A computer-implemented segmentation method (100, 210), the method comprising: performing a first automated segmentation operation on one or more first images of a subject area to automatically determine a first segmentation map of the subject area, wherein the one or more first images are generated using a first technique; performing, at least partially based on the first segmentation map, a second automated segmentation operation on one or more second images of the subject area to automatically determine a second segmentation map of the subject area, wherein the one or more second images of the subject area are generated using a second technique different from the first technique, the first and second imaging techniques to capture different properties of the subject area; automatically determining a mismatch between segmented portions of the first and second segmentation maps, characterised in that the method further comprises: identifying one or more regions of interest within the one or more second images at least partially based on the first segmentation map; generating an estimated second segmentation map using a region growing procedure to grow regions around seed locations within the one or more regions of interest, based one or more predetermined region growing criteria; wherein the second automated segmentation operation is performed at least partially based on the estimated second segmentation map. performing a first automated segmentation operation on one or more first images of a subject area to automatically determine a first segmentation map of the subject area, wherein the one or more first images are generated using a first technique; performing, at least partially based on the first segmentation map, a second automated segmentation operation on one or more second images of the subject area to automatically determine a second segmentation map of the subject area, wherein the one or more second images of the subject area are generated using a second technique different from the first technique, the first and second imaging techniques to capture different properties of the subject area; automatically determining a mismatch between segmented portions of the first and second segmentation maps, characterised in that the method further comprises: identifying one or more regions of interest within the one or more second images at least partially based on the first segmentation map; generating an estimated second segmentation map using a region growing procedure to grow regions around seed locations within the one or more regions of interest, based one or more predetermined region growing criteria; wherein the second automated segmentation operation is performed at least partially based on the estimated second segmentation map. identifying one or more regions of interest within the one or more second images at least partially based on the first segmentation map; generating an estimated second segmentation map using a region growing procedure to grow regions around seed locations within the one or more regions of interest, based one or more predetermined region growing criteria; wherein the second automated segmentation operation is performed at least partially based on the estimated second segmentation map.