A computer implemented method of determining a location at which a given feature is represented in medical imaging data, the medical imaging data comprising an array of elements each having a value, the method comprising: obtaining a first descriptor for a first location in first medical imaging data (220, 772), the first location being the location within the first medical imaging data at which the given feature is represented, the first descriptor being representative of values of elements of the first medical imaging data located relative to the first location according to a first predefined pattern; obtaining a second descriptor for each of a plurality of candidate second locations (334, 340, 440) in second medical imaging data (330, 770), each second descriptor being representative of values of elements (332, 338) of the second medical imaging data located relative to the respective candidate second location according to the first predefined pattern; calculating, for each of the plurality of candidate second locations, a similarity metric indicating a degree of similarity between the first descriptor and the second descriptor for the candidate second location; selecting a candidate second location (334, 448) from among the plurality of candidate second locations based on the calculated similarity metrics; and determining the location (334, 446) at which the given feature is represented in the second medical imaging data based on the selected candidate second location (334, 448); wherein a descriptor for a given location (224, 334, 340) is a vector comprising a plurality of entries, each entry being representative of the values of the elements located within a respective one (223, 333, 339) of a plurality of predefined boxes (222, 332, 338) located relative to the given location (224, 334, 340) according to the first predefined pattern, characterized in that each entry of the plurality of entries of the vector is the average of the values of elements located within a respective one of the plurality of predefined boxes. obtaining a first descriptor for a first location in first medical imaging data (220, 772), the first location being the location within the first medical imaging data at which the given feature is represented, the first descriptor being representative of values of elements of the first medical imaging data located relative to the first location according to a first predefined pattern; obtaining a second descriptor for each of a plurality of candidate second locations (334, 340, 440) in second medical imaging data (330, 770), each second descriptor being representative of values of elements (332, 338) of the second medical imaging data located relative to the respective candidate second location according to the first predefined pattern; calculating, for each of the plurality of candidate second locations, a similarity metric indicating a degree of similarity between the first descriptor and the second descriptor for the candidate second location; selecting a candidate second location (334, 448) from among the plurality of candidate second locations based on the calculated similarity metrics; and determining the location (334, 446) at which the given feature is represented in the second medical imaging data based on the selected candidate second location (334, 448); wherein a descriptor for a given location (224, 334, 340) is a vector comprising a plurality of entries, each entry being representative of the values of the elements located within a respective one (223, 333, 339) of a plurality of predefined boxes (222, 332, 338) located relative to the given location (224, 334, 340) according to the first predefined pattern, characterized in that each entry of the plurality of entries of the vector is the average of the values of elements located within a respective one of the plurality of predefined boxes.