A 3D image processing algorithm for separating vessels in datasets from Magnetic Resonance Angiography (MRA) and Computed Tomography Angiography (CTA) has been developed and tested on clinical MRA data. Relevant and irrelevant vessels are marked interactively by the user. The algorithm them processes the data, ideally yielding a 3D dataset representing only vessels of interest, while removing other structures. The result is projected to 2D images for visualization. In contrast to traditional segmentation methods, little greyscale information is lost in the process, and the amount of interaction required is relatively small. The classification of voxels utilizes a novel greyscale connectivity measure. A comparison based on the greyscale connectivity values with marked regions is made to decide whether a voxel is of interest for visualization or not. In the projection, those voxels are excluded where the connectivity value is smaller for the relevant vascular structure than for the irrelevant ones. In cases of ambiguity, morphological operations applied to unambiguously classified regions may be used as an additional criterium. In the implementation of the connectivity computation, an iterative propagation scheme is used, similar to that used in chamfer algorithms for distance transforms.

Date Published: 26 May 1999
PDF: 8 pages
Proc. SPIE 3658, Medical Imaging 1999: Image Display, (26 May 1999); doi: 10.1117/12.349432

Published in SPIE Proceedings Vol. 3658:
Medical Imaging 1999: Image Display
Seong Ki Mun; Yongmin Kim, Editor(s)