Artery-vein separation via MRA-An image processing approach

• Published in: IEEE transactions on medical imaging Vol. 20; no. 8; pp. 689 - 703
• Main Authors: Tianhu Lei, Udupa, J.K., Saha, P.K., Odhner, D.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2001; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Angiography; Arteries; Arteries - anatomy & histology; Biological and medical sciences; Blood vessels; Cardiovascular system; Carotid Arteries - anatomy & histology; Computerized, statistical medical data processing and models in biomedicine; Contrast Media; Data visualization; Fuzzy Logic; General aspects. Methods; Humans; Image analysis; Image processing; Image Processing, Computer-Assisted; Image segmentation; Imaging, Three-Dimensional; Investigative techniques, diagnostic techniques (general aspects); Iterative algorithms; Iterative methods; Magnetic resonance; Magnetic Resonance Angiography; Medical sciences; Pelvis - blood supply; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Separation processes; Software packages; Software testing; Studies; Veins; Veins & arteries; Veins - anatomy & histology; Human; Evaluation; 3D imaging; Angiography; Segmentation; Image processing; Venous phase; Cardiovascular disease; Nuclear magnetic resonance imaging; Differential diagnostic; Automated processing; Image quality; Biomedical data processing; Fuzzy algorithm; Arterial time; Contrast threshold; Biomedical engineering
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.938238

Presents a near-automatic process for separating vessels from background and other clutter as well as for separating arteries and veins in contrast-enhanced magnetic resonance angiographic (CE-MRA) image data, and an optimal method for three-dimensional visualization of vascular structures. The separation process utilizes fuzzy connected object delineation principles and algorithms. The first step of this separation process is the segmentation of the entire vessel structure from the background and other clutter via absolute fuzzy connectedness. The second step is to separate artery from vein within this entire vessel structure via iterative relative fuzzy connectedness. After seed voxels are specified inside the artery and vein in the CE-MRA image, the small regions of the bigger aspects of artery and vein are separated in the initial iterations, and further detailed aspects of artery and vein are included in later iterations. At each iteration, the artery and vein compete among themselves to grab membership of each voxel in the vessel structure based on the relative strength of connectedness of the voxel in the artery and vein. This approach has been implemented in a software package for routine use in a clinical setting and tested on 133 CE-MRA studies of the pelvic region and two studies of the carotid system from 6 different hospitals. In all studies, unified parameter settings produced correct artery-vein separation. When compared with manual segmentation/separation, the authors' algorithms were able to separate higher order branches, and therefore produced vastly more details in the segmented vascular structure. The total operator and computer time taken per study is on the average about 4.5 min. To date, this technique seems to be the only image processing approach that can be routinely applied for artery and vein separation.