@inproceedings{ae6bb8ef291342e18973333f94543ef6,
title = "A structural saliency-based approach for automatic intrahepatic vascular separation from contrast-enhanced multi-phase MR images",
abstract = "Intrahepatic vascular separation on contrast-enhanced Magnetic Resonance (MR) images is indispensable for the hepatic tumor surgery. This paper presents an unsupervised frame-work based on structural saliency for automatically separating portal vein (PV) and hepatic vein (HV) from contrast-enhanced multi-phase MR images. In our work, we propose a new multi-scale filter based on statistics and shape information in the region of interest, called SSIROI, with which the vascular connectivity and saliency in the 3D hepatic region can be guaranteed. Experiments are conducted on clinical contrast-enhanced MR images, and the results show that our method achieves effective separation of intrahepatic vasculature by extracting the PV and HV from multi-phase images, and our proposed SSIROI filter outperforms state-of-the-art methods.",
keywords = "Contrast-enhanced MR images, Intrahepatic vascular separation, Multi-phase images, Multi-scale filter, Structural saliency",
author = "Qing Guo and Hong Song and Jingfan Fan and Danni Ai and Jian Yang and Yuanjin Gao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 ; Conference date: 13-04-2021 Through 16-04-2021",
year = "2021",
month = apr,
day = "13",
doi = "10.1109/ISBI48211.2021.9433995",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "1686--1690",
booktitle = "2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021",
address = "United States",
}