To overcome existing problems in generating digitallg reconstructed radiongrapl (DRR) and to measure the similarity needed for large computations in the process of 2D/3D medical image registration

a hybrid registration algorithm was proposed. This algorithm combines pattern intensity with gradient on the basis of the Bresenham line generation algorithm. First

the space coordinate system

in which the position of the virtual point light source

3D volume data

and projection panel can be determined

is established. Second

virtual point light source emits virtual light and the light passes through volume data. The DRR image can be obtained by computing the gray value of points projected by every virtual ray to the image panel via the ray-casting algorithm

which is an enhancement of the Bresenham line generation algorithm. Third

the registration components

including interpolator

space transformation component

optimizer

and pyramid filter

are instantiated. The pyramid filter is initialized such that the number of layers and shrinkage factor of each layer are set. Fourth

the reference image and floating image are processed separately into different resolution sequence images and image pyramids. The image resolution increases from top to bottom in the two pyramids. The arranged images in a pyramid correspond to those of another pyramid. The transformation parameters are calculated by the improved mode intensity measure

and the optimal transformation parameters are obtained by the improved Powell algorithm. The above process will be executed circularly until the image registration is complete. The experimental results show that compared with an algorithm based on correlation coefficient

mutual information

and pattern intensity

the proposed method shows a substantial increase in registration efficiency. The completion time of the simulated registration experiment and clinical registration experiment are 76.2 s and 64.9 s

respectively. The proposed method increases efficiency by 3~6 times compared with the traditional registration algorithm. The hybrid algorithm not only has strong robustness and high clinical requirement accuracy but also significantly reduces the time required for registration.