NDLI: Extraction of liver vessel centerlines under guidance of patient-specific models

Content Provider	IEEE Xplore Digital Library
Author	Xishi Huang Zaheer, S. Abdalbari, A. Looi, T. Jing Ren Drake, J.
Copyright Year	2012
Description	Author affiliation: CIGITI, Hosp. for Sick Children, Toronto, ON, Canada (Zaheer, S.; Looi, T.; Drake, J.) \|\| Fac. of Eng. & Appl. Sci., Univ. of Ontario Inst. of Technol., Oshawa, ON, Canada (Abdalbari, A.; Jing Ren) \|\| Dept. of Med. Imaging, Univ. of Toronto, Toronto, ON, Canada (Xishi Huang)
Abstract	Fast extraction of blood vessels of abdominal organs is still a challenging task especially in intra-procedural treatments due to large tissue deformation. In this study, we propose a novel joint vessel extraction and registration framework. This vessel extraction technique is under the guidance of prior knowledge patient specific models. The proposed technique automatically provides correspondence between extracted vessels and pre-procedural vessels, which is important for image guidance such as labeled vessels from pre-procedural models, improves the quality of disease diagnosis using multiple images and follow-up, and provides important information for nonrigid image registration. Another key component in our framework is to dynamically update mapped pre-procedural models by rapidly registering the patient model to the current image based on strain energy, point marks and 3D extracted vessels currently available. We have demonstrated the effectiveness of our technique in extraction of vessels from liver MR images. Validation shows a extraction error of 3.99 mm. This technique has the potential to significantly improve the quality of intra-procedural image guidance, diagnosis of disease and treatment planning.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	2347
Ending Page	2350
File Size	553843
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346434
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Biomedical imaging Liver Strain Bifurcation Blood vessels Planning
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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