A shape-based segmentation algorithm for X-ray digital subtraction angiography images.
We present an efficient algorithm for vessel segmentation of digital subtraction angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By separating vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for some of the parameters used are also reported and discussed.
Franchi
Danilo
D
INFM, c/o Department of Health Sciences, University of L'Aquila, Via Vetoio 10, 67100 Coppito, L'Aquila, Italy.
Gallo
Pasquale
P
Marsili
Luca
L
Placidi
Giuseppe
G
D000465:Algorithms; D015901:Angiography, Digital Subtraction / Q000379:methods*; D016880:Anisotropy; D002533:Cerebral Angiography / Q000379:methods*; D019295:Computational Biology / Q000379:methods; D003287:Contrast Media / Q000494:pharmacology; D005471:Fluoroscopy / Q000379:methods; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008962:Models, Theoretical; D016011:Normal Distribution; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012984:Software; D014965:X-Rays
D003287:Contrast Media