Abstract: An embodiment of the invention may include a method, computer program product and computer system for image artifact removal. The method, computer program product and computer system may include computing device which may receive a primary image and analyze the primary image for global artifacts and local artifacts. The computing device may, in response to identifying a global artifact in the primary image, generate a secondary image with the global artifact removed utilizing a first generative adversarial network. The computing device may, in response to identifying a local artifact in the primary image, generate a patch with the local artifact removed utilizing a second generative adversarial network. The computing device may generate a hybrid image containing a reduction of global artifacts and a reduction of local artifacts by combining the secondary image and the patch utilizing a hybrid generative adversarial network.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for three-dimensional medical image generation. The method, computer program product and computer system may include computing device which may receive a first three-dimensional medical image of a first patient from a first period of time, a two-dimensional medical image of the first patient from a second period of time and a plurality of three-dimensional medical images for a plurality of second patients. The computing device may input the three-dimensional medical image of the first patient, the two-dimensional medical image of the first patient and the plurality of three-dimensional medical images for a plurality of second patients into a generative adversarial network (GAN). The computing device may generate a synthetic three-dimensional medical image for the first patient based on the two-dimensional medical image from the second period of time utilizing the GAN.

Abstract: Provided are techniques for automated software testing using simulated user personas. A request to test software is received. Job roles, user software activities for the software to be tested, and objectives are automatically identified using a first machine learning model. A test operation sequence using the job roles, the user software activities, and the objectives to test the software is generated using a second machine learning model. The test operation sequence is executed to simulate different users having different job roles using the software with the user software activities to achieve the objectives.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for three-dimensional medical image generation. The method, computer program product and computer system may include computing device which may receive a first three-dimensional medical image of a first patient from a first period of time, a two-dimensional medical image of the first patient from a second period of time and a plurality of three-dimensional medical images for a plurality of second patients. The computing device may input the three-dimensional medical image of the first patient, the two-dimensional medical image of the first patient and the plurality of three-dimensional medical images for a plurality of second patients into a generative adversarial network (GAN). The computing device may generate a synthetic three-dimensional medical image for the first patient based on the two-dimensional medical image from the second period of time utilizing the GAN.

Abstract: Provided are techniques for automated software testing using simulated user personas. A request to test software is received. Job roles, user software activities for the software to be tested, and objectives are automatically identified using a first machine learning model. A test operation sequence using the job roles, the user software activities, and the objectives to test the software is generated using a second machine learning model. The test operation sequence is executed to simulate different users having different job roles using the software with the user software activities to achieve the objectives.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for image artifact removal. The method, computer program product and computer system may include computing device which may receive a primary image and analyze the primary image for global artifacts and local artifacts. The computing device may, in response to identifying a global artifact in the primary image, generate a secondary image with the global artifact removed utilizing a first generative adversarial network. The computing device may, in response to identifying a local artifact in the primary image, generate a patch with the local artifact removed utilizing a second generative adversarial network. The computing device may generate a hybrid image containing a reduction of global artifacts and a reduction of local artifacts by combining the secondary image and the patch utilizing a hybrid generative adversarial network.

Abstract: The present invention is a diagnosis support system providing automated guidance to a user by automated retrieval of similar disease images and user feedback. High resolution standardized labeled and unlabeled, annotated and non-annotated images of diseased tissue in a database are clustered, preferably with expert feedback. An image retrieval application automatically computes image signatures for a query image and a representative image from each cluster, by segmenting the images into regions and extracting image features in the regions to produce feature vectors, and then comparing the feature vectors using a similarity measure. Preferably the features of the image signatures are extended beyond shape, color and texture of regions, by features specific to the disease. Optionally, the most discriminative features are used in creating the image signatures. A list of the most similar images is returned in response to a query. Keyword query is also supported.