A method for automatic segmentation of inner ear anatomy of a living subject, which is a bilateral cochlear implant recipient, in a post-implantation CT image, comprising: segmenting a region of the inner ear anatomy that is least likely to be affected by image artifacts in the post-implantation CT image so as to obtain a shape of the segmented region ; characterized in that the method further comprises: selecting a set of inner ear anatomy shapes from a library of inner ear anatomy shapes , wherein each selected inner ear anatomy shape has the smallest dissimilarity quantity with the shape of the segmented region in the post-implantation CT image, and wherein each shape in the library of inner ear anatomy shapes represents a labyrinth and structures-of-interest, SOIs, of an ear, wherein the segmenting the region of the inner ear anatomy is carried out by using a shape chosen from the library of inner ear anatomy shapes; creating a target specific active shape model, ASM, for each of the labyrinth and the SOIs using the selected set of inner ear anatomy shapes ; performing ASM-based segmentation of the labyrinth using the target-specific ASM of the labyrinth ; and fitting points of the target-specific ASM of the SOIs to their corresponding points on the segmented labyrinth to segment the SOIs in the post-implantation CT image . segmenting a region of the inner ear anatomy that is least likely to be affected by image artifacts in the post-implantation CT image so as to obtain a shape of the segmented region ; characterized in that the method further comprises: selecting a set of inner ear anatomy shapes from a library of inner ear anatomy shapes , wherein each selected inner ear anatomy shape has the smallest dissimilarity quantity with the shape of the segmented region in the post-implantation CT image, and wherein each shape in the library of inner ear anatomy shapes represents a labyrinth and structures-of-interest, SOIs, of an ear, wherein the segmenting the region of the inner ear anatomy is carried out by using a shape chosen from the library of inner ear anatomy shapes; creating a target specific active shape model, ASM, for each of the labyrinth and the SOIs using the selected set of inner ear anatomy shapes ; performing ASM-based segmentation of the labyrinth using the target-specific ASM of the labyrinth ; and fitting points of the target-specific ASM of the SOIs to their corresponding points on the segmented labyrinth to segment the SOIs in the post-implantation CT image . selecting a set of inner ear anatomy shapes from a library of inner ear anatomy shapes , wherein each selected inner ear anatomy shape has the smallest dissimilarity quantity with the shape of the segmented region in the post-implantation CT image, and wherein each shape in the library of inner ear anatomy shapes represents a labyrinth and structures-of-interest, SOIs, of an ear, wherein the segmenting the region of the inner ear anatomy is carried out by using a shape chosen from the library of inner ear anatomy shapes; creating a target specific active shape model, ASM, for each of the labyrinth and the SOIs using the selected set of inner ear anatomy shapes ; performing ASM-based segmentation of the labyrinth using the target-specific ASM of the labyrinth ; and fitting points of the target-specific ASM of the SOIs to their corresponding points on the segmented labyrinth to segment the SOIs in the post-implantation CT image . <EOS>