Segmentation with gray‐scale connectedness can separate arteries and veins in MRA

Abstract

Purpose:To describe and present some preliminary results for a novel algorithm for segmentation with gray-scale connectedness as a means to separate arteries and veins in magnetic resonance angiography (MRA). Materials and Methods:The proposed algorithm, SeparaSeed, uses the gray-scale degree of connectedness as a tool to find the zone surrounding each vessel, in order to split the original volume into its different vessel components. In contrast to traditional segmentation methods, no gray-scale information is lost in the process. The segmentation is performed in one step, resulting in a partition of the initial volume into a chosen number of regions of interest (ROIs). Finally, visualization is achieved by projecting the 3D vessel trees to 2D using the common maximum intensity projection (MIP). The algorithm was tested in two MRA data sets of the vessels of the pelvis acquired after injection of an intravascular contrast agent and in one data set of the vessels of the neck with gadolinium. Results:In all data sets, a large proportion of the venous signal was removed while preserving that of the arteries, thus improving visualization of the relevant vessels. Conclusion:Separation of arteries and veins is feasible with the proposed algorithm with a moderate amount of interaction.

Double‐reference cross‐correlation algorithm for separation of the arteries and veins from 3D MRA time series

“…Another approach for artery/vein segmentation is based on different types of connectivity algorithms (13)(14)(15)(17)(18)(19)22), which utilizes a high-resolution dataset to segment out the arteries and veins. It exploits the geometrical characteristics of the arterial and venous vessel trees, comparing the brightness of every voxel with its neighbors and thus deciding whether they belong to the same structure or not.…”

“…Different postprocessing strategies have been proposed to deal with this task (12)(13)(14)(15)(16)(17)(18)(19). The most commonly applied is the simple subtraction of the arterial datasets from venous datasets.…”

Integrating automatic and interactive methods for coronary artery segmentation: let the PACS workstation think ahead

“…Building on our earlier work on "virtual contrast injection" visualization [5][6][7], this paper presents a quantitative coronary CTA analysis tool, built on the open-source PACS workstation software OsiriX [8], which integrates both fully automatic and interactive methods for coronary artery extraction. The computational power of an ordinary PC is exploited by running the non-supervised coronary artery segmentation and centerline tracking in the background as soon as the images are received.…”

Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree

“…Interactive approaches may solve part of this problem but can be very time-consuming. The concept of fuzzy connectedness (greyscale connectedness), which has been proposed to separate arteries and veins in Magnetic resonance angiography (MRA) [5][6][7], shows great ability to separate two contrastfilled structures from each other. A previous feasibility study showed that this approach can be applied to 3D CTA data to separate the coronary arteries from other contrast-filled structures and thus permit coronary artery visualization in an angiographic mode similar to invasive X-ray angiography [8].…”

“…In addition to overcoming several problems of former algorithms [5][6][7], the new algorithm includes automated extraction of the vessel centerline, which is useful, e.g., for creating CPR images.…”