2D-3D medical image parallel registration method based on combination similarity measure

A similarity measurement, 2D-3D technology, applied in image analysis, image data processing, instruments, etc., can solve problems that cannot meet the real-time requirements of image-guided radiotherapy, affect the efficiency of 2D-3D registration algorithms, and achieve global search Excellent ability, easy to calculate the effect

Inactive Publication Date: 2014-11-05
LANZHOU JIAOTONG UNIV
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Problems solved by technology

[0003] In 2D-3D image registration, it is necessary to reconstruct the 3D CT volume data to generate DRR. Since the generation process of DRR images is very time-consuming, and in the 2D-3D image registration algorithm, multiple DRR images need to be generated from different angles. Therefore, the generation process of DRR directly affects the efficiency of the entire 2D-3D registration algorithm. In addition, the calculation of the similarity measure also has an important impact on the operation efficiency and result accuracy of the entire registration process. Therefore, how to improve the 2D-3D registration algorithm The operating efficiency and accuracy to meet the needs of IGRT has become a hot research topic for many scholars.
GraemeP.Penney et al. compared six grayscale-based similarity measures applied to 2D-3D medical image registration. Even when there are differences in soft tissues in the two images to be registered, the pattern intensity and gradient The difference between the two similarity measures can still achieve accurate registration results and has good robustness; W.Birkfellner et al. proposed a DRR image generation method based on splat rendering and applied it to 2D-3D medical image registration In the standard, for volume data with a size of about 30MB on a PC, the time to draw a slightly blurred DRR image that can be used for 2D-3D registration is 100ms; Daniel B. Russakoff et al. proposed a method based on the attenuation domain The DRR rapid generation method is applied to 2D-3D registration, and its 2D-3D registration method has certain advantages in terms of execution efficiency and accuracy compared with t

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Embodiment 1

[0051] CUDA is a development environment and software architecture that can use C-like language for general computing without the help of graphics API. Improve the execution efficiency of the algorithm. In the DRR generation algorithm based on ray casting, each beam of light penetrates volume data to simulate the attenuation process of X-rays after entering the human body, which is independent of each other and has good parallelism. Therefore, the process can be realized by designing a kernel function executed on the GPU. accomplish.

[0052] Since the input data for generating DRR is a medical CT image sequence, its resolution is usually 512*512, and the resolution of DRR that needs to be used in the 2D-3D registration process is also 512*512, so 512*512 can be emitted from the light source 512 rays, each corresponding to a pixel of the DRR image, the process of sampling a ray through the volume data and accumulating the calculation of the CT value is encapsulated in the ker...

Embodiment 2

[0076] Medical image registration is essentially a process of seeking the optimal solution using the similarity measure function as the objective function. Since many similarity measurement functions have multiple local extremums, an intelligent optimization algorithm with a strong global optimization ability is used in the medical image registration process, which is helpful for finding the global optimal value and improving the accuracy of registration results. Significance.

[0077] Fruit Fly Algorithm (FOA) is a global optimization algorithm that simulates the foraging behavior of fruit flies proposed by Professor Pan Wenchao, a Taiwanese scholar. This algorithm has the characteristics of few parameters, short running time, easy understanding and implementation, etc., and is widely used. It is used in many fields of science and engineering. However, when optimizing the similarity measure function with multi-extreme features in medical image registration, FOA, like genetic...

Embodiment 3

[0097] In order to evaluate the execution efficiency and registration accuracy of the 2D-3D registration algorithm of the present invention, the present invention collects multiple groups of clinical radiotherapy X-ray images and CT image sequences used to formulate radiotherapy plans for different patients as the original data of this experiment. In the quasi-experiment, the X-ray image is used as a reference image, and the CT image sequence used for radiotherapy planning is used as a floating image. The DRR image is generated by performing a 6-degree-of-freedom rigid transformation on the CT image sequence, and the mixed similarity of the X-ray image and the DRR image is calculated. Measure and use the fruit fly optimization algorithm for global optimization, so as to realize the whole registration process. Since the two steps of DRR generation process and mixed similarity measure function calculation in the 2D-3D medical image registration algorithm of the present invention ...

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Abstract

The invention discloses a 2D-3D medical image parallel registration method based on combination similarity measure. The method comprises the following steps: firstly, using a CUDA (Compute Unified Device Architecture) parallel computing model to finish a quick generation process of a DRR (Digitally Reconstructed Radiograph) image; combining a SAD (Sum of Absolute Difference) with PI (pattern intensity) as new similarity measure to carry out parallel computation on GPU (Graphics Processing Unit); and finally, transferring a combination similarity measure value to CPU (Central Processing Unit), and adopting a fruit fly optimization algorithm based on bacterial chemotaxis behaviors to optimize for looking for an optimal registration parameter. An experiment verifies the performance of the method to show that the execution speed of the method is effectively improved since DRR high-speed generation and the mixed similarity measure are realized in the GPU. Meanwhile, compared with the single similarity measure, the invention adopts the mixed similarity measure to improve the accuracy of a registration result.

Description

technical field [0001] The invention relates to rapid registration of medical images, in particular to a method for parallel registration of 2D-3D medical images based on combined similarity measure. Background technique [0002] Image-Guided Radiotherapy (IGRT) is a new radiotherapy technology after three-dimensional conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT). In image-guided radiation therapy, in order to determine the actual position of the fractionation treatment, the physicist uses an electronic portal imaging device to obtain X-ray portal images. The X-ray image reflects the actual position during treatment, while the CT volume data before treatment represents the ideal position for treatment. Through the 2D-3D registration of the X-ray field image and the CT volume data, the offset of the treatment bed is calculated, and finally Adjust the position of the treatment bed according to the offset to ensure the accuracy of the positioning d...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 党建武杜晓刚王阳萍杨景玉王松陈永王冰
Owner LANZHOU JIAOTONG UNIV
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