1. A method of operation of an apparatus for identifying anomalous data in a test data set, wherein the test data set is a test image comprising a plurality of test pixels or voxels as test data points, the method comprising: receiving input, by the apparatus, of at least one standard image comprising a plurality of standard pixels or voxels; storing, by the apparatus, one or more standard data sets of a plurality of standard data cases, each standard data case containing one or more standard data points representing normal, non-anomalous, data, wherein each standard data case is a corresponding standard image, of the at least one standard image, comprising a corresponding plurality of standard pixels or voxels as standard data points; establishing a spatial correspondence between test data points of the test data set and respective corresponding standard data points in the one or more standard data sets of the plurality of standard data cases, wherein the establishing the spatial correspondence comprises spatially aligning the test image in co-registration with the at least one standard image; calculating a first average similarity distance measure between (a) and (b), where (a) includes one or more test data points in the test data set, and (b) includes one or more of the nearest neighboring corresponding standard data points in at least two of the plurality of standard data cases; determining a second average similarity distance measure between the nearest neighboring corresponding standard data points in at least two of the plurality of standard data cases; calculating a normalized similarity distance measure relating to the one or more test data points using a mathematical function, wherein at least the first and second average similarity distance measures are inputs to the mathematical function; and identifying a test data point as anomalous in dependence on a value of the calculated normalized similarity distance measure for the test data point.