Segmentation of a structure

摘要

A method and a segmentation system are disclosed. An embodiment of the method includes providing an image representation of the structure; providing a start surface model, including a mesh with a plurality of vertices connected by edges; defining for each vertex a ray normal to the surface model at the position of the vertex; assigning more than two labels to each vertex, each label representing a candidate position of the vertex on the ray; providing a representation of likelihoods for each candidate position the likelihood referring to whether the candidate position corresponds to a surface point of the structure in the image representation; and defining a first order Markow Random Field with discrete multivariate random variables, the random variables including the labels of the candidate positions and the representation of likelihoods, finding an optimal segmentation of the structure by using an maximum a posteriori estimation in this Markow Random Field.

主权项

1. A method for segmentation of a biological structure, in image data, comprising:
providing an image representation of the biological structure; providing a start surface model, including a mesh with a plurality of vertices connected by edges; defining for each vertex a ray normal to the surface model at the position of the vertex; assigning more than two labels to each vertex, each label representing a candidate position of the vertex on the ray; providing a representation of likelihoods for each candidate position, the likelihood referring to whether the candidate position corresponds to a surface point of the biological structure in the image representation; defining a first order Markov Random Field with discrete multivariate random variables, the random variables including the labels of the candidate positions and the representation of likelihoods; and segmenting the image representation of the biological structure, the segmenting including, determining a selected segmentation of the biological structure using an maximum a posteriori estimation in the Markov Random Field, the selected segmentation representing a true surface of the biological structure.