Abstract: A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Abstract: A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Abstract: A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Abstract: A method for ultra-high resolution computed tomography imaging, comprising the steps of: focusing a high energy particle beam, for example x-rays or gamma-rays, onto a target object; acquiring a 2-dimensional projection data set representative of the target object; generating a corrected projection data set by applying a deconvolution algorithm, having an experimentally determined a transfer function, to the 2-dimensional data set; storing the corrected projection data set; incrementally rotating the target object through an angle of approximately 180°, and after each the incremental rotation, repeating the radiating, acquiring, generating and storing steps; and, after the rotating step, applying a cone-beam algorithm, for example a modified tomographic reconstruction algorithm, to the corrected projection data sets to generate a 3-dimensional image. The size of the spot focus of the beam is reduced to not greater than approximately 1 micron, and even to not greater than approximately 0.5 microns.

Abstract: A method for imaging a target volume comprises the steps of: radiating a small bandwidth of energy toward the target volume; focusing the small bandwidth of energy into a beam; moving the target volume through a plurality of positions within the focused beam; collecting a beam of energy scattered from the target volume with a non-diffractive confocal coded aperture; generating a shadow image of said aperture from every point source of radiation in the target volume; and, reconstructing the shadow image into a 3-dimensional image of the every point source by mathematically correlating the shadow image with a digital or analog version of the coded aperture. The method can comprise the step of collecting the beam of energy scattered from the target volume with a Fresnel zone plate.