Abstract: A method for the automated segmentation of in vivo image data is disclosed. A region of carotid artery in a number of patients was imaged using MRI. Histological data for each imaged region was then obtained, identifying various atherosclerotic plaque components in the imaged region. A portion of the histological data, and the image data, was used to generate PDFs based on image intensity, and on morphological data (local wall thickness and distance from lumen). The remaining data was used to validate the method. A plurality of MRI images were taken at various weightings, and the images were registered and normalized. The lumen and outer wall boundary were identified. The PDFs were combined in a Bayesian analysis with the intensity and morphological data to calculate the likelihood that each pixel corresponded to each of four plaque components. A contour algorithm was applied to generate contours segmenting the images by composition.

Abstract: A method and system for in-vivo characterization of lesion feature is disclosed. Using a non-invasive medical imaging apparatus, an image of an interior region of a patient's body is obtained. The interior region may include lesion feature (such as plaques) components from a list of components. The lesion feature components are identified by classifying each point in the image as either corresponding to one of the lesion feature components in the list of components or not, using image intensity information and image morphology information, a first relationship (such as an intensity score) correlating image intensity information with the components in the list of components and a second relationship (such as a morphology score) correlating image morphology information with the components in the list of components. Further, a variety of lesion feature characteristics is derived from the result of the classification.

Abstract: A conditional active shape model wherein a training set of images of objects in a class of objects to be identified, such as vascular cross-sections, is supplemented with training observations of at least one second characteristic of the object. A conditional mean shape of the objects is calculated, conditioned on the second characteristic, thereby reducing the size of the probable search space for the shape. A conditional covariance matrix of the shapes is calculated, conditioned on the second characteristic, and the eigenvectors of the conditional covariance matrix corresponding to largest eigenvalues are calculated. The conditional mean shape, and the eigenvalues and eigenvectors of the conditional covariance matrix are then used in an active shape model to identify the shapes of objects in subsequent images.

Abstract: A novel technique directed toward risk assessment of a patient's plaque vulnerability, wherein clinical events may be caused by internal plaque components affecting a lumen within an artery. A surface area projection or shadow of one or more plaque components onto a lumen can be measured and assessed. Optionally, a total volume projection onto the lumen can also be measured and assessed to refine the determination of risk to a patient and to monitor the progression of atherosclerosis over time.

Abstract: A method for characterizing the risk associated with atherosclerosis is disclosed. The method uses one or more images of cross-sections of the artery or other vessel of interest to identify and locate components of the atherosclerotic deposit, including any hemorrhage, necrotic core, and calcification, and to determine the status and composition of the fibrous cap. In one embodiment, high resolution MRI images are utilized, although other imaging modalities may alternatively be used. A simple scoring system is applied that accounts for the presence of these components and more heavily weights the presence of these components in the juxtaluminal portion of the deposit. The status of the fibrous cap (intact or ruptured) and the composition of the fibrous cap (collagen or mixed tissue) are also incorporated into a final atherosclerosis risk score.

Abstract: A method for the automated segmentation of in vivo image data is disclosed. A region of carotid artery in a number of patients was imaged using MRI. Histological data for each imaged region was then obtained, identifying various atherosclerotic plaque components in the imaged region. A portion of the histological data, and the image data, was used to generate PDFs based on image intensity, and on morphological data (local wall thickness and distance from lumen). The remaining data was used to validate the method. A plurality of MRI images were taken at various weightings, and the images were registered and normalized. The lumen and outer wall boundary were identified. The PDFs were combined in a Bayesian analysis with the intensity and morphological data to calculate the likelihood that each pixel corresponded to each of four plaque components. A contour algorithm was applied to generate contours segmenting the images by composition.

Abstract: Apparatus for removal of flash from small molded plastic and rubber parts, including a specially configured cryogenic shaking vessel and support and drive means for imparting a reciprocating rotational movement thereto. In the preferred embodiment the generally elongated shaker vessel has rounded ends and bottom, and the vessel is oscillated about an axis perpendicular to the longitudinal axis of the vessel, so that a maximum mixing of the product and the deflashing media, which may be sharply pointed objects such as chrome plated tacks, occurs within the shaking vessel.