Multi-channel Diffusion Tensor Imaging Registration Based On Active Demons Algorithm By Using Variable Parameters

Diffusion tensor image(DTI)technology is a new method for brain functional imaging.DTI evaluates the structure and physiological state of biological tissues by measuring the dispersion process of water molecules.It is the only non-invasive method for effectively observing and tracking white matter fiber bundles.DTI registration can monitor the development of degenerative brain diseases and find statistical differences among different populations.DTI contains a wealth of information about the direction of brain white matter fibers.DTI registration not only requires the consistency of the anatomy between the reference and the moving image after registration but also demands consistency between the diffusion tensor direction and the anatomic structure.So DTI registration is more complicated than conventional scalar image registration.In order to effectively utilize the tensor information of DTI and improve the accuracy and speed of DTI registration,this paper focuses on the tensor based method of DTI registration.In order to probe into the advantages and disadvantages of the tensor-based DTI registration method and the scalar-based DTI registration method,The scalar image based registration algorithm of DTI registration methods is considered firstly and the DTI affine registration based on fractional anisotropy(FA)maps is realized in this paper.Then the tensor image based registration algorithms of DTI registration methods is considered.The DTI registration based on demons algorithm,which uses the six independent components of the tensor as inputs,can fully use the direction information of the diffusion tensor data and improve the quality of registration.However,this algorithm does not perform well in the large deformation areas,and its convergence speed is slow.Therefore,a multi-channel DTI registration method based on active demons algorithm is proposed.In the multi-channel DTI registration method based on active demons algorithm,the image topology will change if the homogenization coefficient is too small.Although a faster convergence can be achieved by fixing the homogenization coefficient and introducing a single balance coefficient,the topological structure of the image changes simultaneously.Therefore,by analyzing the influence of the homogeneous and the balance coefficient in the active demons algorithm on the DTI registration and combining the advantages of the balance coefficient of improving the convergence speed and that of homogeneous coefficient of enhancing the accuracy of the multi-channel DTI registration,an appropriate homogeneous coefficient is first manually selected in a reasonable range.Then,the size of the balance coefficient value is dynamically adjusted with the decreasing Gaussian kernel during the convergence of this proposed algorithm.A smaller balance coefficient is used in the initial stage of DTI registration for a faster convergence speed,and then the balance coefficient is gradually increased for a smaller registration error.A multi-channel DTI registration method based on the active demons algorithm by using variable parameter is proposed further.The experimental results prove that under the method proposed above,the convergence speed is increased,the registration effect in large deformation areas is significantly improved,and the topology consistency of the image is preserved before and after registration.At the same time,compared with the DTI affine registration method based on FA images,the DTI registration accuracy is significantly improved and the difference between the reference and moving FA map is reduced by using the two tensor based DTI registration methods proposed in this paper.So the two DTI registration methods proposed in this paper are superior to the scalar-based DTI registration method in terms of registration efficiency.