Organ geometry reconstruction method based on image volume element operation

Abstract

The invention provides an organ geometry reconstruction method based on the image volume element operation. The method comprises the steps of acquiring a location matrix of a volume element relative data set of a specified organ, resampling the location matrix according to accuracy requirements, generating a cuboid coordinate matrix by means of the volume element additive operation, and reconstructing organ geometry according to the cuboid coordinate matrix. The human organ geometry reconstruction method is capable of quickly merging volume elements to the maximum level by means of a volume element additive operation algorithm, keeping the original shape of an organ, completely describing the detailed structure of the interior of the organ, reserving and controlling point clouds on the periphery surface of the organ by flexibly and efficiently combining with sampling and the volume element operation, and therefore Monte Carlo geometric description of an associated organ is enabled to be easy. The research result of the organ geometry reconstruction method based on the image volume element operation is applicable to efficient calculation of different Monte Carlo programs and assessment of human body radiation absorbed doses, and has wide application significance in fields like radiation safety or medical physics.

Description

technical field [0001] The invention relates to an organ geometry reconstruction method based on image voxel operation, through which a solid geometry model expressing the internal or external structure of a real object can be constructed efficiently. The calculation of dose absorption involving solid modeling and this geometric description has application value in the fields of radiation protection, medical radiotherapy planning and imaging science. Background technique [0002] Three-dimensional models are widely used in the fields of scientific experiment analysis and scientific experiment simulation. For example, in the field of nuclear radiation and protection, in order to simulate the absorbed dose of the human body under certain radiation conditions, it is often necessary to use computer technology to perform various processing on human body image data to establish an accurate human body geometric model, and combine it with Monte Carlo programs for simulation calculat...

AI Technical Summary

Problems solved by technology

Based on high-precision human body image slices, commonly used 3D surface reconstruction algorithms (such as Marching Cubes) obtain the surface model structure by extracting the isosurface of the real object. On the one hand, due to the insufficiency of this surface extraction method, often It leads to the ambiguity of the surface structure of the model, resulting in many holes caused by the intersection of inside and outside or the error of the normal vector, which makes the model distorted and cannot truly express the internal geometric structure of the human body.

On the other hand, in the geometric reconstruction process, the analysis of the peripheral surface of the organ and its associated Monte Carlo geometric structure are not fully considered, so there are errors in the degree of analysis, the execution efficiency is not high, and it cannot be widely used

Some existing geometric reconstruction methods based on voxel merging, although in a certain sense, organ voxels have been merged to overcome the above defects, but the surface voxels of organs have not been merged to the maximum so that they cannot effectively reduce organ voxel merging After the number of cuboids, the merging speed is slow, and the point cloud information of the organ surface cannot be generated, and the application limitation in the huge amount of human body image data

Images