Title :
Extraction of liver vessel centerlines under guidance of patient-specific models
Author :
Xishi Huang ; Zaheer, Saima ; Abdalbari, A. ; Looi, Thomas ; Jing Ren ; Drake, James
Author_Institution :
Dept. of Med. Imaging, Univ. of Toronto, Toronto, ON, Canada
fDate :
Aug. 28 2012-Sept. 1 2012
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.
Keywords :
biomedical MRI; blood vessels; feature extraction; liver; medical image processing; abdominal organ blood vessel extraction; disease diagnosis quality; extracted vessels; intraprocedural image guidance; liver magnetic resonance images; liver vessel centerline extraction; patient specific model guidance; preprocedural vessels; prior knowledge patient specific models; strain energy; treatment planning; vessel extraction-registration framework; Bifurcation; Biomedical imaging; Blood vessels; Image segmentation; Liver; Planning; Strain; Computer Simulation; Hepatic Artery; Hepatic Veins; Humans; Image Interpretation, Computer-Assisted; Magnetic Resonance Angiography; Models, Cardiovascular; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346434