Abstract: Provided is a system, method, and computer program product for segmenting vessels in an ultrasound image. The method includes detecting edges of a vessel in the ultrasound image; detecting a vessel contour of the vessel in the ultrasound image based on the detected edges and a distance regularized level set evolution; and tracking the vessel contour with a Kalman Filter.

Abstract: Provided is a system, method, and computer program product for creating a deep-learning model for processing image data. The method includes establishing dense connections between each layer of a plurality of layers of a convolutional neural network (CNN) and a plurality of preceding layers of the CNN, downsampling an input of each downsampling layer of a plurality of downsampling layers in a first branch of the CNN, and upsampling an input of each upsampling layer of a plurality of upsampling layers in a second branch of the CNN by convolving the input.

Abstract: Provided is a system, method, and computer program product for analyzing spatio-temporal medical images using an artificial neural network. The method includes capturing a series of medical images of a patient, the series of medical images comprising visual movement of at least one entity, tracking time-varying spatial data associated with the at least one entity based on the visual movement, generating spatio-temporal data by correlating the time-varying spatial data with the series of medical images, and analyzing the series of medical images based on an artificial neural network comprising a plurality of layers, one or more layers of the plurality of layers each combining features from at least three different scales, at least one layer of the plurality of layers of the artificial neural network configured to learn spatio-temporal relationships based on the spatio-temporal data.

Abstract: Provided is a system, method, and computer program product for segmenting vessels in an ultrasound image. The method includes detecting edges of a vessel in the ultrasound image; detecting a vessel contour of the vessel in the ultrasound image based on the detected edges and a distance regularized level set evolution; and tracking the vessel contour with a Kalman Filter.

Abstract: Systems, methods, and computer program products are provided for removing noise and/or artifacts from an image. The method includes training a generative adversarial network (GAN) based on a plurality of images, the plurality of images comprising at least one undesired element comprising at least one of the following: noise, speckle patterns, artifacts, or any combination thereof, and generating a modified image based on processing an image of an eye or other object with the GAN to remove the at least one undesired element from the image that is above an outer surface of the eye or other object.

Abstract: Provided is a system, method, and computer program product for creating a deep-learning model for processing image data. The method includes establishing dense connections between each layer of a plurality of layers of a convolutional neural network (CNN) and a plurality of preceding layers of the CNN, downsampling an input of each downsampling layer of a plurality of downsampling layers in a first branch of the CNN, and upsampling an input of each upsampling layer of a plurality of upsampling layers in a second branch of the CNN by convolving the input.