CT three-dimensional image acquisition device based on popular learning

Abstract

A popular learning-based CT three-dimensional image acquisition device provided by the present invention comprises a CT scanner, a scanning bed and a cervical vertebra bracket, the CT scanner is provided with a radiation scanning ring for rotary scanning, the scanning bed comprises a base, a fixing plate and a bed backing plate, the base is fixedly arranged on the ground, the fixing plate is fixedly arranged at the upper end of the base, and the bed backing plate is fixedly arranged on the upper end of the fixing plate. The fixing plate is provided with a mattress plate, the fixing plate and the mattress plate are in sliding connection through a sliding block and a sliding rail, the extending direction of the fixing plate and the extending direction of the mattress plate are parallel to the axial direction of the radiation scanning ring, and the mattress plate moves in the direction parallel to the axial direction of the radiation scanning ring. A cervical vertebra bracket is obliquely arranged at the end, close to the radiation scanning ring, of the mattress plate, the cervical vertebra bracket and the mattress plate are fixedly connected through an angle adjusting mechanism, and the mattress plate is driven by a driving device to slide relative to the fixing plate. The invention provides the CT three-dimensional image acquisition device based on manifold learning, which is high in operation stability and accurate in acquired data.

Description

technical field [0001] The invention relates to the technical field of three-dimensional image acquisition devices, in particular to a CT three-dimensional image acquisition device based on popular learning. Background technique [0002] With the development of society, the presentation of two-dimensional images has been unable to meet people's needs, especially the demand for medical images has gradually increased from simple two-dimensional images to three-dimensional images. The method based on popularity learning assumes that the sample points distributed in the high-dimensional space are on or approximately on the nonlinear manifold, and use such methods to find the low-dimensional smooth popularity embedded in the high-dimensional data space. It is a fundamental and forward-looking research direction, which provides an effective way to explore the intrinsic structure of nonlinear manifold distribution data. For example, using CT to collect three-dimensional images of ...

AI Technical Summary

Problems solved by technology

However, popular learning has high requirements for the accuracy of the information collected by the three-dimensional image acquisition device. At present, CT devices cannot keep the head at the center of the scanning ring of the scanner for people with large differences in body size, which leads to the accuracy of image acquisition. insufficient

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