Methods and systems for image alignment of at least one image to a model

Patent metadata

Field	Value
Publication number	US-9830732-B1
Application number	US-201715596173-A
Country	US
Kind code	B1
Filing date	May 16, 2017
Priority date	May 16, 2016
Publication date	Nov 28, 2017
Grant date	Nov 28, 2017

Abstract

A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

First claim

The invention claimed is:

1. A method for image alignment of at least one two-dimensional or three-dimensional image to a two-dimensional or three-dimensional model, executed on a processing unit, the image alignment having an acceptable likelihood of mismatch between the at least one image and the model, the method comprising:
selecting a value for a radius in Fourier space;
discretizing a set of poses into a discrete grid of candidate poses and a set of shifts into a discrete grid of candidate shifts;
determining a fixed fraction (f keep ) as an upper bound on the acceptable likelihood of mismatch, the fixed fraction being determined based on, at least, the fraction of poses and shifts that are discarded on typical dataset of images;
determining whether a selected accuracy of image alignment has been obtained, when such determination is false:
using the upper bound and a lower bound on the acceptable likelihood of mismatch, the lower bound being a combination of a first component (U(r,t)) and a second component (V(r,t)), the second component comprising a first subcomponent added to a second subcomponent and subtracted by a third subcomponent, the first subcomponent being the power of one of the images at high frequencies, the second subcomponent being the power of an image of a slice of the three-dimensional model for one of the poses at high frequencies, the third subcomponent being the correlation between the power of each of the images at high frequencies and the power of the image of the slice of the three-dimensional model for one of the poses at high frequencies;
determining values for the first component for each of the poses and shifts on the discrete grid of candidate poses and the discrete grid of shifts, using only portions of the image below the selected value for the radius in Fourier space;
determining a reference first component (U*) using the fixed fraction;
for every pose in the discrete grid of candidate poses, determining whether a minimum value of the first component over all the candidate shifts is greater than the reference first component and discarding the pose from the discrete grid in such case;
for every shift in the discrete grid of candidate shifts, determining whether the minimum value of the first component over all candidate poses is greater than the reference first component and discarding the shift from the discrete grid in such case;
for every remaining pose in the discrete grid of candidate poses, replacing the pose with a plurality of subdivided grid points representing the candidate poses;
for every remaining shift in the discrete grid of candidate shifts, replacing the shift with a plurality of subdivided grid points representing the candidate shifts; and
increasing the radius in the Fourier space; and

otherwise, returning the pose and shift at the lower bound with minimum value.

2. The method of claim 1 , wherein the lower bound is determined with the images at a resolution that is less than the maximum resolution for the images.

3. The method of claim 1 , wherein the first component is the squared error of Fourier coefficients at or below a selected radius in Fourier space, and the second component is the squared error of Fourier coefficients above the selected radius.

4. The method of claim 1 , wherein the second subcomponent comprises:

V
1

-

Σ


l


>
L

⁢

1
2

⁢

C
l
2

⁢



Y
^

l



2

-

4
⁢

Σ


l


>
L

⁢

1
2

⁢

C
l
2

⁢



Y
^

l



2

,

wherein V 1 is the power of one of the images at high frequencies, subscript l denotes a wavevector, subscript L denotes the selected radius in the Fourier space, C is a contrast transfer function (CTF) of the image-capturing apparatus, and Y is a vector representing a projection of the three-dimensional model.

5. The method of claim 4 , wherein the second subcomponent is only recomputed if the CTF of the image-capturing apparatus is different.

6. The method of claim 1 , wherein the determination of the upper bound comprises evaluating a value for the likelihood of mismatch at a specific pose, specific shift, or both.

7. The method of claim 1 , wherein determining the reference first component (U*) comprises determining the reference first component (U*) such that:



{

(

r
,
t

)

;

U
⁡

(

r
,
t

)

≤

U
*

}





{

Assignees

• Governing Council Univ Toronto

Inventors

• PUNJANI Ali
• Brubaker Marcus Anthony
• Fleet David James

Classifications

• G06T2207/10061

  from scanning electron microscope · CPC title

• G06T15/04 Primary

  Texture mapping · CPC title

• G06T7/37

  using transform domain methods · CPC title

• G16B45/00

  ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks · CPC title

• G06T7/75

  involving models · CPC title