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: This invention pertains to packaging wherein the package comprises a blister member bonded to a substrate member. The blister member has a product-holding cavity having a sidewall, and is secured to the front surface of the substrate member by a bond line extending generally about the product-holding cavity. A tear strip is defined in one of the blister member and the substrate member. The tear strip comprises an opening tab having a distal edge disposed outwardly of the side wall at or adjacent a free edge in the blister card, and lines of weakness extending from approximately the distal edge inwardly on the blister card. The tear strip facilitates the creation of an opening in the blister card to provide access to the product-holding cavity. The tear strip is devoid of fixed bonding to the other of the substrate member and the blister member to allow for easy activation of the tear strip to open the package.