The authors propose a method that describes line structures in given 3D medical images by estimating the values of model parameters: A Gaussian function is employed as the model function and the values of the parameters are estimated by means of a weighted integral method, in which you can estimate the parameter values by solving a system of linear equations of parameters which are derived from differential equations that are satisfied by the Gaussian model function. Different from many other model-based methods for the description, the proposed method requires no parameter sweep and hence can estimate the parameter values efficiently. Once you estimate the parameter values, you can describe the location, the orientation and the scale of line structures in given 3D images. Experimental results with artificial 3D images and with clinical X-ray CT ones demonstrate the estimation performance of the proposed method.