white light data and CT data registration method based on improved iteration nearest point algorithm

Abstract

The invention belongs to the technical field of image data processing, and discloses a white light data and CT data registration method based on an improved iteration nearest point algorithm. The method comprises the following steps of preprocessing the collected CT data, white light data and fluorescence data; reconstructing and segmenting the CT data, and performing surface extraction and segmentation on the CT data to obtain body surface data; carrying out mouse 3D surface gridding reconstruction by adopting an improved voxel-based method; registering the 3D CT data and the 3D white light data by adopting an ICP algorithm based on bidirectional distance proportion improvement; and carrying out multiple pieces of fluorescence information fusion and 3D surface fluorescence luminous flux reconstruction so as to realize fusion of CT data and optical data. According to the method, the registration precision of the white light data and the CT data can be improved, the registration speed is increased, optical reverse reconstruction is facilitated, observation judgment in medical diagnosis, prediction simulation in virtual surgery and training practice in clinical teaching are facilitated, and convenience is brought to a user.

Description

technical field [0001] The invention belongs to the technical field of image data processing, and in particular relates to a method for registering white light data and CT data based on an improved iterative closest point algorithm. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: molecular imaging technology is widely used in medical diagnosis because of its non-destructive and dynamic detection, and with the development of medical imaging technology, multi-modal imaging has also become a modern medical development important direction. Bioautofluorescence tomography is one of the most representative imaging methods in optical molecular imaging, which has the advantages of high sensitivity, low background noise, fast imaging speed, non-invasive, low cost and no ionizing radiation. However, BLI is only two-dimensional imaging, without depth information, and cannot reflect the position information of the interna...

AI Technical Summary

Problems solved by technology

Researchers have done a lot of work on the method of reverse reconstruction, but how to accurately obtain the fusion information of optical data and CT data is rarely studied

[0004] To sum up, the problems existing in the existing technology are: the traditional method of fusion of optical data and CT data needs to set up the system; it relies too much on the selection of marker points, and the artificially selected marker points will also cause certain damage to the registration. The error affects the accuracy of optical inverse reconstruction

[0005] The difficulty and significance of solving the above technical problems: the accuracy of the traditional optical data and CT data fusion method is difficult to guarantee, and the registration method of white light data and CT data based on the improved iterative closest point algorithm requires three-dimensional reconstruction of CT data; The improved voxel-based Space caving method reconstructs the surface of the mouse; the improved iterative closest point algorithm is used to register the 3D CT data and the 3D white light data, in which the accuracy and speed of the registration are crucial, based on the improved two-way distance ratio The assignment of weights in the iterative closest point algorithm, that is, the probability value, is an important problem to be solved

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