CN114451991A - Fracture reduction path planning method based on virtual reduction collision detection - Google Patents
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- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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- A61B2034/105—Modelling of the patient, e.g. for ligaments or bones
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- A—HUMAN NECESSITIES
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- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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Abstract
The invention relates to a path planning algorithm, in particular to a fracture reduction path planning method based on virtual reduction collision detection for fracture reduction in a medical robot reduction operation, which is characterized by acquiring data information of the original position of fracture of a patient and acquiring reduction standard data according to healthy side mirror image data; planning a reset path and storing a reset path planning list; the invention automatically plans the fracture reduction path by collecting the space conversion matrix of the original position of the fracture and the final position after reduction, provides virtual reduction collision detection, further ensures the reliability of the reduction path, thereby effectively improving the safety of the fracture reduction robot, completes the path adjustment and preview by utilizing a UI interface which is convenient for human-computer interaction, and has the remarkable advantages of high path planning accuracy, simple and convenient operation, high safety and the like.
Description
The technical field is as follows:
the invention relates to a path planning algorithm, in particular to a fracture reduction path planning method based on virtual reduction collision detection for fracture reduction in a medical robot reduction operation.
Background art:
at present, algorithms for path planning mainly comprise a neural network algorithm, a genetic algorithm, an artificial force field algorithm and the like. The neural network algorithm is an information processing method for simulating a biological nervous system, has high self-learning and adaptive capacity, and needs to provide a large number of data samples in advance. The genetic algorithm is a random search algorithm which is evolved by simulating natural selection, and has better search capability and obstacle avoidance effect. The artificial potential force field method adopts a virtual force method, provides virtual force restraint for the tail end of the robot, not only can provide accurate obstacle avoidance effect, but also can add attraction force and repulsion force during fracture reduction, and improves the safety of reduction operation. Although in the robot-assisted fracture reduction operation, the neural network algorithm, the genetic algorithm and the artificial force field algorithm can provide an optimal planned path and a good obstacle avoidance effect, the neural network algorithm cannot explain an inference process and an inference basis, so that the safety of the fracture reduction operation cannot be ensured. The genetic algorithm needs to initialize some populations, unknown populations can appear, the calculation complexity is high, genetic operation factors are difficult to determine, and when the genetic algorithm is applied to a robot-assisted fracture reduction operation, the safety of the operation is poor. Although the artificial force field method is mostly used for the robot path planning problem, the artificial force field method is not applied to the robot-assisted fracture reduction operation at present.
Although the reset robot has the basic characteristics of intellectualization, accuracy and stability, the reset robot does not have the high intellectualization like a human in the strict sense, namely, only a computer or a manually specified instruction is mechanically executed, once a certain unexpected error occurs, if a corresponding safety monitoring strategy is not introduced in advance, the instruction execution failure is inevitably caused, the reset error is caused, and even serious consequences such as fracture, vascular nerve injury and the like are caused. Safety is therefore of paramount importance for robotically assisted fracture reduction procedures.
During the fracture reduction operation, firstly, the posture of the fracture far end is adjusted to reach a proper anatomical position based on a healthy side skeleton model. Then, the fracture near end is fixed, the tail end of the reduction robot is fixedly connected with the fracture far end, and the robot makes translational motion of the fracture far end relative to the near end according to the planned reduction path. The fracture far end is prevented from contacting and colliding with peripheral bone tissues, near ends and the like in the resetting movement. During the operation process that the doctor controls the robot that resets and resets, the movable platform of parallel robot is fixed with clamping tool, firmly clamps disconnected bone distal end and along the route that resets of planning, carries out accurate reduction through navigation technique based on image registration and disconnected bone near-end. Because the pose of the fracture section of the patient may change, the reset path of the reset robot needs to be planned in advance and adjusted in real time. In the process of reduction, the path planning of reduction is related to success or failure of the operation. According to different fracture displacement states clinically, for the condition with the interference between fractures, a path is required to be designed to bypass the interference; for carrying large torque forces, it is necessary to design the path and control the speed in order to avoid secondary muscle damage to the patient.
The invention content is as follows:
in order to improve and ensure the safety of the operation of the robot-assisted fracture reduction surgery, the invention provides a fracture reduction path planning method based on virtual reduction collision detection.
The invention is achieved by the following measures:
a fracture reduction path planning method based on virtual reduction collision detection is characterized by comprising the following steps:
step 1: acquiring data information of an original position of fracture of a patient, and acquiring reset standard data according to healthy side mirror image data;
step 2: planning a reset path:
step 2-1: reading a registration matrix of the far and near segment image of the affected side;
step 2-2: acquiring intraoperative real-time position conversion matrixes of the affected side near end and the affected side far end;
step 2-3: previewing whether the obtained automatic planning path has collision or not, and if not, saving the reset planning path;
and step 3: saving a reset path planning list;
and 4, step 4: and 3, performing virtual reset preview on the reset path planning list obtained in the step 3:
step 4-1: whether the proximal end of the affected side and the distal end of the affected side are both visible or not, if the proximal end of the affected side and the distal end of the affected side are not visible, stopping the reset preview, repeating the step 2, and if both the proximal end and the distal end of the affected side are visible, executing the step 4-2;
step 4-2: calculating a relative pose matrix of the far end of the current affected side relative to the near end of the affected side, and adding the start position of the reset path planning list;
step 4-3: circulating from the second matrix of the reset path planning list, and performing uniform interpolation preview between every two matrixes, wherein the every two matrixes refer to the previous pose matrix and the current pose matrix;
step 4-4: and judging whether collision occurs or not, if so, terminating the virtual reset preview, otherwise, judging whether the collision exceeds the last matrix in the list or not, if so, terminating the virtual reset preview, and if not, executing the step 4-3 again.
The step 4-3 of the invention refers to the matrix interpolation preview of two space poses, and specifically comprises the following steps:
step 4-3-1: obtaining an initial matrix and a target matrix, obtaining an initial position parameter and an initial Euler angle parameter from the initial matrix, and obtaining a target position parameter and a target Euler angle parameter from the target matrix;
step 4-3-2: dividing the difference value obtained by subtracting the initial position parameter from the target position parameter by 10 to obtain a position parameter difference offset, dividing the difference value obtained by subtracting the initial euler angle parameter from the target euler angle parameter by 10 to obtain an euler angle difference offset, and setting a cyclic variable i to be 0(i is a common variable symbol in the programming language);
step 4-3-3: adding the difference offset of the i-position parameter to the initial position parameter to obtain a new position parameter, and adding the difference offset of the i-Euler angle parameter to the initial Euler angle parameter to obtain a new Euler angle parameter;
step 4-3-4: converting the obtained new unknown parameters and the Euler angle parameters into a matrix, and applying the matrix to the affected side far end;
step 4-3-5: judging whether collision occurs or not, if so, terminating the matrix interpolation preview of the two space poses, otherwise, judging whether i is more than or equal to 10, if so, terminating the matrix interpolation preview of the two space poses, otherwise, increasing the value of i by 1 on the basis of the existing numerical value, and then, executing the step 4-3-3 again.
In step 2-3 of the invention, if the obtained automatic planning path has collision, starting manual fine adjustment, planning the path through manual translation or rotation by the manual fine adjustment, then judging whether the path planning after the manual translation or rotation has collision, if so, repeating the manual fine adjustment, otherwise, storing a reset path planning list.
The invention automatically plans the fracture reduction path by collecting the space transformation matrix of the original position and the final position after reduction of the fracture, and provides virtual reduction collision detection to further ensure the reliability of the reduction path, thereby effectively improving the safety of the fracture reduction robot, completing the path adjustment and preview by utilizing a UI interface convenient for human-computer interaction, and having the remarkable advantages of high path planning accuracy, simple and convenient operation, high safety and the like.
Description of the drawings:
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a virtual reset preview flow diagram of the present invention.
FIG. 3 is a flow chart of interpolation preview of two adjacent spatial pose matrices in the present invention.
FIG. 4 is a view showing the fracture typing used in example 1 of the present invention.
The specific implementation mode is as follows:
the invention is further described below with reference to the accompanying drawings and examples.
Example 1:
the embodiment provides a fracture reduction path planning method based on virtual reduction collision detection, and during fracture reduction surgery, the posture of the fracture distal end is adjusted to reach a proper anatomical position based on a side-healthy skeleton model; then, the fracture near end is fixed, the tail end of the reduction robot is fixedly connected with the fracture far end, the robot makes the fracture far end perform translational motion relative to the fracture near end according to a planned reduction path, and the fracture far end is prevented from being in contact collision with peripheral bone tissues, the fracture near end and the like in the reduction motion.
The long bone fracture parting Robot is provided by taking the planning of the reduction path of the long bone fracture Robot as an example, and the fracture is classified into Robot-A type, B type and C type 3 types by taking the overlapping length of the fracture tip after initial traction reduction as a standard, and referring to fig. 4; the Robot-A type fracture corresponds to C-type complex fracture in AO typing, and the Robot can finish the resetting operation without limit because the fracture ends do not overlap after the initial resetting. The Robot-B type fracture is defined as the initial reduction, the overlap of the fracture tip is less than 8mm, after proper over-traction, the fracture end is not overlapped, and the reduction Robot can also finish the reduction operation without limit. The overlap of the fracture tip of the Robot-C type fracture is larger than 8mm after the initial reduction, the fracture end still has the overlap condition after proper over-traction, the fracture end must be corrected through special rotation and angulation, and the reduction Robot can complete the reduction operation under the condition of avoiding the collision of the fracture end.
The traditional free-hand reset operation generally comprises the following steps: firstly, traction is carried out on two ends of the fracture until the total length of the fracture slightly exceeds the normal length: correcting rotation, alignment and force lines; and thirdly, shortening until the original normal length is recovered. The classic long bone fracture typing is proposed by AO tissue, called AO typing, and is classified into A type simple fracture (one fracture line, A1 spiral shape, A2 long oblique shape, A3 short oblique shape), B type die fracture (B1 spiral shape, B2 buckling stress type, B3 multiple-fold block type), and C type complex fracture (C1 spiral shape, C2 multiple-segment type, C3 irregular crush type) according to the severity of fracture from light to heavy. This type of typing is clinician-oriented, which guides the physician to perform reduction, fixation, functional exercises according to severity. For the robot, the severity of the fracture cannot be distinguished, and the fracture broken end form is difficult to influence the reduction operation;
the method comprises the steps of performing reverse modeling on fractured bones based on CT scanning data (by combining automatic path planning and manual path planning), previewing a reset path of the automatic path planning/manual path planning, and checking whether collision occurs in a virtual reset process to plan an obstacle avoidance reset path; in the process of operating the reduction robot to perform a reduction operation by a doctor, a clamping tool is fixed on a movable platform of the parallel robot, the far end of the fractured bone is firmly clamped, and the accurate reduction is performed on the near end of the fractured bone through a navigation technology based on image registration along a planned reduction path; because the pose of the fracture section of the patient may change, the reset path of the reset robot needs to be planned in advance and adjusted in real time; the spatial matrixes of the proximal end and the distal end of the long bone on the affected side are T1 and T2, and in order to achieve an ideal reset position relationship, the distal end on the affected side only needs to perform corresponding spatial transformation T (T is T1-1. T2) relative to the proximal end on the affected side.
For long bone fracture robot reset path planning, after a space transformation matrix between an original position and a final reset position of fracture is acquired by a navigation system, the reset robot automatically completes reset operation, but countless motion paths exist between the two positions, namely infinite solutions exist, bones are rigid bodies, and deformation cannot be generated generally unless fracture occurs. Therefore, in the process of resetting, due to the diversity of path solutions, mutual collision between fracture ends may occur in the motion path, which may not only hinder the continuous completion of resetting, but also cause iatrogenic fracture and vascular nerve injury. Therefore, the movement path of the reset robot must be planned in advance, and reasonable path points are set to safely complete the reset operation.
According to Robot fracture typing, virtual resetting preview operation of three-dimensional images is carried out in advance, 4 to 5 key path points are reasonably set, so that the Robot can complete the resetting operation strictly according to a path planned in advance, and the fracture end can be prevented from colliding. The basic principle of path planning is as follows; appropriate traction is performed in advance. ② the reset path is shortened as much as possible. And avoiding important nerve and blood vessel areas. Fourthly, the maximum length of traction is not more than 1cm of the original bone length.
After the broken bone CT image and the healthy side CT image are registered, the reduction of the fracture is realized on the images, and in order to guide the reduction robot to carry out the reduction operation on the human body, the registration matrix needs to be converted into the motion path of the robot. Firstly, a direct registration matrix is required to be obtained according to an image registration result, then a registration path is required to be planned, and the direct registration matrix is decomposed into a plurality of matrixes according to the planning result, and the position conversion relation of the fractured bones at different path stages is corresponded. After the registration matrix and the registration matrix corresponding to each step of the planned path are obtained, the robot motion space needs to be associated with the image space, the registration matrix is further used for guiding the robot to move, and finally the reset operation is realized. Since fracture displacement is a positional change in three-dimensional space, it can be decomposed into translation and rotation (rotational parameters euler angles α, β, γ) along three axes of the cadier coordinate system x, y, z, totaling 6 degrees of freedom of motion.
The specific method for path planning comprises the following steps: setting the reduction process to be that the far end of the tibia fracture is relatively transformed relative to the near end of the femur fracture, and then setting by a doctor according to clinical experience how to avoid interference and not damage muscles in the reduction motion process, and planning the space transformation of the far end of the tibia relative to the near end of the tibia; the final position of the reset, that is, the reset standard value obtained according to the healthy-side mirror image as the standard, cannot be changed at will according to the subjective impression of the doctor, so that the accuracy of the final reset result is ensured. In order to unify the coordinate systems, the relative coordinate systems in this example are all default spatial coordinate systems of the CT data, but when the doctor plans the path, the central coordinate system of the three-dimensional data model itself is selected for use in the path planning because the transformation human-computer interaction function of the default spatial coordinate system of the three-dimensional data model relative to the CT data is not strong and the operation habit of the doctor cannot be reflected well, while the central coordinate system of the three-dimensional data model itself is more in line with the operation habit of the doctor.
In order to maintain consistency of the spatial matrix relationship, it is necessary to convert a transformation matrix represented by the central coordinate system of the three-dimensional data model itself into a transformation matrix represented by the default spatial coordinate system of the CT data;
for automatic path planning, only the affected side far-near end image registration matrix and the affected side near end and affected side far end intraoperative real-time position conversion matrix are needed. For manual path planning, a physician is required to set 4 to 5 critical path points empirically and reasonably. The doctor can use mouse dragging on the coordinate graph of the three-dimensional data model of the affected side far end provided by the software to complete relatively large translation and rotation path planning, and if the micro translation or rotation path planning is needed, the planning can be completed through a fine adjustment panel provided by the software. After the path planning of each pose is completed, virtual resetting can be previewed, and if collision occurs in the resetting process, the planning matrix of the pose can be deleted, and a new reasonable pose matrix is manually planned again.
During each virtual resetting preview, whether the proximal marking point and the distal marking point on the affected side are in a visible range or not is judged, and if the proximal marking point and the distal marking point on the affected side are visible, the virtual resetting can be carried out. Firstly, a real-time pose transformation matrix of the far end of the affected side relative to the near end of the affected side in an operation needs to be obtained, and then interpolation virtual resetting is started between every two matrixes from the real-time pose transformation matrix. In the virtual reset process, 10 small steps are needed to finish the preview according to three translation parameters of x, y and z and three rotation parameters of alpha, beta and gamma (Euler angles).
The flow of the interpolation preview algorithm for two spatial poses is shown in fig. 3, the flow of reset path planning and preview is shown in fig. 1, and the flow of the virtual reset preview algorithm is shown in fig. 2.
And after the reset path planning is finished, entering a navigation reset interface. Firstly, a reset path planning list is read and displayed on a software interface. And after the fracture reset button is clicked each time, only sending the matrix corresponding to the reset path planning list index displayed on the current interface to the reset robot. And after receiving the reset instruction, the reset robot starts to reset according to the planned path. And simultaneously displaying the motion state and the position of the bone on a navigation interface in real time.
Claims (3)
1. A fracture reduction path planning method based on virtual reduction collision detection is characterized by comprising the following steps:
step 1: acquiring data information of an original position of fracture of a patient, and acquiring reset standard data according to healthy side mirror image data;
step 2: planning a reset path:
step 2-1: reading a registration matrix of the far and near segment image of the affected side;
step 2-2: acquiring intraoperative real-time position conversion matrixes of the affected side near end and the affected side far end;
step 2-3: previewing whether the obtained automatic planning path has collision or not, and if not, saving the reset planning path;
and step 3: saving a reset path planning list;
and 4, step 4: and 3, performing virtual reset preview on the reset path planning list obtained in the step 3:
step 4-1: whether the proximal end of the affected side and the distal end of the affected side are both visible or not, if the proximal end of the affected side and the distal end of the affected side are not visible, stopping the reset preview, repeating the step 2, and if both the proximal end and the distal end of the affected side are visible, executing the step 4-2;
step 4-2: calculating a relative pose matrix of the far end of the current affected side relative to the near end of the affected side, and adding the start position of the reset path planning list;
step 4-3: circulating from the second matrix of the reset path planning list, and performing uniform interpolation preview between every two matrixes, wherein the every two matrixes refer to the previous pose matrix and the current pose matrix;
step 4-4: and judging whether collision occurs or not, if so, terminating the virtual reset preview, otherwise, judging whether the collision exceeds the last matrix in the list or not, if so, terminating the virtual reset preview, and if not, executing the step 4-3 again.
2. The method for planning a fracture reduction path based on virtual reduction collision detection according to claim 1, wherein the uniform interpolation preview between every two matrixes in the step 4-3 is a matrix interpolation preview of two spatial poses, and specifically comprises:
step 4-3-1: obtaining an initial matrix and a target matrix, obtaining an initial position parameter and an initial Euler angle parameter from the initial matrix, and obtaining a target position parameter and a target Euler angle parameter from the target matrix;
step 4-3-2: dividing the difference value obtained by subtracting the initial position parameter from the target position parameter by 10 to obtain a position parameter difference offset, dividing the difference value obtained by subtracting the initial euler angle parameter from the target euler angle parameter by 10 to obtain an euler angle difference offset, and setting a cyclic variable i to be 0;
step 4-3-3: adding the difference offset of the i-position parameter to the initial position parameter to obtain a new position parameter, and adding the difference offset of the i-Euler angle parameter to the initial Euler angle parameter to obtain a new Euler angle parameter;
step 4-3-4: converting the obtained new unknown parameters and the Euler angle parameters into a matrix, and applying the matrix to the affected side far end;
step 4-3-5: judging whether collision occurs or not, if so, terminating the matrix interpolation preview of the two space poses, otherwise, judging whether i is more than or equal to 10, if so, terminating the matrix interpolation preview of the two space poses, otherwise, increasing the value of i by 1 on the basis of the existing numerical value, and then, executing the step 4-3-3 again.
3. The method for planning the bone fracture reduction path based on the virtual reduction collision detection according to claim 1, wherein in step 2-3, if the obtained automatically planned path has a collision, manual fine adjustment is started, the manual fine adjustment is performed through manual translation or rotation path planning, then whether the path planning after the manual translation or rotation has a collision is judged, if the path planning has a collision, the manual fine adjustment is repeated, otherwise, a reduction path planning list is saved.
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|---|---|---|---|---|
| CN114974509A (en) * | 2022-05-26 | 2022-08-30 | 哈尔滨工业大学 | Fracture reduction path planning method, fracture reduction method and electronic equipment |
| CN114974509B (en) * | 2022-05-26 | 2024-05-10 | 哈尔滨工业大学 | Fracture reduction path planning method, fracture reduction method and electronic equipment |
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| CN114451991B (en) | 2024-02-27 |
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