Abstract: A feature extractor and novel training objective are provided for content-based image retrieval. For example, a computer-implemented method includes applying a query image and a search image to a neural network of a feature extraction network of a computing device, the query image indicating an object to be searched for in the search image. The feature extraction network includes the neural network, a spatial feature neural network receiving a first output of the neural network pertaining to the search image, and an embedding network receiving a second output of the neural network pertaining to the query image. The method includes generating spatial search features from the spatial feature neural network, generating a query feature from the embedding network, applying the query feature to an artificial neural network (ANN) index, and determining an optimal matching result of an object in the search image based on an operation using the ANN index.

Abstract: A feature extractor and novel training objective are provided for content-based image retrieval. For example, a computer-implemented method includes applying a query image and a search image to a neural network of a feature extraction network of a computing device, the query image indicating an object to be searched for in the search image. The feature extraction network includes the neural network, a spatial feature neural network receiving a first output of the neural network pertaining to the search image, and an embedding network receiving a second output of the neural network pertaining to the query image. The method includes generating spatial search features from the spatial feature neural network, generating a query feature from the embedding network, applying the query feature to an artificial neural network (ANN) index, and determining an optimal matching result of an object in the search image based on an operation using the ANN index.

Abstract: Techniques performed by a data processing system for operating a personalized oncology system herein include accessing a first histopathological image of a histopathological slide of a sample taken from a first patient; analyzing the first histopathological image using a first machine learning model configured to extract first features from the first histopathological image; searching a histological database that includes a plurality of second histopathological images and corresponding clinical data for a plurality of second patients to generate search results; analyzing the plurality of third histopathological images and the corresponding clinical data associated with the plurality of third histopathological images using statistical analysis techniques to generate associated statistics and metrics associated with mortality, morbidity, time-to-event, or a combination thereof for the plurality of third patients associated with the third histopathological images; and presenting an interactive visual representat