Abstract: A method and apparatus for enhancing magnetic resonance images to produce contrast-enhanced images without the need to administer contrast agent to a patient. The image processing apparatus utilises a trained machine learning algorithm as an image processor, preferably a generative adversarial network, to produce images from contrast agent-free magnetic resonance images with the produced images having similar appearance and better image quality and better pathological sensitivity and being able to differentiate more pathological conditions than actually acquired contrast-enhanced images.

Abstract: A method of selecting an operation for analysis of data, the method comprising: processing the data using at least two operations, wherein each of the at least two operations are different, to obtain a set of outputs including the output associated with each operation; determining an output from the set of outputs with the highest predicted accuracy; and selecting the operation associated with the determined output for further analysis of data; wherein the determination of the output with the highest predicted accuracy comprises: selecting an output from the set of outputs; calculating a degree of similarity between the selected output and another output of the set of outputs; using the degree of similarity to predict the accuracy of the selected output based on a relationship between the similarity of the outputs and the accuracy of the outputs, the relationship being derived from an analysis of the degrees of similarity between the outputs of the operations on training data including ground truth and the ac