Virtual colonoscopy is a method that scans through the 3D structure of a colon constructed by CT or MRI images and detects colon tissue

specifically

the polypus

which has great significance for early colorectal cancer screening. Registering colon images that have been acquired with different body positions can greatly improve the efficiency and accuracy of polyp detection in virtual colonoscopy. However

the traditional registration cannot accomplish this goal because of the drastic change in the supine and prone position of the patient

and the extraction of the feature points in the existing registration scheme does not take into account more special cases. Therefore

finding a new registration scheme of colon image is crucial. In this paper

a new method of colon registration that can complete the image registration acquired in different positions is proposed. Many previous works gradually flatten the three-dimensional (3D) colon to two-dimensional (2D) coordinates because of the large volume of 3D colon data. Registering 2D colon image directly is more convenient and easy to use for clinical application. Substantial work has been done to extract the effective feature points of the two images in registration. However

feature points acquired with previous methods cannot fully reflect the structural characteristics of the colon images obtained in different body positions

particularly the correlation between the two images. Haustral folds are remarkable and distributed in the entire colon; these folds are stable while the patient switches position. Therefore

the corresponding center of the fold can fully reflect the structural characteristics of the colon and is very suitable for colon registration. This paper proposes a new method to match the folds the two colon images and extract the center of matched folds as the feature point for registration. The complete registration scheme is as follows. First

extract the haustral fold that can reflect the information of fold structure. Gather the matched haustral folds using the method of template matching and feature matching and extract the center of matched folds as the feature points for image registration. Subsequently

do the non-rigid registration based in the center of matched haustral folds as coarse registration. The deformation between the two images is reduced in a more appropriate range after coarse registration. Finally

use b-spline registration based on gray value to complete the fine registration of the two pictures. This method can retrieve the drastic change in the colon image and make the change of the two images within certain limits. The traditional registration method can also be used as the feature point registration in previous works. Specific trained people can find out the two sets of matching colon folds because of the fold is remarkable in the colon. In the five sets of clinical data

about 62% haustral folds can be matched in comparison with the results of artificial matching. The rate of matching error is 4.7% because the center of matched folds is a significant feature point with high confidence in the two colon images and is very stable when patients switch position from supine to prone. The center of matched folds is more illustrative than other structural feature points in colon registration. The colonic deformation decreases after the rough registration of the folds

which makes the two colon images be registered using the traditional registration method. We accomplished the registration of colon images by using b-spline registration based on coarse registration. After registration

the gray absolute difference between the two colon images is clearly reduced. The set of colons that matches the high ratio of folds has the best registration accuracy. The gray value of the folds will have some differences because of the different angles of color rendering

and the absolute difference of gray image will still have a certain value after image registration. However

gray-scale difference can only reflect the global difference between the two colon images

but the structural features of the colon cannot be well evaluated. Therefore

the difference of polyp location detected by clinicians will be added to improve the evaluation method in the future. A new colon registration scheme is proposed in this paper. The drastic deformation between colon images caused by colon displacement and colon leakage makes the registration environment more complex and the previous feature points acquired unable to work well. Compared with the feature points using the previous method

the center of matched folds used as feature points can characterize the colon structure more significantly. The deformation of two colon images can be corrected when performing the rough registration of two colon images. We also completed fine registration using b-spline registration method based on coarse registration. In the present work

selecting the central points of the matched folds is still a more subjective process. Using all the center points may cause over registration and using less center points may also cause under-registration. Moreover

there will be more quantitative work on the final selection of feature points. However

the assessment cannot be completed simply using the difference of gray scale when performing registration evaluation. Therefore

others should be selected as criteria to improve the results of registration evaluation.