CN106344154A - Surgical instrument tip point calibration method based on maximum joint entropy - Google Patents

Surgical instrument tip point calibration method based on maximum joint entropy Download PDF

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CN106344154A
CN106344154A CN 201610821462 CN201610821462A CN106344154A CN 106344154 A CN106344154 A CN 106344154A CN 201610821462 CN201610821462 CN 201610821462 CN 201610821462 A CN201610821462 A CN 201610821462A CN 106344154 A CN106344154 A CN 106344154A
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surgical instrument
point
image
coordinates
calibration
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CN 201610821462
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邱天爽
吕丽明
朱永杰
栾声扬
张家成
丑远婷
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大连理工大学
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    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects

Abstract

The invention belongs to the technical field of optical positioning surgical navigation, and provides a surgical instrument tip point calibration method based on the maximum joint entropy. According to the method, under the non-Gaussian noise, binocular vision is used for performing estimation and tracking on the status of a surgical instrument tip, and the surgical instrument tip point is calibrated. The method comprises the following steps that 1, an optical system based on binocular vision obtains a rotating image of a surgical instrument to be calibrated; 2, plane image coordinates and space coordinates of a mark point of the surgical instrument are obtained; 3, the surgical instrument tip point is calibrated, on the basis of the maximum joint entropy criterion, space coordinates of the surgical instrument tip point are obtained, and the surgical instrument tip point is calibrated. Experiments prove that an algorithm performance is good, and in actual engineering application, the surgical instrument tip point can be accurately calibrated.

Description

一种基于最大相关熵的手术器械尖端点的标定方法 CALIBRATION METHOD surgical instrument center point based on the maximum correlation entropy

技术领域 FIELD

[0001] 本发明属于光学定位的手术导航技术领域,涉及非高斯噪声下一种双目视觉的手术器械尖端点标定方法,特别是涉及到一种基于最大相关熵的手术器械尖端点的标定方法。 [0001] The present invention belongs to the technical field of optical surgical navigation positioning, the tip point calibration method relates to non-Gaussian noise surgical instrument of binocular vision, particularly relates to a calibration method based on the surgical instrument tip to the point of maximum correlation entropy .

背景技术 Background technique

[0002] 手术导航的核心工作就是跟踪术中各种器械的位置和方向,针对介入式手术需要跟踪手术器械的尖端点,常用的方法是在手术器械上面设置三个或三个以上不共线的标志点,利用光学跟踪系统定位三个标志点的位置,术前标定手术器械尖端点,计算出尖端点在手术器械中的位置。 [0002] The surgical navigation core work is to track the position and orientation of the various surgical instruments, the need for surgical intervention the surgical instrument of the tracking center point, the commonly used method is a surgical instrument disposed above three or more non-colinear the landmarks, using an optical position location tracking system three mark point, center point calibration preoperative surgical instrument calculates the position of the center point of the surgical instrument.

[0003] 当标志点的位置无法准确识别时,就会出现标志点"抖动"的情况,可以用脉冲性的噪声对其进行刻画。 [0003] When the position of the marker point can not be accurately identified, the flag will be point "blur", the impulsive noise can be portrayed. 现有的通过双目视觉标定手术器械尖端点的方法主要是基于最小二乘准则的,此类方法在脉冲性噪声下性能迅速退化,故还需要对此问题进行进一步研究。 Conventional surgical instrument center point calibration method by binocular vision is mainly based on least squares criterion, such methods deteriorate rapidly under impulsive noise performance, it also requires further study this issue.

发明内容 SUMMARY

[0004] 针对现有技术的不足,本发明提供一种基于最大相关熵准则的手术器械尖端点标定方法,该方法是一种对非高斯噪声具有较强抑制能力标定方法,能够实现对手术器械尖端点较为准确的标定。 [0004] for the deficiencies of the prior art, the present invention provides a surgical instrument calibration method based on the center point of maximum correlation entropy criterion, which is a kind of non-Gaussian noise has a strong ability to inhibit the calibration method, the surgical instrument can be achieved center point more accurate calibration.

[0005] 为了达到上述目的,本发明的技术方案为: [0005] To achieve the above object, the technical solution of the present invention is:

[0006] -种基于最大相关熵的手术器械尖端点标定方法,包括以下步骤: [0006] - based on the maximum correlation entropy Species surgical instrument tip point calibration method, comprising the steps of:

[0007] 第一步,基于双目视觉的光学系统,获取待标定手术器械的旋转图像。 [0007] The first step, an optical system based on binocular vision, to be calibrated images acquired rotation of the surgical instrument.

[0008] 1)将手术器械尖端点进行固定,并将手术器械围绕此尖端点进行旋转; [0008] 1) The tip of the surgical instrument fixed point, and the surgical instrument is rotated around this center point;

[0009] 2)利用双目视觉光学系统进行图像采集。 [0009] 2) image acquisition optical system using binocular vision.

[0010] 第二步,获取手术器械标志点的平面图像坐标和空间坐标。 [0010] The second step, obtaining the surgical instrument of the mark point image coordinate and space coordinate plane.

[0011] 1)利用图像识别方法对双目视觉光学系统获取图像中的手术器械上标志点进行识别; [0011] 1) The method of acquiring image recognition mark points on the image of the surgical instrument of binocular vision optical system identification;

[0012] 2)利用三维重建算法计算标志点的空间坐标。 [0012] 2) the spatial coordinates of the mark point is calculated using three-dimensional reconstruction algorithm.

[0013]第三步,对手术器械尖端点进行标定。 [0013] The third step, the tip of the surgical instrument calibration point.

[0014] 1)建立标定方程组; [0014] 1) establish calibration equations;

[0015] 2)基于最大相关熵准则求取手术器械尖端点的空间坐标,通过完成手术器械间断点的标定。 [0015] 2) obtaining spatial coordinates of the surgical instrument based on the center point of maximum correlation entropy criterion, discontinuous point calibration by completing the surgical instrument.

[0016] 本发明的有益效果为:该方法能够在非高斯噪声条件下,克服由于手术器械标志点识别不准确所引入的脉冲性噪声,在双目识别手术导航实践中具有较好的应用前景。 [0016] Advantageous effects of the present invention is: in the process can be non-Gaussian noise conditions, impulse noise due to overcome the surgical instrument landmark recognition inaccuracies introduced, having a good prospect in practice binocular surgical navigation identification .

附图说明 BRIEF DESCRIPTION

[0017] 图1是手术器械结构示意图,图中mi、m2、m3、m4为四个反射红外光的小球;Tip为手术器械的尖端点;Xn轴、Yn轴、ZN轴为手术器械坐标系N的三个坐标轴; [0017] FIG. 1 is a schematic view of the structure of the surgical instrument, FIG mi, m2, m3, m4 four reflected infrared light beads; the Tip of the center point of the surgical instrument; axis Xn, Yn axis, the axis of the surgical instrument coordinate ZN N lines of the three axes;

[0018] 图2是围绕尖端点旋转手术器械的示意图; [0018] FIG. 2 is a schematic view of the surgical instrument to rotate about the center point;

[0019] 图3是基于双目视觉系统的手术器械标志点获取图; [0019] FIG. 3 is a surgical instrument based on the mark point acquired FIG binocular vision system;

[0020] 图4是手术器械标志点和尖端点的三维重建图; [0020] FIG. 4 is a three-dimensional reconstruction of the surgical instrument of FIG marker point and the center point;

[0021 ]图5是本发明具体流程图。 [0021] FIG. 5 is a detailed flowchart of the present invention.

具体实施方式 detailed description

[0022]为使本发明实施例的目的、技术方案及其优点更加清楚,下面结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚完整的描述,具体流程图如图5所示: [0022] The object of the present invention embodiment, the technical solution and merits thereof more apparent, the present invention in conjunction with the accompanying drawings in the following embodiments, the technical solutions in the embodiments of the present invention is a complete and clear description, a detailed flowchart of FIG. Figure 5:

[0023] 第一步,基于双目视觉的光学系统,获取待标定手术器械的旋转图像。 [0023] The first step, an optical system based on binocular vision, to be calibrated images acquired rotation of the surgical instrument.

[0024] 1)将手术器械的尖端点进行固定。 [0024] 1) The tip of the surgical instrument is a fixed point. 参见图1,图中血^⑩^为四个反射红外光的小球,小球的球心为手术器械的标志点;手术器械坐标系N的三个坐标轴具体为:为XN 轴,过点nu垂直于ΧΝ轴的直线为ΥΝ轴,原点On为ΧΝ轴与Υ Ν轴的交点,过原点On垂直于平面OnXnYn的直线为Zn轴。 Referring to Figure 1, the blood ^ ⑩ ^ is four pellets reflected infrared light, a small center of the sphere to the point of the surgical instrument marker; N surgical instrument coordinate system of the three axes is specifically: XN axis is, over nu vertical axis to point to the straight line ΧΝ ΥΝ axis, the origin of the intersection of the axis of v on ΧΝ Upsilon axis, perpendicular to the line through the origin on OnXnYn plane axis is Zn.

[0025] 2)将手术器械围绕其尖端点进行旋转,参见图2,并使用双目视觉光学系统进行图像采集,并对每幅图像按照采集的顺序进行编号,左面相机采集的图片编号为1^儿2,…,LN, 右面相机采集的图片编号为Ri,!^,···,!^,共为2N幅图片。 [0025] 2) rotating surgical instrument, see FIG. 2 around its center point, and binocular vision image pickup optical system, and each image are numbered in the order of acquisition, the camera captured image left numbered 1 child ^ 2, ..., LN, the right camera captured images numbered Ri,! ^, ···,! ^, for a total of 2N pictures. 参见图2。 See Figure 2.

[0026] 第二步,获取手术器械标志点的平面图像坐标和空间坐标 [0026] The second step, obtaining the surgical instrument of the mark point image coordinate and space coordinate plane

[0027] 1)利用图像识别方法对第一步2)获取的双目视觉光学系统获取图像中的手术器械上标志点进行识别;并将其图像坐标分别记为, [0027] 1) The method of acquiring image recognition mark points on the image of the surgical instrument identification Step 2) obtained by binocular vision optical system; and referred to as the image coordinates,

[0028] PLn,m= [uLn,m, VL,nm] ^PpRn,m= [uRn,m, VRn,m] (1) [0028] PLn, m = [uLn, m, VL, nm] ^ PpRn, m = [uRn, m, VRn, m] (1)

[0029] 其中,下标中的L和R分别表示左相机和右相机,η(η=1,···,Ν)表示图像采集的顺序,m(m=l,2,3,4)表示标志点的顺序;u、ν为标志点像素图像坐标。 [0029] wherein the subscripts L and R denote the left and right cameras, η (η = 1, ···, Ν) a sequence of image acquisition, m (m = l, 2,3,4) It represents a sequence of landmarks; u, ν is the mark point image pixel coordinates. 参见图3。 See Figure 3.

[0030] 2)利用三维重建公式以及第二步(1)中得到的手术器械标志点在图像中的坐标, 得到手术器械标志点的三维空间坐标Xn, m=[Xn,m,yn,m,Zn,m]T。 [0030] 2) and a second step using three-dimensional reconstruction of the formula (marker coordinate point surgical instrument 1) obtained in the image, to obtain a three-dimensional landmark surgical instrument spatial coordinates Xn, m = [Xn, m, yn, m , Zn, m] T.

[0031] 三维重建公式如下: [0031] The three-dimensional reconstruction of the following formula:

Figure CN106344154AD00051

[0034]其中,双£4和财fx4分别表示左侧和右侧摄像机标定的投影矩阵;zu,4Pz Rn,m分别为在左侧和右侧摄像机Z轴中的二维坐标点;[ULn.m, VLn,m,1]T和[URn,m,VRn,m,1]T是PLn,m和PRn,m在像素坐标系下的齐次坐标;[^^^^^以为标志点点^^在世界坐标系下的齐次坐标; [0035]联立公式(2)和公式(3),得到: [0034] wherein, bis £. 4 and financial fx4 represent the left and right camera calibration projection matrix; zu, 4Pz Rn, m are two-dimensional coordinate point in the left and right cameras in the Z-axis; [ULn .m, VLn, m, 1] T and [URn, m, VRn, m, 1] T is PLn, m and PRn, m homogeneous coordinates of the pixel at coordinates; [flag bit that ^^^^^ ^^ homogeneous coordinates in the world coordinate system; [0035] the simultaneous equations (2) and formula (3), to give:

[0036] [0036]

Figure CN106344154AD00061

[0037] 采用最小二乘法求出公式(4),得出的最优解即为手术器械标志点的空间坐标。 [0037] determined using the method of least squares equation (4), is the optimal solution obtained spatial coordinates of the surgical instrument landmarks. [0038]第三步,对手术器械尖端点进行标定。 [0038] The third step, the tip of the surgical instrument calibration point.

[0039] 1)建立标定方程组,如下所示: [0039] 1) to establish the calibration equation, as follows:

[0040] 第m个标志点所在球面的半径公式如下 [0040] Formula m-th flag radius point is located below the spherical

[0041] ( Xn, m-Xtip ) 2+ ( yn, my tip ) 2+ ( Zn, mZ tip ) 2 = Γ2 (5) [0041] (Xn, m-Xtip) 2+ (yn, my tip) 2+ (Zn, mZ tip) 2 = Γ2 (5)

[0042] 其中,手术器械尖端点的坐标为加厂匕叫^^^^^为手术器械绕尖端点旋转时其标志点所在球的半径;^^^^^、^^为手术器械上标志点的空间坐标; [0042] wherein the center point coordinates of a surgical instrument is called ^^^^^ dagger plant plus the radius of the sphere where the marker point is rotated about the center point of the surgical instrument; ^^^^^ ^^ of the surgical instrument flag the spatial coordinates of the point;

[0043]上式共有nXm个方程,依此减去第一行的式子,可得: [0043] There are nXm formula equations, so the first line is subtracted equation, we obtain:

Figure CN106344154AD00062

[0045] 2)以xtiP=[xti P,ytiP,ztiP]T作为待估计的FIR滤波器的系数,以标定方程组(6)中每个方程的等号左面的系数为滤波器输入,记作11(1) = |^1111-»1111,71111-71111,21 111-21111]1'(1 = 2,3,..,11),等号右面的常数项作为期望的输出,记作:J (:/): .= (4. +尤+ 4 -Γ匕,)/2 (/ = 2,3,.,,«)。 [0045] 2) In xtiP = [xti P, ytiP, ztiP] T as a coefficient of the FIR filter to be evaluated, the calibration factor equals the left of equations (6) in each equation is the filter input, denoted for 11 (1) = | ^ 1111- »1111,71111-71111,21 111-21111] 1 '(1 = 2,3, .., 11), the right of the equal sign of the constant term as the desired output, referred to as : J (: /):. = (4. + + 4 -Γ esp dagger,) / 2 (/ = 2,3,,, «.). 以递归最大相关熵为自适应滤波算法对FIR滤波器的系数进行估计,迭代公式如下: To estimate the FIR filter coefficients to entropy maximum correlation recursive adaptive filtering algorithm, the iteration formula is as follows:

Figure CN106344154AD00063

[0050]其中,u(l)为滤波器输入序列;d(l)为期望输出序列;1表示为数据的序列;e(l)为观测误差;w(l)为滤波器权值,《(1)=0;λ = 0.99是遗忘因子;k(l)为增益向量;P。 [0050] where, u (l) is the filter input sequence; d (l) is the desired output sequence; 1 is represented as a sequence of data; e (l) is the observation error; w (l) of filter weights, " (1) = 0; λ = 0.99 is a forgetting factor; k (l) is a gain vector; P. 为自相关矩阵的逆矩阵,? Self-inverse correlation matrix? (1)=人410。 (1) = 410 people. ( ·)= exp(-( · )2/〇2)表示高斯核函数。 (·) = Exp (- (·) 2 / 〇2) represents Gaussian kernel. 从而实现手术器械尖端点的标定。 Enabling calibration center point of the surgical instrument. 参见图4。 See Figure 4.

Claims (1)

  1. 1. 一种基于最大相关熵的手术器械尖端点标定方法,其特征在于以下步骤: 第一步,基于双目视觉的光学系统,获取待标定手术器械的旋转图像1) 将手术器械的尖端点进行固定; 2) 将手术器械围绕其尖端点进行旋转,使用双目视觉光学系统进行图像采集,并对每幅图像按照采集的顺序进行编号,左面相机采集的图片编号为L1,L2,…,LN,右面相机采集的图片编号为R1,R2,…,RN,共2N幅图片; 第二步,获取手术器械标志点的平面图像坐标和空间坐标1) 利用图像识别方法对第一步2)获取的图像中的手术器械上标志点进行识别;并将标志点图像坐标P分别记为: PLn,m-[ULn,m,VL,rmi]矛口PRn,m -[uRn,m , VRn,m] ( 1 ) 其中,下标中的L和R分别表示左相机和右相机;n表示图像采集的顺序,n = l,…,N;m表示标志点的顺序,m = 1,2,3,4; u、v为标志点像素图像坐标; 2) 利用三 A surgical instrument calibration method center point based on the maximum correlation entropy, characterized by the following steps: first, an optical system based on binocular vision, obtaining the surgical instrument to be calibrated image rotation 1) the center point of the surgical instrument fixing; 2) for the surgical instrument is rotated about its center point, using a binocular vision optical system for image acquisition, each image and numbered in the order of acquisition, the camera captured image left numbered L1, L2, ..., LN, right camera image acquisition numbered R1, R2, ..., RN, a total of 2N pictures; a second step of obtaining the surgical instrument of the mark point image coordinate and space coordinate plane 1) using the image recognition method of Step 2) identified landmark on the image acquired in the surgical instrument; and the mark point image coordinates P are denoted as: PLn, m- [ULn, m, VL, rmi] spear port PRn, m - [uRn, m, VRn, m] (1) wherein the subscripts L and R denote the left and right cameras; n-represents the order of image acquisition, n = l, ..., N; m represents a sequence of landmarks, m = 1,2, 3,4; u, v is the image pixel coordinates mark point; 2) by using three 维重建公式和第二步1)中得到的手术器械标志点在图像中的坐标,得到手术器械标志点的三维空间坐标Xn, m=[Xn,m,yn,m,Zn,m]T; 所述的三维重建公式如下: The coordinates of the surgical instrument and 3D reconstruction formula landmark Step 1) obtained in the image, to obtain a three-dimensional landmark surgical instrument spatial coordinates Xn, m = [Xn, m, yn, m, Zn, m] T; the three-dimensional reconstruction of the following formula:
    Figure CN106344154AC00021
    (2; (3) 其中,^;4和遍&分别表示左侧和右侧摄像机标定的投影矩阵;分别为在左侧和右侧摄像机Z轴中的二维坐标点;[ULn.m, VLn,m,1 ]T和[URn,m,VRn,m,1 ]T是PLn,m和PRn,m在像素坐标系下的齐次坐标;[心,^^,21^,1]7为标志点点&,在世界坐标系下的齐次坐标; 联立公式(2)和公式(3),得到: (2; (3) where, ^; 4 & times and the left and right respectively of the projection matrix camera calibration; are two-dimensional coordinate point in the left and right cameras in the Z-axis; [ULn.m, VLn, m, 1] T and [URn, m, VRn, m, 1] T is PLn, m and PRn, m homogeneous coordinates of the pixel at coordinates; [heart, ^^, ^ 21, 1] 7 & marked by little, homogeneous coordinates in the world coordinate system; simultaneous equations (2) and equation (3) yields:
    Figure CN106344154AC00022
    采用最小二乘法求出公式(4),得出的最优解即为手术器标志点的空间坐标; 第三步,对手术器械尖端点进行标定1)建立标定方程组,如下所示: 第m个标志点所在球面的半径公式为: (Xn,m_Xtip) +(yn,m_ytip) +(Zn,m_Ztip) -T (5) 其中,手术器械尖端点的坐标为^^二卜伽"^^^^^为手术器械绕尖端点旋转时其标志点所在球的半径;&,^71^、21^为手术器械上标志点的空间坐标; 由公式(5)得到如公式(6)所示的标定方程组: 、、. ^ - - Determined using the method of least squares equation (4), the optimal solution is the space coordinates resulting operation flag point; a third step, the tip of the surgical instrument calibration points 1) to establish the calibration equation, as follows: a first flag formula m radius spherical surface where the points: (Xn, m_Xtip) + (yn, m_ytip) + (Zn, m_Ztip) -T (5) wherein the coordinates for the center point of the surgical instrument Bojia two ^^ "^^ the radius of the ball point where the mark when rotated about the center point ^^^ surgical instrument; &, ^, 21 ^ spatial coordinates of the surgical instrument ^ 71 mark point; obtained by the formula as shown in formula (5) (6) calibration equations: ,, ^ - -
    Figure CN106344154AC00031
    '* v ,1 2)以^11)=[^11)^11),^11^作为待估计的? '* V, 1 2) to 11 ^) = [^ 11) 11 ^), ^ 11 ^ as estimated to be? 11?滤波器的系数;以标定方程组中每个方程等号左面的系数为滤波器输入,记作u(l);以标定方程组中每个方程等号右面的常数项作为期望输出,记作d(l); ? 11 filter coefficients; calibration factor of each equation in the equation is the filter input equals the left, referred to as u (l); desired output constant term of each equation in the calibration equation as the right of the equal sign, referred to as d (l);
    Figure CN106344154AC00032
    以递归最大相关熵为自适应滤波算法,进行迭代,对FIR滤波器的系数进行估计,实现手术器械尖端点的标定; 所述的迭代公式如下: Maximum entropy correlation recursive adaptive filter algorithm iterates, the FIR filter coefficients are estimated, to achieve a surgical instrument calibration center point; iteration according to the following formula:
    Figure CN106344154AC00033
    其中,u(l)为滤波器输入序列;d(l)为期望输出序列;1表示为数据的序列;e(l)为观测误差;w(l)为滤波器权值,《(1)=〇4 = 〇.99是遗忘因子也1)为增益向量办为自相关矩阵的逆矩阵,• )=exp(-( • )2/〇2)表示高斯核函数。 Wherein, u (l) is the filter input sequence; d (l) is the desired output sequence; 1 is represented as a sequence of data; e (l) is the observation error; w (l) of filter weights, "(1) = = 〇.99 〇4 is also forgetting factor 1) for the gain vector to do the inverse matrix of the autocorrelation matrix, •) = exp (- (•) 2 / 〇2) represents the Gaussian kernel.
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