In medical domain

the Computed radiography image system comes into a brand-new development. Image segmentation takes an important place in medical image processing. Different segmentation methods used in medical images cause different effects due to the particularities of medical images. With digital chest radiographs as research objects in this paper

several segmentation methods are presented to detect the ribs in digital chest radiographs

which include iterative probabilistic relaxation

K-means clustering and Gaussian curve plane threshold methods

etc. The evaluations of their results are given in the end of the paper. The experimental results indicate that Gaussian curve plane threshold method is more effective than the others to detect the ribs in digital chest radiographs. By using it

subsequent processing can be simplified and full information of the ribs can be obtained

so more reliable experiment data can be supplied to subsequent computer aided diagnosis.