Freeze electron cross-sectional image-oriented mismatching removal method

A tomographic image and cryo-electron technology, applied in the field of structural biology, can solve problems such as inapplicable image pairing, and achieve the effect of improving the accuracy rate, improving the accuracy rate, and ensuring the correctness.

Pending Publication Date: 2022-04-15
ZHEJIANG UNIV
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can perform mismatch filtering on images without setting too many parameters, but this method needs to be processed under the three-dimensional point cloud image, and is not suitable for nanoscale image pairing

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Freeze electron cross-sectional image-oriented mismatching removal method
  • Freeze electron cross-sectional image-oriented mismatching removal method
  • Freeze electron cross-sectional image-oriented mismatching removal method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] A set of experimental data is set, the projection angle ranges from -60° to 60°, and the interval of each projection is 3°. A total of 41 cryo-electron tomography projection images are taken, each with a size of 5760×4092.

[0031] For this set of data, such as figure 1 As shown, mis-match removal is performed on the projection image of cryo-electron tomography, including:

[0032] S1 Screen stable matches from a group of cryo-electron tomographic image pairs, extract motion information between feature points as training samples, first calculate the neighbor ratio between feature points, set the threshold = 0.4, and then select the match with the neighbor ratio < threshold The feature points are used as a stable match and used as a training set.

[0033] Data points in the training set:

[0034]

[0035] where p i is the matching motion information of the i-th pair, To identify the label, where the label is 1 means that the match is correct, x i and y i Indica...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a frozen electron cross-sectional image-oriented mismatching removal method, which comprises the following steps of: S1, screening stable matching from a group of frozen electron cross-sectional image pairs, and extracting motion information between feature points as a training sample; s2, inputting the training sample obtained in the S1 into a pre-constructed nonlinear regression model, and fitting an identification function for calculating all matching correctness probabilities of the frozen electron cross-sectional image pair through training; s3, an identification function is obtained based on training fitting in the S2, and the frozen electron cross-sectional image pair is calculated to obtain an initial matching group; s4, repeating S1, S2 and S3 until an initial matching group of all the frozen electron cross-sectional image pairs is obtained; and S5, on the basis of all the initial matching groups, finishing final mismatching removal work through an RANSAC (Random Sample Consensus) algorithm. According to the method, the wrong matching is removed by using the motion consistency between the electron tomography projection image sequences, so that the correct matching between the images is effectively kept, and meanwhile, the accuracy of the alignment result is improved.

Description

technical field [0001] The invention relates to the technical field of structural biology, in particular to a method for removing mismatches for frozen electron tomography images. Background technique [0002] Cryo-electron microscopy combined with three-dimensional reconstruction technology has developed rapidly in the field of structural biology in recent years and is making important breakthroughs. Compared with traditional methods such as X-ray crystallography and nuclear magnetic resonance spectroscopy to determine the three-dimensional structure of protein molecules, it has the following advantages: Several advantages: [0003] 1. Maintain the activity and functional status of biological samples; [0004] 2. There is no need to prepare crystals, especially suitable for the determination of the three-dimensional structure of macromolecules and their complexes that are difficult to crystallize; [0005] 3. Combined with new equipment and technologies such as electron m...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/74G06K9/62
Inventor 冯结青郭珂诚
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products