This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.
A new computerized imaging, circular polarized light microscopy technique is de veloped to measure the orientation of fibers in images of nonwovens. The system consists of a modified Olympus BX50 polarized microscope, a Sony AVC-D7 video camera, and a Silicon Graphics Indy computer. There are two methods of image seg mentation : Gaussian distribution' based minimum error thresholding and Poisson dis tribution based minimum error thresholding. Segments of fiber midlines are traced with vertical and horizontal scanlines or, alternatively, whole midlines are identified recur sively with the Hilditch technique. The fiber midlines produced with this technique are traversed by a midline traversal algorithm, and the orientation distribution is obtained by least squares line fitting. The accuracy of the technique is evaluated against synthetic images composed of straight lines and sinuous curves. Kupier's statistic is used to evaluate the consistency of the fiber orientation calculations. A statistical analysis of the results shows that the proposed Hilditch connectivity, which preserves skeletoni zation, produces the most accurate results.
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