Jeongjin Lee1, Kyoung Won Kim2, So Yeon Kim2, Juneseuk Shin3, Kyung Jun Park1, Hyung Jin Won2, Yong Moon Shin2. 1. School of Computer Science and Engineering, Soongsil University, Dongjak-Gu, Seoul, Korea. 2. Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Songpa-ku, Seoul, Korea. 3. Department of Systems Management Engineering, Sungkyunkwan University, Seobu-ro, Jangan-gu, Suwon-si, Gyeong gi-do, Korea.
Abstract
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.
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.