Abstract: Disclosed herein are methods of utilizing machine learning methods to analyze microscope images of populations of cells.

Abstract: Disclosed herein are methods of utilizing machine learning methods to analyze microscope images of populations of cells.

Abstract: Disclosed herein are methods of utilizing machine learning methods to analyze microscope images of populations of cells.

Abstract: Disclosed herein are methods of detecting a target viral nucleic acid sequence, determining the localization of the target viral nucleic acid sequence, and/or quantifying the number of target viral nucleic acid sequences in a cell. This method may be used on small target nucleic acid sequences, and may be referred to as Nano-FISH or viral Nano-FISH.

Abstract: Disclosed herein are methods of utilizing machine learning methods to analyze microscope images of populations of cells.

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 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.