Ultrasound Analysis Of Vascular Structure And Deformation

Low-power, portable ultrasound imaging devices are well-suited for the diagnostic requirements of healthcare delivery on the modern battlefield. The non-invasiveness and good spatiotemporal resolution of ultrasonography allow for early detection of changes in tissue anatomy and material behavior that signal the presence of injury from exposure to biological hazards or disease processes that can jeopardize the performance of personnel in the field. This potential has not been fully realized however due to the presence of image degrading factors that make ultrasound imagery notoriously difficult to interpret. To detect and quantify tissue pathology from ultrasound, anatomical boundaries and tissue deformation in the images must be estimated accurately; this requires image processing in a way that suppresses noise while retaining salient tissue borders in the imagery. We focus here on detecting abnormalities in cross-sections of the carotid vessel which often exhibits early changes in response to injurious stimuli. We present a novel approach to vessel boundary extraction and deformation tracking over time for the purpose of detecting abnormal tissue characteristics. We validate this concept in noisy simulated images derived from finite-element models of normal and abnormal Vessel cross-sections, and in real ultrasound images from a human subject.