CN114820489B - OPM array rapid optical scanning positioning method based on space mark points - Google Patents
OPM array rapid optical scanning positioning method based on space mark points Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
- A61B5/004—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part
- A61B5/0042—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room adapted for image acquisition of a particular organ or body part for the brain
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/242—Detecting biomagnetic fields, e.g. magnetic fields produced by bioelectric currents
- A61B5/245—Detecting biomagnetic fields, e.g. magnetic fields produced by bioelectric currents specially adapted for magnetoencephalographic [MEG] signals
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
- A61B5/4064—Evaluating the brain
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/344—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving models
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
- G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
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- A—HUMAN NECESSITIES
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- A61B2576/02—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part
- A61B2576/026—Medical imaging apparatus involving image processing or analysis specially adapted for a particular organ or body part for the brain
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- G06T2207/30—Subject of image; Context of image processing
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Abstract
The invention provides a space mark point-based OPM array rapid optical scanning positioning method, which comprises the steps of establishing a helmet coordinate system, obtaining three-dimensional image coordinates by means of optical scanning, and performing image registration by means of space mark points and a registration algorithm to realize rapid and accurate positioning of all OPMs; the method of the invention uses optical scanning to rapidly obtain the OPM array and the tested head image, has high sampling speed, and saves time and labor; and quickly acquiring the positions of all OPMs from the three-dimensional image of the optical scanning by using the space mark points and the priori knowledge of the slots on the rigid helmet, and quickly corresponding the positions of the OPMs to the slots.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a space mark point-based OPM array rapid optical scanning positioning method.
Technical Field
Magnetoencephalogram (hereinafter abbreviated as MEG) is a technique for inferring non-destructive brain function of brain activity in the head by measuring the magnetic field generated by nerve current outside the head, brain imaging, and diagnosis of brain diseases. Recently, an atomic magnetometer (hereinafter abbreviated as "OPM") has been developed as a detection unit of a magnetoencephalogram because of its high sensitivity and small volume.
OPMs are often packaged in a single channel, and the position of each OPM in the MEG detector array is adjustable, which enables the MEG to adapt to different head styles and different measurement requirements. In order to compromise detector array's stability, the MEG can adopt the rigidity helmet to fix the OPM, and the OPM can slide from top to bottom in the slot of rigidity helmet simultaneously, also can keep detector array's flexibility through changing the different head types of insertion depth adaptation like this.
By using the distribution of the brain magnetic field measured by the OPM, if the relative position of each probe and the cerebral cortex to be tested can be known, under a proper source model, the position of the neuron which is activated by stimulation on the cortex can be uniquely determined, and the process is also called a source tracing analysis. The analysis of MEG tracing can be used to study various cranial nerve activity processes including spontaneous and evoked activity of the brain, and is clinically used to locate epileptic focus.
To obtain the position of the probe relative to the cerebral cortex, it is necessary to separately obtain the position of the probe relative to the head to be examined and the position of the cerebral cortex in the head to be examined, the latter being provided by the magnetic resonance structure image, while the former requires the development of a localization technique. Since the OPM arrays are not fixed but are inserted one by one on the magnetoencephalography cap, and the insertion depth is adjustable, each OPM needs to be positioned separately. How to quickly and accurately position all OPMs is a difficulty that must be overcome.
Disclosure of Invention
Aiming at the existing restriction limitation, the invention provides a rapid optical scanning positioning method of an OPM array based on space mark points, which realizes rapid and accurate positioning of all OPMs by setting a helmet coordinate system, obtaining three-dimensional image coordinates by means of optical scanning and carrying out image registration by means of the space mark points and a registration algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a space mark point-based OPM array rapid optical scanning positioning method, which is used for obtaining the position of OPM relative to cerebral cortex and is characterized in that,
the method is realized by the following steps:
s1, establishing a helmet coordinate system according to the characteristics of the rigid helmet to obtain helmet coordinate system coordinates of all slots on the rigid helmet;
s2, arranging space mark points on the rigid helmet and acquiring helmet coordinate system coordinates of all the space mark points;
s3, acquiring three-dimensional images of the rigid helmet, the tested head and all OPMs through optical scanning;
s4, directly reading the three-dimensional image coordinates of the space mark points from the three-dimensional image of the rigid helmet, and carrying out image registration on the three-dimensional image coordinates of the space mark points and the helmet coordinate system coordinates thereof to obtain a first coordinate transformation relation;
s5, directly reading three-dimensional image coordinates of the space mark points attached to all OPMs from the three-dimensional images of the OPMs, and performing coordinate system transformation through a first coordinate transformation relation to obtain helmet coordinate system coordinates of all OPMs;
s6, obtaining the corresponding relation between the slot and the OPM;
s7, obtaining a head image reconstructed from the magnetic resonance structural image, and carrying out image registration on the head image and the three-dimensional image of the tested head to obtain a second coordinate transformation relation;
s8, acquiring magnetic resonance structural image coordinates of a cerebral cortex part in the head image, and transforming the magnetic resonance structural image coordinates through a second coordinate transformation relation and a first coordinate transformation relation respectively to obtain helmet coordinate system coordinates of the cerebral cortex; the relative position of the OPM and the cerebral cortex is obtained through the relation between the helmet coordinate system coordinate of the OPM and the helmet coordinate system coordinate of the cerebral cortex.
Compared with the prior art, the invention has the following advantages:
(1) The method of the invention uses optical scanning to obtain the OPM array and the tested head image, has high sampling speed, and saves time and labor;
(2) The positions of all OPMs are quickly obtained from the optically scanned three-dimensional image by using the space mark points and the priori knowledge of the slots on the rigid helmet, and the positions of the OPMs can be quickly corresponding to the slots (slot numbers).
(3) The three-dimensional image of the tested head and the head image reconstructed by the magnetic resonance structure image are used for registration, and an algorithm combining global registration and ICP local optimization is adopted for image registration, so that automatic registration can be realized, and the method has the advantage of high precision.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
Drawings
Fig. 1 is a schematic structural view of a rigid helmet according to an embodiment of the present invention.
Fig. 2 is a flowchart of an OPM array fast optical scanning positioning method based on spatial marker points according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a point feature histogram extraction method according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a Darboux coordinate system of the point feature histogram extraction method according to the embodiment of the present invention.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. For a further understanding of the present invention, reference will now be made in detail to the preferred embodiments of the present invention.
The following is an explanation of the embodiments of the present invention relating to noun terms:
OPM: the magnetometer is manufactured by utilizing the principle of observing the magnetic resonance effect by utilizing circularly polarized light to excite a gas atom system in a magnetic field to be measured to generate the particle number difference between Zeeman sub energy levels; OPM is mainly used for measuring weak magnetic fields.
Rigid helmets: namely, the helmet for fixing the OPM is made of a rigid material, as shown in fig. 1, the rigid helmet, in combination with the helmet positioning mark points and the detector positioning mark points, meets the requirements of the OPM array rapid optical scanning positioning method. The rigid helmet comprises a fixed base and a module which can move in a small range to adjust the size of the interior of the helmet, and after the helmet is tried to be worn, the size of the helmet can be adjusted to fit the head type of the helmet to be tested as much as possible. The helmet is provided with slots for fixing the OPM, and the inserting depth of the OPM can be adjusted in the slots.
The following specifically describes implementations of the present invention in conjunction with the foregoing noun terms:
the invention provides a space mark point-based OPM array rapid optical scanning positioning method, which is used for obtaining the position of OPM relative to cerebral cortex;
referring to fig. 2, the method is implemented by the following steps:
s1, establishing a helmet coordinate system according to the characteristics of the rigid helmet to obtain helmet coordinate system coordinates of all slots on the rigid helmet;
s2, arranging space mark points on the rigid helmet and acquiring helmet coordinate system coordinates of all the space mark points;
s3, acquiring three-dimensional images of the rigid helmet, the tested head and all OPMs through optical scanning;
s4, directly reading the three-dimensional image coordinates of the space mark points from the three-dimensional image of the rigid helmet, and carrying out image registration on the three-dimensional image coordinates of the space mark points and the helmet coordinate system coordinates thereof through a first image registration algorithm to obtain a first coordinate transformation relation;
the first coordinate transformation relation is a coordinate transformation relation between the coordinates of the helmet coordinate system and the coordinates of the three-dimensional image;
s5, directly reading three-dimensional image coordinates of space marking points attached to all OPMs from the three-dimensional images of the OPMs, and performing coordinate system transformation through a first coordinate transformation relation to obtain helmet coordinate system coordinates of all OPMs;
s6, obtaining the corresponding relation between the slot and the OPM through a first matching rule;
s7, obtaining a head image reconstructed from the magnetic resonance structural image, and carrying out image registration on the head image and the three-dimensional image of the tested head to obtain a second coordinate transformation relation;
the second coordinate transformation relation is a coordinate transformation relation between the three-dimensional image coordinate and the magnetic resonance structure image coordinate;
s8, acquiring magnetic resonance structure image coordinates of a cerebral cortex part in the head image, transforming the magnetic resonance structure image coordinates through a second coordinate transformation relation to obtain three-dimensional image coordinates of the cerebral cortex, and transforming the three-dimensional image coordinates of the cerebral cortex through a first coordinate transformation relation to obtain helmet coordinate system coordinates of the cerebral cortex; the relative position of the OPM and the cerebral cortex is obtained through the relation between the helmet coordinate system coordinate of the OPM and the helmet coordinate system coordinate of the cerebral cortex.
The helmet coordinate system is a three-dimensional coordinate system; the three-dimensional image coordinate is a coordinate under a coordinate system defined during optical scanning, and meets the size of a real space; the magnetic resonance structure image coordinates are coordinates in a coordinate system defined by the magnetic resonance scanning apparatus.
When the steps S1-8 are executed sequentially, the position of the OPM relative to the cerebral cortex can be obtained, namely, the rapid optical scanning positioning method of the OPM array is realized; the OPM array consists of all OPMs.
As an embodiment, the helmet coordinate system is a three-dimensional coordinate system;
the method for establishing the helmet coordinate system comprises the following steps: when the rigid helmet is fixed on the scanning bed, the helmet coordinate system takes the center of the rigid helmet as an origin, the plane where the scanning bed is located is an X-Y plane, the direction from the tested head to the feet is an X-axis direction, and the vertical upward direction perpendicular to the scanning bed is a Z-axis direction.
The three-dimensional image coordinates are coordinates in a coordinate system defined during optical scanning, and the size of a real space is met.
The magnetic resonance structure image coordinates are coordinates in a coordinate system defined by the magnetic resonance scanning apparatus.
As an embodiment, the space mark points are reflective bright sheets, the reflective bright sheets have brightness values different from those of conventional materials (such as silver-plated stainless steel and reflective PU) during optical scanning, and the number of the space mark points is 5-10.
The spatial marker in step S5 may be fixedly assembled to the OPM before the method of the present invention is performed, or may be assembled to the OPM when any step of the method of the present invention is performed before step S3; the OPM fits into a slot of the rigid helmet before step S3 is performed.
As an embodiment, the optical scanning includes laser reflection positioning, structured light scanning positioning, and binocular camera positioning.
As an embodiment, the three-dimensional image includes reflection brightness information of the scanned object, where the reflection brightness information includes a gray value, a three-dimensional point cloud reconstructed according to a shape of the scanned object, and a patch formed by linking the three-dimensional point cloud.
As an embodiment, the first matching rule comprises:
and comparing the helmet coordinate system coordinates of all the OPMs with the helmet coordinate system coordinates of all the slots, wherein if the helmet coordinate system coordinate of a certain OPM is within a preset coordinate range of the helmet coordinate system coordinate of a certain slot, the OPM is the OPM in the slot.
As an example, the preset coordinate range is obtained as follows: the range is estimated from the distribution of slots on the helmet, which should ensure that the OPM does not fall within the range of two slots simultaneously, which is the euclidean distance perpendicular to the slot axis.
As an embodiment, the first image registration algorithm is implemented by:
respectively calculating a three-dimensional image coordinate point set P and a helmet coordinate system point set P * And extracting eigenvectors V and V of the matrix * (ii) a The three-dimensional image coordinate point set is a point set formed by three-dimensional image coordinates of the space mark points, and the helmet coordinate system point set is a point set formed by helmet coordinate system coordinates of the space mark points;
respectively calculating a three-dimensional image coordinate point set P (P) 1 ,p 2 ,p 3 …p n ) And helmet coordinate system point set
And extracting the eigenvectors (V) of the matrix 1 ,V 2 ,V 3 ) And
the three-dimensional image coordinate point set is a point set formed by three-dimensional image coordinates of the space marking points, and the helmet coordinate system point set is a point set formed by helmet coordinate system coordinates of the space marking points;
set of points P and P * Respectively of c and c * Then the transformation matrix Trans between the two point sets is:
wherein, the first and the second end of the pipe are connected with each other,
T＝c * -Rc；
acting Trans on P, then P and P * Approximately match, distance in P
Nearest point p j And
establishing point pairs, and obtaining P after reordering a (p 1 ,p 2 ,p 3 …p n ) And
wherein p is i And
is the nearest point pair;
calculating a point set P according to a least square estimation method a And
is optimally spatially transformed such that
Minimum;
definition of
c a ,
Representing the center of mass,
singular value decomposition is carried out on H to obtain U lambada V t And then:
finally, obtaining a space transformation matrix from the three-dimensional image coordinate system to the helmet coordinate system:
as an embodiment, the second registration algorithm adopts a combination algorithm of global registration and Iterative-Closest-Points (ICP) local optimization, and the algorithm is as follows:
calculating a Fast-Point-Feature-Histogram (Fast-Point-Feature-Histogram) of the head image reconstructed by the tested head three-dimensional image and the magnetic resonance structural image to obtain the global features of the two three-dimensional images;
selecting a set of points Q (Q) of similar global features in a two-dimensional three-dimensional image 1 ,q 2 ,q 3 …q n ) And
then obtaining the optimal space transformation Trans between two point sets according to the flow of the first image registration algorithm 0 (ii) a The global feature is a point feature histogram distribution feature.
Will Trans 0 Acting on the three-dimensional image of the tested head, roughly fitting the three-dimensional image of the tested head and the head image reconstructed from the magnetic resonance structural image (namely preliminarily fitting the three-dimensional image of the tested head and the head image reconstructed from the magnetic resonance structural image), and then optimizing the registration result of the two images through an iterative nearest neighbor algorithm to obtain a more accurate spatial transformation matrix.
As an embodiment, the fast Point Feature Histogram is based on a Point-Feature Histogram (PFH), which is a global Feature, and a multidimensional Histogram is formed by parameterizing spatial differences between a query Point and neighbor points so as to geometrically describe the neighbors of a Point; the information provided by the histogram has translational and rotational invariance to the point cloud and robustness to sampling density and noise points. PFH describes geometric features based on the relationship between points and their neighbors and their estimated normals.
The extraction method of the point feature histogram comprises the following steps:
as shown in fig. 3, for any point p in the three-dimensional image, k adjacent points are selected, wherein p is taken as the center of a circle and r is taken as the radius;
as shown in fig. 4, two points p are arbitrarily selected from k adjacent points 1 ，p 2 And their corresponding normal vectors n at that point 1 ,n 2 Computing a Darboux coordinate system (u, v, w), wherein
u＝n 1
v＝u×(p 2 -p 1 )
W＝u×V
Calculating PFH characteristic value (alpha, phi, theta) under Darboux coordinate system, wherein the PFH characteristic value is n 1 And n 2 Angle difference of (1), wherein
α＝V·n 2
θ＝arctan(w·n 2 ,u·n 2 )
Computing a triplet (α, φ, θ) for all point pairs in the k neighborhood; a total of k points, then the result is
A triplet; dividing each value in the triple into b intervals, and then establishing a histogram by taking the whole triple as a parameter, wherein the histogram has b 3 A section;
count this
And forming a PFH point feature histogram by the frequency of the triad in each interval.
As an embodiment, the iterative nearest neighbor algorithm is implemented by:
selecting point pairs with the shortest Euclidean distances on the two images, and matching the point pairs one by one;
based on least square estimation, calculating the optimal rigid transformation between two point sets by utilizing SVD matrix decomposition, reselecting the point pair with the closest Euclidean distance on the two images according to the transformation function and the two images, and calculating the optimal rigid transformation between the two point sets;
and repeating the process until the phase difference ratio between the rigid transformations obtained by two adjacent iterations is smaller than a preset value, namely outputting the final rigid transformation, wherein the preset value is usually 0.0001.
As an example, the methods of the present invention may be implemented in software and/or a combination of software and hardware, for example, using Application Specific Integrated Circuits (ASICs), a general purpose computer or any other similar hardware devices.
The method of the present invention may be implemented in the form of a software program that is executable by a processor to perform the steps or functions described above. As such, the software programs (including associated data structures) may be stored on a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like.
Additionally, some of the steps or functions of the methods of the present invention may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, a part of the method according to the present invention may be applied as a computer program product, such as computer program instructions, which, when executed by a computer, may invoke or provide the method and/or technical solution according to the present application through the operation of the computer. Program instructions for carrying out the methods of the present invention may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium, and/or stored in a working memory of a computer device operating in accordance with the program instructions.
The present invention also provides, as an embodiment, an apparatus including a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a technical solution according to the foregoing embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.
Finally, it is noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or terminal apparatus that comprises the element.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An OPM array rapid optical scanning positioning method based on spatial mark points is characterized by comprising the following steps:
s1, establishing a helmet coordinate system according to the characteristics of the rigid helmet to obtain helmet coordinate system coordinates of all slots on the rigid helmet;
s2, arranging space mark points on the rigid helmet and acquiring helmet coordinate system coordinates of all the space mark points;
s3, acquiring three-dimensional images of the rigid helmet, the tested head and all OPMs through optical scanning;
s4, directly reading the three-dimensional image coordinates of the space mark points from the three-dimensional image of the rigid helmet, and carrying out image registration on the three-dimensional image coordinates of the space mark points and the helmet coordinate system coordinates thereof to obtain a first coordinate transformation relation;
s5, directly reading three-dimensional image coordinates of the space mark points attached to all OPMs from the three-dimensional images of the OPMs, and performing coordinate system transformation through a first coordinate transformation relation to obtain helmet coordinate system coordinates of all OPMs;
s6, acquiring the corresponding relation between the slot and the OPM;
s7, obtaining a head image reconstructed from the magnetic resonance structural image, and carrying out image registration on the head image and the three-dimensional image of the tested head to obtain a second coordinate transformation relation;
s8, obtaining magnetic resonance structural image coordinates of a cerebral cortex part in the head image, and transforming the magnetic resonance structural image coordinates through a second coordinate transformation relation and a first coordinate transformation relation respectively to obtain helmet coordinate system coordinates of the cerebral cortex; the relative position of the OPM and the cerebral cortex is obtained through the relation between the helmet coordinate system coordinate of the OPM and the helmet coordinate system coordinate of the cerebral cortex.
2. The method of claim 1,
the first coordinate transformation relation is a coordinate transformation relation between the coordinates of the helmet coordinate system and the coordinates of the three-dimensional image;
the second coordinate transformation relation is a coordinate transformation relation between the three-dimensional image coordinate and the magnetic resonance structure image coordinate;
the first coordinate transformation relation and the second coordinate transformation relation are both space transformation matrixes.
3. The method of claim 1,
in step S6, obtaining the corresponding relationship between the slot and the OPM is implemented by a first matching rule, where the first matching rule includes: and comparing the helmet coordinate system coordinates of all the OPMs with the helmet coordinate system coordinates of all the slots, wherein if the helmet coordinate system coordinate of a certain OPM is within a preset coordinate range of the helmet coordinate system coordinate of a certain slot, the OPM is the OPM in the slot.
4. The method of claim 1,
the helmet coordinate system is a three-dimensional coordinate system;
the three-dimensional image coordinate is a coordinate under a coordinate system defined during optical scanning, and meets the size of a real space;
the magnetic resonance structure image coordinates are coordinates in a coordinate system defined by the magnetic resonance scanning device.
5. The method of claim 1,
the space mark points are reflective paillettes with high brightness values;
the optical scanning comprises one or more of laser reflection positioning, structured light scanning positioning and binocular camera positioning.
6. The method of claim 1,
the three-dimensional image comprises reflection brightness information of a scanned object, and the reflection brightness information comprises a gray value, a three-dimensional point cloud reconstructed according to the shape of the scanned object and a surface patch formed by linking the three-dimensional point cloud.
7. The method of claim 3,
the preset coordinate range is obtained according to the following mode: the range is estimated based on the distribution of the slots on the helmet, and should be such that the OPM does not fall within the range of two slots simultaneously, which is the euclidean distance perpendicular to the slot axis.
8. The method of claim 1,
in step S4, a first image registration algorithm is adopted for image registration;
the first image registration algorithm is implemented by:
(1) Respectively calculating a three-dimensional image coordinate point set P and a helmet coordinate system point set P * And extracting eigenvectors V and V of the matrix * (ii) a The three-dimensional image coordinate point set is a point set formed by three-dimensional image coordinates of the space marking points, and the helmet coordinate system point set is a point set formed by helmet coordinate system coordinates of the space marking points;
(2) Calculating P and P * The transformation matrix of (2) Trans;
(3) Mixing P with P * The points in (1) are reordered according to the nearest matching method to obtain P a And P a * ；
(4) Obtaining P according to least square estimation a And P a * To obtain the final spatial transformation matrix.
9. The method of claim 1,
in step S7, a second image registration algorithm is adopted for image registration;
the second image registration algorithm is a combination algorithm of global registration and local optimization of an iterative nearest neighbor algorithm, and is realized by the following steps:
(1) Calculating a fast point feature histogram of a three-dimensional image of the tested head and a head image reconstructed from the magnetic resonance structural image to obtain global features of the two images;
(2) Selecting point sets Q and Q of similar global features in the two images * Calculating to obtain the optimal space transformation Trans between two point sets 0 ；
(3) Will Trans 0 Acting on the three-dimensional image of the tested head, and preliminarily fitting the three-dimensional image of the tested head and the head image reconstructed from the magnetic resonance structural image;
(4) And optimizing the registration result of the two images by an iterative nearest neighbor algorithm to obtain a final spatial transformation matrix.
10. An electronic device is characterized in that a first electronic component is connected to a second electronic component,
the electronic device comprises a memory and a processor; the memory having stored therein a computer program arranged to execute the method of any of claims 1-9; the processor is arranged to run the computer program to perform the method according to any of claims 1-9.
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| CN116392132B (en) * | 2023-06-07 | 2023-09-15 | 季华实验室 | Flexible brain magnetic head helmet and sensor array space positioning method thereof |
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