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A semi-automatic segmentation sequential optimization registration method

A sequential optimization, semi-automatic technology, applied in image analysis, image enhancement, instrument and other directions, can solve the problems of increased number of registrations, time-consuming, registration errors, etc., and achieve the effect of reducing time-consuming

Active Publication Date: 2019-05-17
NORTHWEST UNIV(CN)
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Problems solved by technology

[0005] The purpose of the present invention is to provide a semi-automatic segmented sequential optimization registration method, to eliminate the registration error caused by the relative movement of bone tissue in the prior art, The increase in the number of registrations after segmentation leads to a time-consuming problem

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  • A semi-automatic segmentation sequential optimization registration method
  • A semi-automatic segmentation sequential optimization registration method

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Embodiment Construction

[0033] The technical solutions of the present invention will be described more clearly and completely below in conjunction with the accompanying drawings and the embodiments of the present invention.

[0034] In this embodiment, CT images and X-ray images of the spine of the Third Hospital of Peking University were used to intercept the CT and X-ray images of the lesion, including three segments of bone tissue in total. The CT image volume data size is 512×359×238, and the slice thickness is 0.7mm. X-ray image size is 1024×803. The resolution is 0.28346mm / pixel.

[0035] The volume data described in this method is a term in three-dimensional graphics visualization, and the volume data is composed of voxels. Voxel is the basic volume element, and can also be understood as a point or a small area with arrangement and color in three-dimensional space. The CT image volume data used in this embodiment is similar to cuboid data in which all slices are superimposed without segment...

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Abstract

The invention discloses a semi-automatic segmentation 2D-3D sequential optimization registration method. The method comprises the steps that a CT sequence containing bone tissue is traversed, corner points are extracted through a Curveur Scale (CSS) algorithm, the bone tissue range is iteratively expanded, and plane segmentation is utilized to obtain volume data of all segments; a sequential optimization registration method is adopted, the initial registration parameters are obtained in a solution space according to the sequence, and finally a step acceleration method is used in a very small range for optimization search. According to the present invention, the problems that the preoperative CT and intraoperative X-ray shooting time are different, and the bone tissues generate the relativemotion, and the registration time is increased along with the increase of the number of segments, are solved, and the time complexity is reduced to O (6n).

Description

technical field [0001] The invention belongs to the field of medical image registration, and in particular relates to a semi-automatic segmentation sequential optimization registration method. Background technique [0002] In traditional orthopedic surgery, the surgeon needs to rely on clinical experience, combined with preoperative CT or X-ray images, to build a three-dimensional model of the bone structure in the brain to locate the lesion. Excessive reliance on doctors' clinical experience and lack of medical imaging evidence. With the development of computer-aided surgery systems, there has been a navigation system that reconstructs preoperative CT data into three-dimensional volume data and combines intraoperative X-ray images for surgery. It not only provides an objective imaging basis for the operation, but also makes the entire operation process visualized. [0003] The key to the research of surgical navigation is the registration of multimodal medical images. 2D...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/30G06T7/13G06T7/12G06T7/00G06T5/40G06T5/00
Inventor 田丰源周明全张晓杨稳胡佳贝耿国华
Owner NORTHWEST UNIV(CN)
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