Ali K. Hamou, September 2001--June 2003, "Segmentation of
Carotid Artery Ultrasound Images", degree conferred on Autumn
2003 convocation, Computer Science Department, University of
Western Ontario, Canada.
M.Sc. Thesis Abstract
Over the past few years, medical imaging techniques have been
evolving to keep up with the most current technological
developments. A major advance was the arrival of ultrasound
imaging and its uses. Ultrasound provides a non-invasive
means for visualizing various tissues within the human body.
However, these visualizations tend to be filled with speckle
noise and other artifacts, due to the nature of sound waves.
This thesis presents a novel segmentation technique for use
on noisy B-mode ultrasound images of the carotid artery. This
scheme is based on several commonly used image-processing
techniques, such as histogram equalization, Canny edge
detection and morphology. The proposed scheme provides various
degrees of customizability, for a wide range of ultrasound
images. The experimental results show that this scheme
accurately segments the different textures in ultrasound
images. These segmented regions alleviate the need for a
technician's manual segmentation of wanted regions. Moreover,
this technique can be used in conjunction with other schemes
to uncover further details of the carotid artery, (such as
plaque levels and flow).