We describe methods to extract, measure and visualize three-dimensional shapes from Intracoronary Ultrasound (IVUS) videos recorded in vivo, with image segmentation for lumen and intima thickening, and functional model recovery from...
moreWe describe methods to extract, measure and visualize three-dimensional shapes from
Intracoronary Ultrasound (IVUS) videos recorded in vivo, with image segmentation for
lumen and intima thickening, and functional model recovery from discrete representations,
with IVUS video segmentation, probe motion recovery, and verification and applications
of all the methods.
We have developed a novel time-variant shape extration method that is based on the
principle of IVUS video formation and heart vessel phasic motion. We have demonstrated
that image distance, computed by multiresolution approach, is an efficient and reliable way
to recover phase information directly from cardiac IVUS image sequences. The reconstruction
is fully automatic and takes linear time with respect to the number of frames. It is a robust
approach and had been successfully applied to low-image-quality digitized videos. The
recovered shapes not only show strong visual coherence but also detailed phasic changes of
important anatomical and physiological structures. The recovered three-dimensional model
is properly aligned by three-dimensional registration techniques.
Biomechanical studies such as stress analysis require a smoothmodel. For this, we have
introduced a new functional model recovery method that computes an implicit polynomial
representation from any discrete pointset input. This new minimal description length based
model is both stable and repeatable.
We have developed a shortest path segmentation algorithm that is based on line-integral
edge weight. We have shown that this algorithm performs well for extracting a global optimal
path for a curved area of interest from speckle images. We apply the algorithm to
IVUS videos to analyze the time-dependency of the morphological characteristics of epicardial
arteries. We guide the video segmentation process with an automatically-computed
segmentation graph. Using this, we have achieved significant performance gain over traditional
video segmentation algorithms, and obtaining vessel lumen contours that match well
with those traced by an expert.
This system has been applied to animal studies, to visualize and measure intima thickness
and lumen areas in response to acute mean arterial pressure changes, and to track
changes of vessel size and intima thickening for a period of over 15 months.