Premium
3D reconstruction of the cerebral arterial network from stereotactic DSA
Author(s) -
Coste Eric,
Vasseur Christian,
Rousseau Jean
Publication year - 1999
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.598682
Subject(s) - imaging phantom , epipolar geometry , computer vision , 3d reconstruction , iterative reconstruction , reconstruction algorithm , computer science , artificial intelligence , algorithm , radiology , medicine , image (mathematics)
The authors present an automatic algorithm for 3D reconstruction of cerebral blood vessels by digital subtracted angiography. The patient is localized by a stereotactic method. The reconstruction algorithm includes two steps: first vessel extraction then 2D matching and reconstruction. Accurate vessel skeletons are generated by a combination of mathematical morphological algorithms and adaptive filters. The 3D reconstruction algorithm is based on the reconstruction of vessels center lines. For that purpose, three different projections of the vascular network are used. Reconstruction is computed segment by segment (a curved line between two nodes). For each segment point, the algorithm defines all epipolar solutions on the other views. These epipolar solutions are sorted and pooled by 2D continuity and 3D proximity criteria resulting in a 3D graph. Optimal 3D segment is defined by a recursive algorithm that looks up the better path in the 3D graph. The algorithms have been implemented on a Compatible‐PC computer in C language. More than 95% of static copper phantom was reconstructed in 5 min and with 1 mm 3D accuracy. 70% of arteries (from carotid to the seventh node) of a true patient arterial network were reconstructed is less than 30 min.