Abstract: Disclosed is a method (100) for correcting artifacts in Optical Coherence Tomography (OCT) images. The method involves acquiring an OCT image and subsequently transforming it from a Cartesian coordinate system to a polar coordinate system via polar reconstruction, generating a reconstructed polar OCT image. This image is then segmented into RED, GREEN, BLUE color channels. Fourier transformation is applied to each channel, transitioning them into their frequency domain representations. A custom frequency mask is utilized on these images, filtering out artifact-related frequencies. Following this, an inverse Fourier transformation is executed, reverting the images back to their Cartesian format. These images are then combined to produce a reconstituted OCT image. Further, this reconstituted image is merged with the original OCT image, resulting in an OCT image that is substantially free from artifacts.

Abstract: Disclosed is a method for analyzing a set of images of a coronary artery tissue. The method comprises segmenting the images for the presence of normal artery features and those associated with OCT, correcting artifacts, and optimizing the images. The method further comprises segmenting the diseased tissue into distinct tissue types, and measuring features of interests of the segmented tissue types. The method further comprises compiling a first set of measurements for each identified feature of interest at a first time, and a second set of measurements at a second time subsequent to the first time. The method further comprises determining changes in the coronary artery tissue, indicative of progression or regression of a diseased state, or prediction of multiple adverse cardiovascular events (MACE) such as cardiac death or myocardial infarction.

Abstract: Embodiments of the present techniques provide apparatus and methods for analysing intracoronary images, for example to predict the likelihood of a disease, disease presentation or event, and/or to track performance of a drug or other treatment. The method may comprise: for each image in the set of images of a coronary artery: classifying the image, using a first neural network, for the presence or absence of diseased tissue; when the image is classified as having diseased tissue present, classifying the image, using a second neural network, for the presence or absence of an artefact; determining whether to analyse the image based on the classifying steps; when the image is to be analysed, analysing the image by identifying, using a third neural network, one or more features of interest in a coronary artery tissue; and measuring each identified feature of interest.

Abstract: Embodiments of the present techniques provide apparatus and methods for analysing intracoronary images, for example to predict the likelihood of a disease, disease presentation or event, and/or to track performance of a drug or other treatment. The method may comprise: for each image in the set of images of a coronary artery: classifying the image, using a first neural network, for the presence or absence of diseased tissue; when the image is classified as having diseased tissue present, classifying the image, using a second neural network, for the presence or absence of an artefact; determining whether to analyse the image based on the classifying steps; when the image is to be analysed, analysing the image by identifying, using a third neural network, one or more features of interest in a coronary artery tissue; and measuring each identified feature of interest.

Abstract: A technique for determining a state of MS (Multiple Sclerosis) in a MS patient, for example Relapsing-Remitting MS (RRMS) or Secondary Progressive MS (SPMS) or an in-transition from RRMS to SPMS state, is presented. In the technique, patient data and age of the patient, and optionally EDSS score and/or T25FW score, is inputted by a user to a processor. The patient data queries comprise items grouped into a first group relating to relapse and recovery, a second group relating to symptoms experienced and a third group relating to impacts experienced by the patient in a predetermined period. Each item has an assigned predetermined weight and comprises a plurality of corresponding predetermined responses. Each response has an assigned predetermined score. Predetermined weights are also assigned for age query and to the EDSS query and/or the T25FW query.

Abstract: An image of an eye is obtained via a camera. A multi-step filter is applied to the image for multiple iterations. Applying the multi-step filter includes, for each iteration, performing one or more pixel merge operations on the image. The pixel merge operations are controlled based on one or more input parameters to control whether or not the iteration classifies pixels of the image as corresponding to a feature of the eye. The one or more input parameters vary from at least one iteration to another. The iterations each output a provisional output, in which some pixels of the image are deemed as corresponding to the feature of the eye. The provisional outputs provide diverse definitions of the eye feature, and may be combined in various ways to yield a refined output, in which some pixels of the image are deemed as corresponding to the feature of the eye.

Abstract: An image of an eye is obtained via a camera. A multi-step filter is applied to the image for multiple iterations. Applying the multi-step filter includes, for each iteration, performing one or more pixel merge operations on the image. The pixel merge operations are controlled based on one or more input parameters to control whether or not the iteration classifies pixels of the image as corresponding to a feature of the eye. The one or more input parameters vary from at least one iteration to another. The iterations each output a provisional output, in which some pixels of the image are deemed as corresponding to the feature of the eye. The provisional outputs provide diverse definitions of the eye feature, and may be combined in various ways to yield a refined output, in which some pixels of the image are deemed as corresponding to the feature of the eye.

Abstract: A display system comprises a display and a controller operatively coupled to the display. The controller is configured to receive text, parse the text to isolate a segment of the text, compute a time interval for display of the segment, present the segment on the display during the computed time interval, remove the segment from the display following the computed time interval, and repeat the parsing computing, presenting, and removing, for subsequent segments of the text.

Abstract: A comparative evaluation of a plurality of alternative candidates is performed by creating a plurality of evaluation criteria for evaluating the alternative candidates, comparing pairs of the evaluation criteria and assigning a relative weight to each compared pair of evaluation criteria, assigning an evaluation value to the evaluation criteria for each of the alternative candidates, and generating a relative ranking of the alternative candidates based at least in part on the assigned relative weights and the assigned evaluation values.

Abstract: A wall bracket for a loudspeaker or the like, particularly for use in the home theatre context, and comprising a wall plate (20) arranged for attachment to a wall, the plate having at least a pair of raised, laterally outward projecting flanges (21a, 21b); a bracket base arranged for engaging with the flanges and being thereby held to the wall plate, the bracket base having two substantially similar opposing parts (30, 40) each incorporating a substantially hemispherical socket (34); and a bracket mount (50) arranged for attachment to the loudspeaker etc, the bracket mount incorporating a ball member (51) adapted to be gripped between the bracket base sockets in a variety of configurations.