurately aligned. All of the hepatocellular carcinomas including small size ones in our 25 subjects were accurately detected using our method.
Conclusion:
We conclude that our method is useful for detecting hepatocellular carcinomas.
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
06:09Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Published on: July 21, 2023