Download Automatic Segmentation of Coronary Arteries using Hessian

Automatic Segmentation of Coronary Arteries using Hessian-based Multi-Scale Filtering and
Eigenvectors to Track Vessels
Shant Malkasian
Mentors: Benjamin Ziemer, Sabee Molloi
Using diagnostics like Fractional Flow Reserve (FFR) or blood perfusion have become gold standards in
identifying coronary artery disease, the leading cause of death in the United States. As medical imaging has
improved, it is now becoming possible to calculate these diagnostics, using only a Computed Tomography
Angiography (CTA), an X-ray scan that images a patient’s heart in three dimensions. To calculate FFR and
myocardial perfusion from a CTA, it is necessary to segment the coronary arteries out of the CTA image. A
method of coronary artery segmentation has been developed that will utilize a number of specially designed
filters, including a Hessian-based multi-scale filter, in order to yield a three dimensional image of only the
coronary arteries. This image can then be used by array of other diagnostics, like CTA FFR and CTA
myocardial perfusion. I found that CTA images required many steps of processing, prior to applying the
multi-scale filter, in order to properly work. While the current results are promising, there is still much more
work to be done in refining the methods developed this fall. Improvements in implementing this method of
segmentation have been made both in the Hessian-based multi-scale filter and in the processing steps prior to
applying the filter to the CTA images.