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A method is presented for segmentation of anatomical structures that incorporates prior information about shape. The method iteratively applies steps, which find object's border considering its properties independently from shape. The boundary is regularized taking in account the shape being extracted. Detection is not directly performed in the image but in a "shape space" referred to the shape in each step. The problem is reduced to work in this new coordinate system where the border is approximately a horizontal line. Shape information is introduced through a higher dimensional map similar to a distance map of a mean shape. Segmentation results are demonstrated on ultrasound imagery to measure meat quality of bovine and ovine livestock.