Self-adaptive registration method and self-adaptive registration system for biological imaging

A biological imaging and self-adaptive technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as application limitations, and achieve the effects of speeding up, significant registration time loss, and significant registration self-adaptation

Inactive Publication Date: 2018-09-18
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

The registration algorithm based on the physical model will increase the deformation energy in proportion to the degree of deformation during the registration process, so there are certain limitations in the processing of large deformations, and the parameters in the model will vary due to different registration objects. There is a large difference, which requires artificial resetting, which also limits the application of this type of method

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  • Self-adaptive registration method and self-adaptive registration system for biological imaging
  • Self-adaptive registration method and self-adaptive registration system for biological imaging

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[0033] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0034] Such as Figure 1 to Figure 3 As shown, a kind of self-adaptive registration method for biological imaging provided by the present invention comprises:

[0035] SIFT feature extraction step: extract the SIFT feature points of the image and match them. The RANSAC algorithm is used for matching through SIFT feature point extraction. Introducing features into the grayscale-based registration algorithm can form a good algorithm complementarity, which makes the algorithm more capable of processing f...

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Abstract

The invention provides a self-adaptive registration method and a self-adaptive registration system for biological imaging. The method comprises the steps of extracting the SIFT feature points of images and matching the feature points; according to the SIFT feature points, generating deformation field initial parameters for different deformation images in the self-adaptive manner; fusing the spacecorrelation information of the images with the image registration based on the gray level; and adjusting the step size in the self-adaptive manner in the iteration process. According to the invention,the self-adaptive registration of high-resolution biological imaging is realized through the automatic and intelligent means. The operation is simple and convenient, and the detection efficiency is high. The reliability is high, and the universality is high.

Description

technical field [0001] The invention relates to an image adaptive registration method, in particular to an adaptive registration method for high-resolution biological imaging. Background technique [0002] In view of the important application of image registration technology, it has always been a research hotspot in remote sensing image and medical image analysis. Image registration technology started relatively late and was gradually developed in the 1980s. Its development is inseparable from the development of computer graphics processing technology. Image registration has been developed to the present, and the solution to practical problems is often achieved through the synthesis of multiple methods. If it is only limited to classification, people are used to dividing the types of image registration into rigid registration and non-rigid registration according to the deformation type of registration tissue; according to the dimensionality of image data, it can be divided ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/33
CPCG06T7/33G06T2207/20221
Inventor 沈健胡洁戚进黄海清何涛胡方凯
Owner SHANGHAI JIAO TONG UNIV
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