Research On Living Liver Image Registration And Its Application

Liver is one of the most important organs in human.With the development of the medicine and computer technique,more and more modals medical images have emerged.Modern medical research usually requires integrated analysis of multiple images to get more information.A fundamental problem in medical image integrated analysis is that the images should be perfectly aligned,one essential aspect thereof is image registration,i.e.,recovering the geometric relationship between corresponding points in multiple images of the same scene.Medical image registration is an important technique in the field of medical image processing,and becoming more and more important for clinical diagnosis and treatment.The living liver images are obtained from the clinical medical examination,which contain the individual characteristic information.Registration of the living liver images will help for clinical diagnosis directly.Based on the registration methods,this work was supported by the National Nature Science Foundation of China(30770561 and 60701022)and the Science Research Foundation of ministry of Health & United Fujian Provincial Health and Education Project for Tacking the Key Research,P.R.China(WKJ2005-2-001). This thesis covered several registration methods of living liver images such as rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data,registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.The main contents and contributions of this thesis are as follows:1)A rigid registration algorithm based on joint distribution histogram was proposed for different phases of contrast enhanced liver CT data.The four key steps of the rigid algorithm have been improved in this algorithm.1) A fast image transformation method was proposed,which speed up the transformation procedure 2)An improved measure function based on joint distribution histogram was proposed,which speed up the registration procedure without losing the accuracy;3)A hybrid interpolation algorithm based on B-spline transform was proposed,which improved the interpolation results;4)A hybrid optimization algorithm based on PSO and Powell was proposed,which had higher convergence speed and settling local extremum preferably.After rigid registration the images of different phases of contrast enhanced liver CT were aligned approximately.2)A nonrigid registration algorithm based on thin-plate splines was proposed which locate the control points automatically.The control points and the interpolation function are the key factors of the nonrigid algorithm.This algorithm adopted weighted interpolation based on thin-plane splines interpolation so that there were no"blank value points"in the images.Because the images were aligned approximately after rigid registration,the control points could be located by an improved SIFT algorithm.After nonrigid registration the images of different phases of contrast enhanced liver CT were aligned precisely.Finally,the post-registration images were fused by a wavelets-based scheme and the different information was merged into a new image.3)An algorithm based on maximum mutual information was proposed for the registration of CT and DSA images.Firstly,projection transformation was applied to CT images so that 2D DSA information and 3D CT information was in the same coordinate system.Then after segment blood vessels and extracting skeleton line of blood vessels,the blood vessels were separated into several parts by some blood vessel nodes in the liver.Finally based on the maximum mutual information registration algorithm,the multimode registration of CT and DSA liver images was achieved.4)A two-step registration algorithm was proposed for the registration of CT and MRI images.Firstly a method based on principle axes and Fourier-Mellin transform was adopted for the coarse registration.Because there are clear contours in CT and MR image,we presented a registration method based on principal axes.Through matching the centroid and principal axes of image,the desired parameters for translation and rotation transform were obtained.After that the scaling parameter was obtained by Fourier-Mellin transform.Secondly,maximum mutual information algorithm was applied to achieve precise registration.Experiments show that the two-step algorithm could avoid erroneous results because of the local extremum.5)An algorithm was proposed to analyze the route and topology configuration of the liver vessels.After registration the types of branch variation of liver vessels were determined, while the diameter and length of vessels were calculated.This algorithm helped the liver surgery planning greatly.In summary,this thesis covered on several registration methods of living liver images including rigid registration of different phases of contrast enhanced liver CT data,nonrigid registration of different phases of contrast enhanced liver CT data, registration of MR and CT images,registration of DSA and CT images and the analysis of the types of branch variation of liver vessels.Several algorithms were proposed in this thesis for solving some problems for liver image registration. Although there is still much work to do,this thesis may help a lot for establishing a real applied digital virtual liver and liver surgery planning system.