CN106344154B - A kind of scaling method of the surgical instrument tip point based on maximal correlation entropy - Google Patents
A kind of scaling method of the surgical instrument tip point based on maximal correlation entropy Download PDFInfo
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Abstract
The invention belongs to the Technology of surgery navigation fields of optical alignment, a kind of scaling method of the surgical instrument tip point based on maximal correlation entropy is provided, this method can be under non-Gaussian noise, the state of surgical instrument point is estimated and tracked using binocular vision, by completing the point calibration of surgical instrument tip.This method includes：1) optical system based on binocular vision obtains the rotation image of surgical instrument to be calibrated；2) the flat image coordinate and space coordinate of surgical instrument index point are obtained；3) it clicks through rower to operation instrument tip to determine, the space coordinate of surgical instrument tip point is sought based on maximal correlation entropy criterion, complete the calibration of surgical instrument tip point.Experiments have shown that inventive algorithm is functional, in true engineer application, it can realize and operation instrument tip point is accurately demarcated.
Description
Technical Field
The invention belongs to the technical field of surgical navigation of optical positioning, relates to a method for calibrating a tip point of a surgical instrument of binocular vision under non-Gaussian noise, and particularly relates to a method for calibrating a tip point of a surgical instrument based on maximum correlation entropy.
Background
The core work of the surgical navigation is to track the position and direction of various instruments in the operation, and aiming at the need of tracking the tip point of the surgical instrument in the interventional operation, the common method is to set three or more non-collinear mark points on the surgical instrument, position the positions of the three mark points by using an optical tracking system, calibrate the tip point of the surgical instrument before the operation, and calculate the position of the tip point in the surgical instrument.
When the position of the mark point can not be accurately identified, the mark point is shaken, and can be characterized by impulsive noise. The existing method for calibrating the tip point of the surgical instrument through binocular vision is mainly based on the least square criterion, and the performance of the method is rapidly degraded under impulse noise, so that the problem needs to be further researched.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a surgical instrument tip point calibration method based on the maximum correlation entropy criterion, which has strong inhibition capability on non-Gaussian noise and can realize more accurate calibration on the surgical instrument tip point.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a surgical instrument tip point calibration method based on maximum correlation entropy comprises the following steps:
firstly, acquiring a rotating image of the surgical instrument to be calibrated based on an optical system of binocular vision.
1) Fixing the tip point of the surgical instrument, and rotating the surgical instrument around the tip point;
2) and acquiring an image by using a binocular vision optical system.
And secondly, acquiring plane image coordinates and space coordinates of the marking points of the surgical instruments.
1) Identifying the mark points on the surgical instruments in the images acquired by the binocular vision optical system by using an image identification method;
2) and calculating the space coordinates of the mark points by using a three-dimensional reconstruction algorithm.
And thirdly, calibrating the tip point of the surgical instrument.
1) Establishing a calibration equation set;
2) and (4) solving the space coordinate of the surgical instrument tip point based on the maximum correlation entropy criterion, and completing the calibration of the surgical instrument discontinuity point.
The invention has the beneficial effects that: the method can overcome impulse noise caused by inaccurate identification of the mark points of the surgical instruments under the condition of non-Gaussian noise, and has better application prospect in the practice of binocular identification surgical navigation.
Drawings
FIG. 1 is a schematic view of a surgical instrument, in which m is1、m2、m3、m4Four small balls reflecting infrared light; tip is the Tip point of the surgical instrument; xNAxis, YNAxis, ZNThe axes are three coordinate axes of a coordinate system N of the surgical instrument;
FIG. 2 is a schematic view of the surgical instrument rotated about the tip point;
FIG. 3 is a binocular vision system based surgical instrument landmark acquisition view;
FIG. 4 is a three-dimensional reconstruction of the surgical instrument marker points and tip points;
FIG. 5 is a flow chart embodying the present invention.
Detailed Description
In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the following describes the technical solution in the embodiments of the present invention clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and a specific flowchart is shown in fig. 5:
firstly, acquiring a rotating image of the surgical instrument to be calibrated based on an optical system of binocular vision.
1) The tip point of the surgical instrument is fixed. Referring to FIG. 1, m1,m2,m3,m4The infrared light reflecting small balls are provided, and the centers of the small balls are the mark points of the surgical instruments; the three coordinate axes of the surgical instrument coordinate system N are specifically:is XNAxis, passing point m1Perpendicular to XNStraight line of the axis being YNAxis, origin ONIs XNAxis and YNIntersection of axes, passing through origin ONPerpendicular to plane ONXNYNIs a straight line of ZNA shaft.
2) Rotating the surgical instrument around its tip point, see fig. 2, and using a binocular vision optical system for image acquisition, and numbering each image in the order of acquisition, with the picture number L acquired by the left camera1，L2，…，LNThe picture number collected by the right camera is R1，R2，…，RNThe total number is 2N pictures. See fig. 2.
Secondly, acquiring plane image coordinates and space coordinates of the marking points of the surgical instruments
1) Identifying the mark points on the surgical instruments in the images acquired by the binocular vision optical system acquired in the first step 2) by using an image identification method; and the image coordinates thereof are respectively noted as,
pLn,m＝[uLn,m,vL,nm]Tand pRn,m＝[uRn,m,vRn,m]T(1)
Where L and R in the subscripts denote a left camera and a right camera, respectively, N (N ═ 1, …, N) denotes the order of image acquisition, and m (m ═ 1,2,3,4) denotes the order of marker points; u and v are the coordinates of the pixel image of the mark point. See fig. 3.
2) Obtaining the three-dimensional space coordinate x of the mark point of the surgical instrument by using the three-dimensional reconstruction formula and the coordinate of the mark point of the surgical instrument in the image obtained in the second step (1)n,m＝[xn,m,yn,m,zn,m]T。
The three-dimensional reconstruction formula is as follows:
wherein,andrespectively representing the projection matrixes calibrated by the left camera and the right camera; z is a radical ofLn,mAnd zRn,mThree-dimensional coordinate points in the Z axes of the left and right cameras respectively; [ u ] ofLn.m,vLn,m,1]TAnd [ u ]Rn,m,vRn,m,1]TIs pLn,mAnd pRn,mHomogeneous coordinates under a pixel coordinate system; [ x ] ofn,m,yn,m,zn,m,1]TIs a mark point xn,mHomogeneous coordinates in a world coordinate system;
simultaneous equations (2) and (3) yields:
and (3) solving a formula (4) by adopting a least square method, wherein the obtained optimal solution is the space coordinate of the mark point of the surgical instrument.
And thirdly, calibrating the tip point of the surgical instrument.
1) A calibration equation set is established as follows:
the radius formula of the spherical surface where the mth mark point is located is as follows
(xn,m-xtip)2+(yn,m-ytip)2+(zn,m-ztip)2＝r2(5)
Wherein the coordinate of the tip point of the surgical instrument is xtip＝[xtip,ytip,ztip]T(ii) a r is the radius of the sphere where the marker point of the surgical instrument is located when the surgical instrument rotates around the tip point; x is the number ofn,m、yn,m、zn,mSpatial coordinates of a landmark point on the surgical instrument;
the above equation has n × m equations, and the equation in the first row is subtracted, so that:
2) with xtip＝[xtip,ytip,ztip]TAs the coefficients of the FIR filter to be estimated, the coefficients to the left of the equal sign of each equation in the calibration equation set (6) are taken as the filter input, denoted u (l) ═ xlm-x1m,ylm-y1m,zlm-z1m]T(l ═ 2,3,. n), the constant term to the right of the equal sign, as the desired output, written as:
estimating the coefficient of the FIR filter by taking the recursive maximum correlation entropy as an adaptive filtering algorithm, wherein an iterative formula is as follows:
e(l)＝d(l)-uT(l)w(l-1) (7)
w(l)＝w(l-1)+e(l)k(l) (9)
wherein u (l) is the filter input sequence; d (l) is the desired output sequence; l is represented as a sequence of data; e (l) is the observation error; w (l) is the weight of the filter, w (1) is 0; λ ═ 0.99 is the forgetting factor; k (l) is a gain vector; pσIs the inverse of the autocorrelation matrix, P (1) ═ λ-1I；κσ(·)＝exp(-(·)2/σ2) Representing a gaussian kernel function. Thereby realizing the calibration of the surgical instrument tip point. See fig. 4.
Claims (1)
1. A surgical instrument tip point calibration method based on maximum correlation entropy is characterized by comprising the following steps:
firstly, acquiring a rotating image of a surgical instrument to be calibrated based on an optical system of binocular vision
1) Fixing the tip point of the surgical instrument;
2) rotating the surgical instrument around the tip point of the surgical instrument, acquiring images by using a binocular vision optical system, numbering each image according to an acquisition sequence, wherein the images acquired by a left camera are numbered as L1, L2, … and LN, the images acquired by a right camera are numbered as R1, R2, … and RN, and the number of the images is 2N;
secondly, acquiring the plane image coordinates and three-dimensional space coordinates of the marking points of the surgical instruments
1) Identifying the surgical instrument mark points in the image obtained in the first step 2) by using an image identification method; and respectively recording the coordinates p of the plane image of the mark point of the surgical instrument as:
pLn,m＝[uLn,m,vL,nm]Tand pRn,m＝[uRn,m,vRn,m]T(1)
Wherein L and R in the subscripts denote a left camera and a right camera, respectively; n denotes the order of image acquisition, N is 1, …, N; m represents the sequence of the mark points of the surgical instrument, and m is 1,2,3, 4; u and v are pixel coordinates of the mark points of the surgical instruments;
2) obtaining the three-dimensional space coordinate x of the surgical instrument mark point by using the three-dimensional reconstruction formula and the coordinate of the surgical instrument mark point in the image obtained in the second step 1)n,m＝[xn,m,yn,m,zn,m]T；
The three-dimensional reconstruction formula is as follows:
wherein,andrespectively representing the projection matrixes calibrated by the left camera and the right camera; z is a radical ofLn,mAnd zRn,mThree-dimensional space coordinate points of the left camera and the right camera in the Z axis respectively; [ u ] ofLn.m,vLn,m,1]TAnd [ u ]Rn,m,vRn,m,1]TIs pLn,mAnd pRn,mHomogeneous coordinates under a pixel coordinate system; [ x ] ofn,m,yn,m,zn,m,1]TMarking points x for surgical instrumentsn,mHomogeneous coordinates in a world coordinate system;
simultaneous equations (2) and (3) yields:
solving a formula (4) by adopting a least square method, wherein the obtained optimal solution is the three-dimensional space coordinate of the mark point of the surgical instrument;
thirdly, calibrating the tip point of the surgical instrument
1) A calibration equation set is established as follows:
the radius formula of the spherical surface where the mth surgical instrument mark point is located is as follows:
(xn,m-xtip)2+(yn,m-ytip)2+(zn,m-ztip)2＝r2(5)
wherein the coordinate of the tip point of the surgical instrument is xtip＝[xtip,ytip,ztip]T(ii) a r is the radius of the sphere where the surgical instrument mark point is located when the surgical instrument rotates around the tip point; x is the number ofn,m、yn,m、zn,mMarking the three-dimensional space coordinates of the points for the surgical instrument;
from equation (5), a calibration equation set as shown in equation (6) is obtained:
2) with xtip＝[xtip,ytip,ztip]TAs the coefficients of the FIR filter to be estimated; taking the coefficient on the left of the equal sign of each equation in the calibration equation set as the input of the FIR filter, and recording the coefficient as u (l); taking a constant term on the right side of the equal sign of each equation in the calibration equation set as expected output, and recording the constant term as d (l);
u(l)＝[xlm-x1m,ylm-y1m,zlm-z1m]T,(l＝2,3,..,n)
iteration is carried out by taking the maximum recursive correlation entropy as a self-adaptive filtering algorithm, and the coefficient of the FIR filter is estimated to realize the calibration of the tip point of the surgical instrument;
the iterative formula is as follows:
e(l)＝d(l)-uT(l)w(l-1) (7)
w(l)＝w(l-1)+e(l)k(l) (9)
wherein u (l) is the FIR filter input sequence; d (l) is the desired output sequence; l is represented as a sequence of data; e (l) is the observation error; w (l) is the weight of the FIR filter, w (1) is 0; λ ═ 0.99 is the forgetting factor; k (l) is a gain vector; pσIs the inverse of the autocorrelation matrix, P (1) ═ λ-1I；κσ(·)＝exp(-(·)2/σ2) Representing a gaussian kernel function.
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| CN107550576A (en) * | 2017-10-26 | 2018-01-09 | 上海逸动医学科技有限公司 | Space positioning apparatus and localization method, rectifier, antidote |
| CN110811834B (en) * | 2019-11-22 | 2021-07-02 | 苏州微创畅行机器人有限公司 | Checking method and checking system of osteotomy guiding tool and detection target |
| CN112168240B (en) * | 2020-09-24 | 2022-03-01 | 武汉联影智融医疗科技有限公司 | Surgical instrument calibration method and device, computer equipment and storage medium |
| CN112568995A (en) * | 2020-12-08 | 2021-03-30 | 南京凌华微电子科技有限公司 | Bone saw calibration method for robot-assisted surgery |
| CN113313754A (en) * | 2020-12-23 | 2021-08-27 | 南京凌华微电子科技有限公司 | Bone saw calibration method and system in surgical navigation |
| CN114005022B (en) * | 2021-12-30 | 2022-03-25 | 四川大学华西医院 | Dynamic prediction method and system for surgical instrument |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2587369Y (en) * | 2002-08-15 | 2003-11-26 | 刘道平 | Electromagnetic operation navigation apparatus based on C type X-ray unit |
| WO2006029541A1 (en) * | 2004-09-15 | 2006-03-23 | Ao Technology Ag | Calibrating device |
| CN101249003A (en) * | 2007-01-31 | 2008-08-27 | 韦伯斯特生物官能公司 | Correlation of ultrasound images and gated position measurements |
| CN103325143A (en) * | 2013-06-13 | 2013-09-25 | 华南理工大学 | Mark point automatic registration method based on model matching |
| WO2014005225A1 (en) * | 2012-07-03 | 2014-01-09 | 7D Surgical Inc. | Attachments for tracking handheld implements |
| CN103654965A (en) * | 2013-12-03 | 2014-03-26 | 华南理工大学 | Mark point used for optical surgical navigation system and image extraction method |
| CN103908346A (en) * | 2012-12-31 | 2014-07-09 | 复旦大学 | High-precision automatic neuronavigation space registration method |
| CN103948431A (en) * | 2014-04-14 | 2014-07-30 | 华南理工大学 | Tracer design method applied to surgery navigation mark point error indication |
| CN104361627A (en) * | 2014-11-07 | 2015-02-18 | 武汉科技大学 | SIFT-based (scale-invariant feature transform) binocular vision three-dimensional image reconstruction method of asphalt pavement micro-texture |
| CN105055021A (en) * | 2015-06-30 | 2015-11-18 | 华南理工大学 | Calibration device and calibration method for surgical navigation puncture needle |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2328500B1 (en) * | 2008-06-11 | 2017-03-22 | Dune Medical Devices Ltd. | Double registration |
| DE102010042540B4 (en) * | 2010-10-15 | 2014-09-04 | Scopis Gmbh | Method and apparatus for calibrating a distance determining device of an optical system |
-
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- 2016-09-14 CN CN201610821462.9A patent/CN106344154B/en not_active Expired - Fee Related
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2587369Y (en) * | 2002-08-15 | 2003-11-26 | 刘道平 | Electromagnetic operation navigation apparatus based on C type X-ray unit |
| WO2006029541A1 (en) * | 2004-09-15 | 2006-03-23 | Ao Technology Ag | Calibrating device |
| CN101249003A (en) * | 2007-01-31 | 2008-08-27 | 韦伯斯特生物官能公司 | Correlation of ultrasound images and gated position measurements |
| WO2014005225A1 (en) * | 2012-07-03 | 2014-01-09 | 7D Surgical Inc. | Attachments for tracking handheld implements |
| CN103908346A (en) * | 2012-12-31 | 2014-07-09 | 复旦大学 | High-precision automatic neuronavigation space registration method |
| CN103325143A (en) * | 2013-06-13 | 2013-09-25 | 华南理工大学 | Mark point automatic registration method based on model matching |
| CN103654965A (en) * | 2013-12-03 | 2014-03-26 | 华南理工大学 | Mark point used for optical surgical navigation system and image extraction method |
| CN103948431A (en) * | 2014-04-14 | 2014-07-30 | 华南理工大学 | Tracer design method applied to surgery navigation mark point error indication |
| CN104361627A (en) * | 2014-11-07 | 2015-02-18 | 武汉科技大学 | SIFT-based (scale-invariant feature transform) binocular vision three-dimensional image reconstruction method of asphalt pavement micro-texture |
| CN105055021A (en) * | 2015-06-30 | 2015-11-18 | 华南理工大学 | Calibration device and calibration method for surgical navigation puncture needle |
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