A computer-implemented method of segmenting a surface in a multi-dimensional dataset comprising a plurality of sequential images, said method comprising the steps of: - selecting an image segmentation algorithm that is based on a deformable surface model comprising an a-priori constructed shape model and an a-priori constructed appearance model configured to model the image appearance, whereby the shape model is characterized by first parameters and the appearance model is characterized by second parameters; - accessing pre-determined shape parameters and appearance parameters of the surface, the surface being modeled by a surface mesh made of a number of vertices and triangles, wherein the vertices constitute the shape model and vectors of image gray values make up the appearance model, wherein the appearance parameters are derived from the vectors of image intensity gray values; - adapting the first parameters and the second parameters based on the shape parameters and the appearance parameters yielding adapted first parameters and adapted second parameters; - segmenting the surface in the multi-dimensional dataset using said image segmentation algorithm with the adapted first parameters and the adapted second parameters yielding respective portions of the surface for each segmented image; - tracking the surface in the multi-dimensional dataset to establish spatial correspondence between said surface portions, wherein the appearance model is made up by the vectors ĝ i for all triangles i, where ĝ i = I ( p i, k) with p i,k = m i + R i s k, wherein I is an image gray value, m i is the center of mass of the triangle, R i is a rotation matrix that transforms vector |0,01| into the triangle normal n i, and s k is an offset, wherein the segmentation of the surface in the multi-dimensional dataset using said image segmentation algorithm with the adapted first parameters and the adapted second parameters comprises an optimization in which the image gray values of the vector ĝ i for a triangle i are compared to image gray values of corresponding vectors at a number of discrete candidate points x i surrounding the center of mass m i of the triangle on a multi-icosahedron grid in all directions and at different distances. - selecting an image segmentation algorithm that is based on a deformable surface model comprising an a-priori constructed shape model and an a-priori constructed appearance model configured to model the image appearance, whereby the shape model is characterized by first parameters and the appearance model is characterized by second parameters; - accessing pre-determined shape parameters and appearance parameters of the surface, the surface being modeled by a surface mesh made of a number of vertices and triangles, wherein the vertices constitute the shape model and vectors of image gray values make up the appearance model, wherein the appearance parameters are derived from the vectors of image intensity gray values; - adapting the first parameters and the second parameters based on the shape parameters and the appearance parameters yielding adapted first parameters and adapted second parameters; - segmenting the surface in the multi-dimensional dataset using said image segmentation algorithm with the adapted first parameters and the adapted second parameters yielding respective portions of the surface for each segmented image; - tracking the surface in the multi-dimensional dataset to establish spatial correspondence between said surface portions,