Automatic 3D segmentation of intravascular ultrasound images using region and contour information.
Intravascular ultrasound (IVUS) produces images of arteries that show the lumen in addition to the layered structure of the vessel wall. A new automatic 3D IVUS fast-marching segmentation model is presented. The method is based on a combination of region and contour information, namely the gray level probability density functions (PDFs) of the vessel structures and the image gradient. Accurate results were obtained on in-vivo and simulated data with average point to point distances between detected vessel wall boundaries and validation contours below 0.105 mm. Moreover, Hausdorff distances (that represent the worst point to point variations) resulted in values below 0.344 mm, which demonstrate the potential of combining region and contour information in a fast-marching scheme for 3D automatic IVUS image processing.
Cardinal
Marie-Hélène Roy
MH
Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital, Canada. roycarmh@iro.umontreal.ca
Meunier
Jean
J
Soulez
Gilles
G
Maurice
Roch L
RL
Thérasse
Eric
E
Cloutier
Guy
G