1. A method for automatic boundary segmentation of an object in a medical image, comprising the steps of: determining a point indicating a center or an approximate center of an object in a medical image displayed on a display; applying a filter to the medical image so as to determine candidate pixels as edge pixels indicating a boundary of the object; removing linked candidate pixels, a length of the linked candidate pixels being shorter than a predetermined threshold; determining a pixel among the candidate pixels as a false edge of the boundary of the object by using domain knowledge and removing the candidate pixel determined as the false edge, wherein the determining is based on a probability that the candidate pixel indicates part of the boundary of the object, wherein the probability is determined based on a combination of the following: a contrast membership function; a domain membership function; and a texture membership function; identifying candidate pixels which are first detected when the medical image is scanned along each radial direction from the center as the remaining candidate pixels; removing a candidate pixel from the remaining candidate pixels by fitting a polynomial to the remaining candidate pixels; generating a closed contour as the boundary of the object by applying a Discrete Dynamic Contour (DDC) model to the remaining candidate pixels other than the candidate pixels removed by fitting a polynomial to the remaining candidate pixels; and displaying the closed contour on the display.