CN113116524B - Detection compensation method, device, navigation processing method, device and navigation system - Google Patents

Detection compensation method, device, navigation processing method, device and navigation system Download PDF

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CN113116524B
CN113116524B CN202110406710.4A CN202110406710A CN113116524B CN 113116524 B CN113116524 B CN 113116524B CN 202110406710 A CN202110406710 A CN 202110406710A CN 113116524 B CN113116524 B CN 113116524B
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detection information
kth
information
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CN113116524A (en
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孙加源
谢芳芳
郑筱轩
陈日清
余坤璋
李楠宇
徐宏
苏晨晖
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Shanghai Chest Hospital
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Abstract

The invention provides a detection compensation method, a device, a navigation processing method, a device and a navigation system, wherein N sensors are arranged on a catheter, the N sensors are sequentially distributed at different positions in the length direction of the catheter, and the detection compensation method for multi-sensor navigation comprises the following steps: after the catheter enters a physiological pipeline to be detected, acquiring actual detection information of the N sensors, wherein the detection information characterizes the position and the posture of the catheter position where the sensors are positioned; and correcting the actual detection information of at least part of the sensors according to the actual detection information of the N sensors and the interval length information among the sensors to obtain corrected detection information, wherein the interval length information characterizes the length of a catheter part among the sensors in the catheter.

Description

Detection compensation method, device, navigation processing method, device and navigation system
Technical Field
The present invention relates to the field of medical treatment, and in particular, to a detection compensation method, a detection compensation device, a navigation processing method, a navigation processing device, and a navigation system.
Background
In medical activities, catheters are required to be guided into physiological channels of animals or human bodies, and further, the implementation of endoscopic, biopsy and other processes can be facilitated. After the catheter enters the physiological channel, navigation of the catheter's position within the physiological channel is often required.
In the related art, a sensor may be provided on a catheter and navigation may be performed based on detection information of the sensor, however, the detection information of the sensor may be disturbed by a physiological reaction (e.g., respiration).
Disclosure of Invention
The invention provides a detection compensation method, a detection compensation device, a navigation processing method, a navigation processing device and a navigation system, which are used for solving the problem that detection information of a sensor is interfered by physiological reaction.
According to a first aspect of the present invention, there is provided a detection compensation method for multi-sensor navigation, N sensors are disposed in a catheter, and the N sensors are sequentially distributed at different positions along the length direction of the catheter, where N is greater than or equal to 2;
the detection compensation method for the multi-sensor navigation comprises the following steps:
after the catheter enters a physiological pipeline to be detected, acquiring actual detection information of the N sensors, wherein the detection information characterizes the position and the posture of the catheter position where the sensors are positioned;
and correcting the actual detection information of at least part of the sensors according to the actual detection information of the N sensors and the interval length information among the sensors to obtain corrected detection information, wherein the interval length information characterizes the length of a catheter part among the sensors in the catheter.
In the scheme, under the condition that a plurality of sensors are adopted, correction of detection information is realized, and because interval length information among the sensors is combined in the correction process, the correction result can be constrained by the distribution positions of the sensors, the accuracy of the detection information after correction is improved, and further, the navigation accuracy can be effectively improved when navigation is carried out based on the correction result.
Optionally, according to the actual detection information of the N sensors and the interval length information between the sensors, correcting at least part of the actual detection information of the sensors to obtain corrected detection information, which specifically includes:
for any kth sensor, according to detection information of one or more sensors between the kth sensor and an inlet of the physiological channel to be detected and interval length information between the kth sensor and the kth sensor, the actual detection information of the kth sensor is corrected, wherein k is greater than or equal to 2, the kth sensor refers to the kth sensor which is distributed along a target sequence in the N sensors, and the target sequence is opposite to the sequence in which the sensors sequentially enter the physiological channel to be detected.
Optionally, correcting the actual detection information of the kth sensor according to the detection information of one or more sensors between the kth sensor and the entrance of the physiological channel to be detected and the interval length information between the kth sensor and the kth sensor, so as to obtain corrected detection information of the kth sensor, which specifically includes:
predicting at least part of detection information of the kth sensor according to the actual detection information or the corrected detection information of the mth sensor and the interval length information between the kth sensor and the mth sensor to obtain the prediction detection information of the kth sensor; wherein m is less than k;
and correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor.
In the above embodiments, the correction of the sensor is performed based on the detection information of the sensor before the sensor, and the deeper into the human body, the less likely the physiological conduit to be measured is to interfere with the physiological reaction (for example, the influence of respiration), the less the sensor before the conduit is subjected to the interference, and the closer the sensor before the conduit is to the upper lobe of the lung, the less the sensor before the conduit is subjected to the interference of respiration. Furthermore, the front sensor is utilized to correct and compensate the rear sensor, so that the influence of interference on the detection result can be eliminated or reduced, and the accuracy of detection information can be improved.
Optionally, m=k-1, and the detection information of at least part of the sensors is sequentially corrected along the target sequence.
In the scheme, each correction can be ensured to be carried out based on more accurate detection information.
Optionally, the predicted detection information includes position information of a predicted position of the kth sensor, and a distance between the predicted position and a position characterized by the detection information of the mth sensor matches interval length information between the kth sensor and the mth sensor.
Optionally, correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor, including:
determining a corresponding extension line according to the actual detection information or the corrected detection information of the mth sensor, wherein the position of the extension line is matched with the position represented by the corresponding detection information, and the extension direction of the extension line is matched with the gesture represented by the corresponding detection information;
and determining the predicted position according to the extension line and the interval length information between the kth sensor and the mth sensor.
In the schemes, the position and the gesture of the mth sensor can be fully considered in the position prediction of the kth sensor, so that the correction result can be accurate, the position and the gesture of the mth sensor can be fully considered, and the correction accuracy is improved.
Optionally, the predicted detection information further includes posture information of a predicted posture of the kth sensor, and the predicted posture is matched with the posture of the mth sensor.
In the scheme, the gesture of the kth sensor can be fully considered in the gesture prediction of the mth sensor, so that the correction accuracy is improved.
Optionally, correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor, which specifically includes:
correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information;
wherein the correction reference information includes: the first correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the prediction detection information, and/or the second correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the actual detection information.
Optionally, the revised reference information for the different order sensors is different, and:
and in the N sensors, the closer to the inlet of the physiological channel to be detected, the lower the matching degree represented by the first correction reference information of the sensor is, and the higher the matching degree represented by the second correction reference information is.
In the above scheme, as the sensor is closer to the inlet of the physiological channel to be detected, the interference suffered by the sensor is smaller (for example, the sensor is closer to the upper lung leaf, and the respiratory interference is smaller), correspondingly, the correction reference information of different sensors in the above scheme can be more accurately matched with the order in which the sensors are positioned, so that the size distribution of the interference is more accurately matched, and the correction accuracy is ensured.
Optionally, correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information specifically includes:
according to the correction reference information, carrying out weighted summation on the prediction detection information of the kth sensor and the actual detection information of the kth sensor to obtain detection information after correction of the kth sensor; the first correction reference information is a first weighted value corresponding to the prediction detection information, and the second correction reference information is a second weighted value corresponding to the actual detection information.
In the scheme, a quantifiable processing means is provided for correction of the detection information, and based on a weighted summation mode, the prediction detection information and the actual detection information can be effectively considered based on the weighted value, and meanwhile, the relative simplification of an algorithm can be ensured.
Optionally, according to the corrected reference information, the weighted summation is performed on the predicted detection information of the kth sensor and the actual detection information of the kth sensor to obtain corrected detection information of the kth sensor, which specifically includes:
correcting the actual monitoring information of the kth sensor based on the following formula:
(x k ′，y k ′，z k， ，α k ′，β k ′，γ k ′)＝(1-λ)(x k ，y k ，z k ，α k ，β k ，γ k )+λ(x p ，y p ，z p ，α p ，β p ，γ p )
wherein:
(x k ′，y k ′，z k， ′α k ′，β k ′，γ k ') the detection information after the k sensor correction is characterized;
x k ' characterizing coordinates in the x-axis direction in the detection information corrected by the kth sensor;
y k ' characterizing the coordinates in the y-axis direction in the detection information corrected by the kth sensor;
z k ' characterizing the z-axis coordinate in the detection information corrected by the kth sensor;
α k ' characterizing a rotation angle around an x-axis in the detection information corrected by the kth sensor;
β k ' characterizing a rotation angle around a y-axis in the detection information corrected by the kth sensor;
γ k ' characterizing a rotation angle around a z-axis in the detection information corrected by the kth sensor;
(x k ，y k ，z k， α k ，β k ，γ k ) Characterizing actual monitoring information of a kth sensor;
x k characterizing the coordinates in the x-axis direction in the actual detection information of the kth sensor;
y k characterizing the coordinate in the y-axis direction in the actual detection information of the kth sensor;
z k characterizing the coordinate in the z-axis direction in the actual detection information of the kth sensor;
α k characterizing the rotation angle around the x axis in the actual detection information of the kth sensor;
β k characterizing the rotation angle around the y axis in the actual detection information of the kth sensor;
γ k characterizing the rotation angle around the z axis in the actual detection information of the kth sensor;
(x p ，y p ，z p ，α p ，β p ，γ p ) Predictive detection information characterizing a kth sensor;
x p characterizing coordinates in the x-axis direction in the predictive detection information of the kth sensor;
y p characterizing coordinates in a y-axis direction in the predictive detection information of the kth sensor;
z p characterizing the z-axis coordinate in the predictive detection information of the kth sensor；
α p Characterizing a rotation angle around an x-axis in the predictive detection information of the kth sensor;
β p characterizing a rotation angle around a y-axis in the predictive detection information of the kth sensor;
γ p Characterizing a rotation angle around a z-axis in the predictive detection information of the kth sensor;
λ is the first weighted value;
and 1-lambda is the second weighted value.
Optionally, the distribution positions of the N sensors are determined according to a scanned image of the physiological channel to be measured, and the intervals of the N sensors are matched with the shape of the physiological channel to be measured represented by the scanned image.
Optionally, the detection compensation method for multi-sensor navigation further includes:
and forming a virtual model of the physiological pipeline to be detected according to the scanning image, and using the virtual model as a determination basis of the N sensor distribution positions.
In the above alternatives, since the distribution positions of the N sensors are determined based on the scanned image and the virtual model of the physiological pipeline to be measured, the distribution result can be ensured to fully meet the requirement of the physiological pipeline to be measured.
Optionally, the physiological channel to be measured is a bronchial tree to be measured,
the distribution positions of the N sensors meet at least one of the following:
the length of the catheter part between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports in the bronchial tree to be tested;
The length of the catheter part between two adjacent sensors is shorter than the channel length between any two adjacent bifurcation openings in the bronchial tree to be tested;
the length of the catheter portion between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be tested.
In the above scheme, since the length between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports, the length can be necessarily longer than the longest channel length of the adjacent bifurcation ports, and further, under the scene that the curvature information is enough based on the detection information, the following can be ensured: the outlined curvature can fully cover at least two bifurcation ports, so that the defect of bifurcation ports is avoided, the requirement of subsequent positioning is met, and the positioning accuracy is improved.
Because the length between adjacent sensors is shorter than the channel length between any two adjacent bifurcation ports, the length can be necessarily shorter than the shortest channel length of the adjacent bifurcation ports, and furthermore, under the scene that curvature information is enough based on detection information, the information of the bifurcation ports can be prevented from being lost by the outlined curvature, and the positioning accuracy is improved.
Because the length between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be detected, furthermore, under the scene of needing to be based on the curvature information of the detection information, N sensors can be guaranteed not to be located in the same lung segment in a centralized mode, and positioning accuracy is guaranteed.
According to a second aspect of the present invention, there is provided a transcatheter navigation processing method comprising:
determining corrected detection information of the N sensors by using a detection compensation method of multi-sensor navigation related to the first aspect and an optional scheme thereof;
and determining the position of the catheter in the physiological pipeline to be detected according to the corrected detection information.
According to a third aspect of the present invention, there is provided a detection and compensation device for multi-sensor navigation, wherein N sensors are disposed in a catheter, and the N sensors are sequentially distributed at different positions along the length direction of the catheter, where N is greater than or equal to 2;
a detection compensation device for multi-sensor navigation, comprising:
the acquisition module is used for acquiring the actual detection information of the N sensors after the catheter enters the physiological pipeline to be detected, wherein the detection information represents the position and the posture of the catheter position where the sensors are positioned;
and the correction module is used for correcting the actual detection information of at least part of the sensors according to the actual detection information of the N sensors and the interval length information among the sensors to obtain corrected detection information, and the interval length information characterizes the length of the catheter part among the sensors in the catheter.
According to a fourth aspect of the present invention, there is provided a transcatheter navigation processing device comprising:
a detection compensation unit, configured to determine corrected detection information of the N sensors by using the detection compensation method of multi-sensor navigation related to the first aspect and its alternative;
and the positioning unit is used for determining the position of the catheter in the physiological pipeline to be detected according to the corrected detection information.
According to a fifth aspect of the present invention, there is provided an electronic device, characterized by comprising a processor and a memory,
the memory is used for storing codes;
the processor is configured to execute the code in the memory to implement the detection compensation method of the multi-sensor navigation related to the first aspect and its alternatives, or the transcatheter navigation processing method related to the second aspect.
According to a sixth aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the detection compensation method of multi-sensor navigation according to the first aspect and its alternatives, or the catheter navigation processing method according to the second aspect.
According to a seventh aspect of the present invention, there is provided a transcatheter navigation system comprising: the device comprises a catheter, N sensors and a data processing module, wherein the N sensors are arranged on the catheter and are sequentially distributed at different positions in the length direction of the catheter, and the data processing module can be directly or indirectly communicated with the N sensors;
The data processing module is configured to perform the detection compensation method of the multi-sensor navigation related to the first aspect and its alternatives, or the transcatheter navigation processing method related to the second aspect.
Optionally, the sensor is a magnetic navigation sensor.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic diagram of the construction of a transcatheter navigation system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing the distribution of sensors on a catheter in accordance with one embodiment of the present invention;
FIG. 3 is a flow chart of a method for compensating for detection of multi-sensor navigation according to an embodiment of the invention;
FIG. 4 is a flowchart of step S22 according to an embodiment of the present invention;
FIG. 5 is a flowchart of step S220 in an embodiment of the present invention;
FIG. 6 is a schematic diagram of a geometric model of a sensor in an embodiment of the invention;
FIG. 7 is a flowchart of step S221 in an embodiment of the present invention;
FIG. 8 is a flowchart of step S222 according to an embodiment of the present invention;
FIG. 9 is a flowchart of step S2220 in an embodiment of the present invention;
FIG. 10 is a second flow chart of a detection compensation method for multi-sensor navigation according to an embodiment of the invention;
FIG. 11 is a schematic representation of modeling of a bronchial tree in an embodiment of the invention;
FIG. 12 is a flow chart of a transcatheter navigation processing method according to an embodiment of the present invention;
FIG. 13 is a schematic diagram of a program module of a detection compensation device for multi-sensor navigation according to an embodiment of the present invention;
FIG. 14 is a second program module of the detection compensation device for multi-sensor navigation according to an embodiment of the present invention;
FIG. 15 is a schematic diagram of a program element of a transcatheter navigation processing device according to an embodiment of the present invention.
Fig. 16 is a schematic view of the configuration of an electronic device in an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical scheme of the invention is described in detail below by specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
The detection compensation method (and device) for multi-sensor navigation and the navigation processing method (and device) for navigation provided by the embodiment of the invention can be applied to the same or different execution subjects with data processing capability, and the execution subjects can be specifically the electronic equipment 60 and the data processing module 103 which are referred to later. At least part of the steps of the navigation processing method and the detection compensation method can be realized based on LungPoint software.
Referring to fig. 1, the transcatheter navigation system may include a catheter 101, N sensors 102, where N sensors 102 are all disposed on the catheter 101, where N is greater than or equal to 2, for example, 5, 6, 7, 8, 9, 10, etc., and the number of the sensors may be arbitrarily selected according to the requirements of medical activities, the type and shape of the physiological channel to be measured, and the detection accuracy of the sensors.
In some aspects, the navigation system may further include: the endoscope module may be omitted in another embodiment.
If the endoscope module is included, the endoscope module may be understood as a component or a combination of components that can perform an endoscope in a physiological channel, and may include at least one of an image acquisition component, an illumination component, and the like, but is not limited thereto, and may be a structure in which they are assembled and packaged together. In addition, the endoscope module may be provided at the distal end of the catheter 101 or at a non-distal position.
Catheter 101, which may be understood as a structure provided with sensors and adapted to deliver N sensors into a physiological passage, may for example comprise a flexible tube, or may comprise a rigid tube, wherein there may be provided instruments for guiding the catheter, or other instruments for medical activities, or may be provided with circuitry, circuits, structures for electrically connecting sensors 202 to the outside.
The sensor 102 may be understood as a sensor capable of detecting its own position and posture, and when the sensor 102 is disposed in a catheter, the sensor may be understood as a sensor capable of detecting the position and posture of the catheter where the sensor 102 is disposed, and further, the detection information detected by the sensor may be indicative of the position and posture of the catheter where the sensor 102 is disposed, and in addition, the detection information detected by the sensor is not limited to the position and posture. Any sensor in the art capable of detecting position and posture does not depart from the scope of the embodiment of the invention. In a further embodiment, the sensor 102 may be a magnetic navigation sensor, an optical fiber sensor, a shape sensor, or the like, and no matter what kind of sensor is used, the sensor does not deviate from the scope of the embodiment of the present invention.
In the embodiment of the present invention, referring to the geometric model diagram shown in fig. 2, N sensors 102 are sequentially distributed at different positions along the length direction of the catheter 101, and further, a length of a catheter portion may be spaced between two adjacent sensors 102, where the length of the spaced catheter portion may be uniform or non-uniform, and in the example shown in fig. 2, the number of the sensors 102 is seven.
The execution body referred to above may be connected to the sensor in communication, and the communication connection may be wired or wireless.
Referring to fig. 3, a detection compensation method for multi-sensor navigation according to an embodiment of the present invention includes:
s21: after the catheter enters a physiological pipeline to be detected, acquiring actual detection information of the N sensors;
s22: and correcting at least part of the actual detection information of the sensors according to the actual detection information of the N sensors and the interval length information among the sensors to obtain corrected detection information.
The physiological channel to be measured may be any physiological channel of any human body or animal body, for example, may be a bronchial tree (which may be understood by referring to the form of the virtual model shown in fig. 11), and in other examples, the physiological channel to be measured may also be a channel of the urinary system, a channel of the digestive system, or the like. The physiologic tunnel can have multiple intersections (or can be understood as bifurcation) therein.
Wherein the interval length information characterizes the length of the catheter sections between the sensors in the catheter. Which may include the length of the conduit portion between adjacent sensors, and may also include the length of the conduit portion between non-adjacent sensors.
In the scheme, under the condition that a plurality of sensors are adopted, correction of detection information is realized, and because interval length information among the sensors is combined in the correction process, the correction result can be constrained by the distribution positions of the sensors, the accuracy of the detection information after correction is improved, and further, the navigation accuracy can be effectively improved when navigation is carried out based on the correction result.
In one embodiment, referring to fig. 4, step S22 may include:
s220: for any kth sensor, according to detection information of one or more sensors between the kth sensor and an inlet of the physiological channel to be detected and interval length information between the kth sensor and the kth sensor, the actual detection information of the kth sensor is corrected, wherein k is greater than or equal to 2, the kth sensor refers to the kth sensor which is sequentially distributed along a target sequence in the N sensors, and the target sequence is opposite to the sequence in which the sensors sequentially enter the physiological channel to be detected, namely the sequence far away from the inlet of the physiological channel to be detected.
Further, k may take different values one by one (e.g., 2, 3, 4, … … consecutive values, or discontinuous values), so that step S220 is performed one by one for the sensors of the at least some of the sensors.
Still further, referring to fig. 5, step S220 may specifically include:
s221: predicting at least part of detection information of the kth sensor according to the actual detection information or the corrected detection information of the mth sensor and the interval length information between the kth sensor and the mth sensor to obtain the prediction detection information of the kth sensor; wherein m is less than k;
s222: and correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor.
In the above embodiments, the correction of the sensor is performed based on the detection information of the sensor located in front of the sensor, and the deeper the sensor is in the physiological duct to be measured, the less likely the sensor located in front of the sensor is to interfere with the physiological reaction (e.g., the influence of respiration), and therefore, the less the sensor located in front of the sensor is to interfere with the respiration, the less the sensor located in front of the sensor is to interfere with the upper lobe of the lung. Furthermore, the front sensor is utilized to correct and compensate the rear sensor, so that the influence of interference on the detection result can be eliminated or reduced, and the accuracy of detection information can be improved.
In other words, taking the bronchial tree as an example, in consideration of pulmonary respiration, the detection information (e.g., coordinates, angles) of the front sensor is less affected than the detection information (e.g., coordinates, angles) of the rear sensor, and by correction of the detection information (e.g., correction of coordinates, angles), each sensor can give accurate detection information.
In a specific example, m=k-1, and the detection information of at least part of the sensors is sequentially corrected along the target sequence. Further, the detection information of the sensors may be corrected one by one from front to back, and the detection information of the last sensor in the target order among the adjacent sensors is used to correct the next sensor. In the scheme, each correction can be ensured to be carried out based on more accurate detection information.
In other examples, m may not be equal to k-1, and the sensor for correcting the detection information of the kth sensor may not be limited to one.
Wherein, the front sensor and the front sensor refer to the front sensor and the front sensor along the target sequence; the latter sensor and the rear sensor refer to the rear and rear sensors in the target order.
In one embodiment, the predicted detection information includes position information of a predicted position of the kth sensor, and a distance between the predicted position and a position characterized by the detection information of the mth sensor matches interval length information between the kth sensor and the mth sensor. The matching between the distance and the interval may be the same or similar (e.g., less than a certain distance threshold). Therefore, the constraint of the position and interval length information of the mth sensor on the predicted position is realized in the scheme, and the predicted result is ensured to be accurately matched with the position and the interval length.
In addition to distance, the pose of the mth sensor may also put constraints on the predicted position.
Thus, referring to fig. 7, step S221 may include:
s2211: determining a corresponding extension line according to the actual detection information or the corrected detection information of the mth sensor;
s2212: and determining the predicted position according to the extension line and the interval length information between the kth sensor and the mth sensor.
Wherein the position of the extension line matches the position characterized by the corresponding detection information, for example, the extension line may pass through the position in the detection information of the mth sensor (for example, the coordinates of x, y and z in the detection information need to be passed through), and the extension direction of the extension line matches the gesture characterized by the corresponding detection information (for example, the extension direction matches the α, β and γ in the detection information).
Since the posture of the sensor is actually the posture of the catheter where it is located, and it changes with the bending of the catheter, the extending direction may specifically match the tangential direction of the catheter where the sensor is located and point to the next sensor side along the target sequence, for example: the extending direction may be the same as, similar to (or at a specified angle from) the tangential direction (the angle difference is less than a certain threshold). In the scheme, the restriction of the posture of the mth sensor on the position of the kth sensor is fully considered, so that the prediction result can be accurately matched with the posture of the mth sensor (namely, the prediction result is matched with the bending condition of the corresponding catheter position).
Furthermore, the position and the gesture of the mth sensor can be fully considered in the position prediction of the kth sensor, so that the correction result can be accurate, the position and the gesture of the mth sensor can be fully considered, and the correction accuracy is improved.
In one embodiment, the predicted detection information further includes posture information of a predicted posture of the kth sensor, the predicted posture matching a posture of the mth sensor. It can be seen that the pose prediction of the kth sensor is mainly constrained by the pose of the mth sensor.
Furthermore, in the scheme, the gesture of the kth sensor can be fully considered in the gesture prediction of the mth sensor, so that the correction accuracy is improved.
In one embodiment, referring to fig. 8, step S222 may include:
s2220: correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information;
wherein the correction reference information includes: the first correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the prediction detection information, and/or the second correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the actual detection information.
The first correction reference information and the second correction reference information may be any information capable of characterizing a corresponding matching degree, and the content of the correction reference information may be changed arbitrarily based on different correction algorithms, without departing from the scope of the embodiment of the present invention.
In one example, the revised reference information for the different order sensors is different, and:
And in the N sensors, the closer to the inlet of the physiological channel to be detected, the lower the matching degree represented by the first correction reference information of the sensor is, and the higher the matching degree represented by the second correction reference information is.
In the above scheme, as the sensor is closer to the inlet of the physiological channel to be detected, the interference suffered by the sensor is smaller (for example, the sensor is closer to the upper lung leaf, and the respiratory interference is smaller), correspondingly, the correction reference information of different sensors in the above scheme can be more accurately matched with the order in which the sensors are positioned, so that the size distribution of the interference is more accurately matched, and the correction accuracy is ensured.
Further, the magnitude of the change in the degree of matching between adjacent sensors may be the same (e.g., the first weight of each sensor along the target order may change equally, the second weight of each sensor may change equally), or the magnitude of the change in the degree of matching between adjacent sensors may be different (e.g., the differences in the first and second weights of each adjacent sensor may be different). The magnitude of the change in the degree of matching between adjacent sensors may also be correlated with the length of the gap between the sensors, e.g., the longer the gap distance, the greater the magnitude of the change in the degree of matching. Regardless of how the specifically quantized correction parameter information changes, it does not depart from the scope of the above approach.
In a further aspect, referring to fig. 8, step S2220 specifically includes:
s22200: and according to the corrected reference information, carrying out weighted summation on the predicted detection information of the kth sensor and the actual detection information of the kth sensor to obtain the detection information corrected by the kth sensor.
The first correction reference information is a first weighted value corresponding to the prediction detection information, and the second correction reference information is a second weighted value corresponding to the actual detection information.
In the scheme, a quantifiable processing means is provided for correction of the detection information, and based on a weighted summation mode, the prediction detection information and the actual detection information can be effectively considered based on the weighted value, and meanwhile, the relative simplification of an algorithm can be ensured.
In one example, the sum of the first weighted value and the second weighted value is 1, and the value of the first weighted value is less than or equal to 0.5.
In addition, in some examples, if other factors are also considered in the correction, the weighting values may further include other weighting values corresponding to the other factors.
For example, for the kth sensor, in addition to the detection information of the mth sensor, the detection information of the kth sensor (q is smaller than k and not equal to m) may be combined, the past detection information of the kth sensor (for example, the detection information of the previous time) may be combined, the detection information of the kth sensor (p is larger than k) may be combined, and at this time, the sum of the first weighted value and the second weighted value may be smaller than 1.
Referring to fig. 6, corresponding to the geometric model of the sensor and catheter in fig. 2, the data of six degrees of freedom of the sensor in three-dimensional space are: coordinates in the x-axis direction, coordinates in the y-axis direction, coordinates in the z-axis direction, rotation angle about the x-axis, rotation angle about the y-axis, rotation angle about the z-axis. The data of the six degrees of freedom can be understood as the detection information, and the interval length information between adjacent sensors can be, for example, the lengths characterized by L1, L2, L3, L4, L5, and L6 therein.
Taking the seven sensors shown in fig. 6 as an example, the x-axis coordinates of the seven sensors are respectively x 1 ，x 2 ，x 3 ，x 4 ，x 5 ，x 6 ，x 7 The method comprises the steps of carrying out a first treatment on the surface of the The y-axis coordinates are y 1 ，y 2 ，y 3 ，y 4 ，y 5 ，y 6 ，y 7 The method comprises the steps of carrying out a first treatment on the surface of the The z-axis coordinates are z1, z2, z3, z4, z5, z6, z7 respectively; the three rotation angles are respectively alpha 1, alpha 2, alpha 3, alpha 4 and alpha 5 ，α 6 ，α 7 ；β 1 ，β 2 ，β 3 ，β 4 ，β 5 ，β 6 ，β 7 ；γ 1 ，γ 2 ，γ 3 ，γ 4 ，γ 5 ，γ 6 ，γ 7 。
Further, the actual monitoring information of the kth sensor may be corrected based on the following formula:
(x k ′，y k ′，z k， ′α k ′，β k ′，γ k ′)＝(1-λ)(x k ， y k，z k， α k ，β k ，γ k )+λ(x p ，y p ，z p ，α p ，β p ，γ p )
wherein:
(x k ′，y k ′，z k， ′α k ′，β k ′，γ k ') the detection information after the k sensor correction is characterized;
x k ' characterizing coordinates in the x-axis direction in the detection information corrected by the kth sensor;
y k ' characterizing the coordinates in the y-axis direction in the detection information corrected by the kth sensor;
z k ' characterizing the z-axis coordinate in the detection information corrected by the kth sensor;
α k ' characterizing a rotation angle around an x-axis in the detection information corrected by the kth sensor;
β k ' characterizing a rotation angle around a y-axis in the detection information corrected by the kth sensor;
γ k ' characterizing a rotation angle around a z-axis in the detection information corrected by the kth sensor;
(x k ，y k ，z k， α k ，β k ，γ k ) Characterizing actual monitoring information of a kth sensor;
x k characterizing the coordinates in the x-axis direction in the actual detection information of the kth sensor;
y k characterizing the coordinate in the y-axis direction in the actual detection information of the kth sensor;
z k characterizing the coordinate in the z-axis direction in the actual detection information of the kth sensor;
α k characterizing the rotation angle around the x axis in the actual detection information of the kth sensor;
β k characterizing the rotation angle around the y axis in the actual detection information of the kth sensor;
γk represents the rotation angle around the z axis in the actual detection information of the kth sensor;
(x p ，y p ，z p ，α p ，β p ，γ p ) Predictive detection information characterizing a kth sensor；
x p Characterizing coordinates in the x-axis direction in the predictive detection information of the kth sensor;
y p characterizing coordinates in a y-axis direction in the predictive detection information of the kth sensor;
z p characterizing the z-axis coordinate in the predictive detection information of the kth sensor;
α p Characterizing a rotation angle around an x-axis in the predictive detection information of the kth sensor;
β p characterizing a rotation angle around a y-axis in the predictive detection information of the kth sensor;
γ p characterizing a rotation angle around a z-axis in the predictive detection information of the kth sensor;
λ is the first weighted value;
and 1-lambda is the second weighted value.
It can be seen that considering the respiratory model of the lung, the respiratory deformation of the lower lobe of the lung is greater than that of the middle lobe and the upper lobe of the lung, and the noise epsilon is increased sequentially from top to bottom. Based on this, the above proposal proposes a method of correcting in turn, and respiratory compensation is performed on the detection information of the following sensor by using the coordinates and angles (i.e., detection information) of the preceding sensor (closer to the upper lobe of the lung, less disturbed by respiration), so as to obtain more accurate coordinates and angles. And coordinates and angles are corrected by calculating distances (i.e., interval length information) and giving weights (embodied by the first weighting value λ and the second weighting values 1- λ).
In addition, as the information of the six degrees of freedom of the kth-1 sensor and the interval length information between the kth sensor and the kth sensor are known, under the constraint of the information and the information, the detection information of the kth sensor can be predicted by adopting any existing or improved prediction algorithm in the field to obtain corresponding prediction detection information, and other information can be combined for prediction in part of schemes. The predicted detection information may be all detection information (e.g., data of six degrees of freedom) of the kth sensor, or may be partial detection information (e.g., x-axis coordinates, y-axis coordinates, and z-axis coordinates) of the kth sensor. Regardless of which detection information is predicted, the manner in which the detection information is predicted does not depart from the scope of the embodiments of the present invention.
In one embodiment, the distribution positions of the N sensors may be determined according to a scanned image of the physiological channel to be measured, and the intervals of the N sensors are matched with the shape of the physiological channel to be measured represented by the scanned image.
The scan image may be, for example, but not limited to, a CT scan image of a physiological channel to be measured, and in addition, in determining a distribution position according to the scan image, the distribution position may be determined directly based on the scan image, or other information (e.g., a virtual model) may be formed based on the scan image, and then the distribution position may be determined based on the information.
Taking a bronchial tree as an example, the physiological structure of the bronchial tree can be fully considered by using a distribution strategy of N sensor positions, and specifically, the distribution strategy needs to ensure that the sensor at the front end can provide detection information, so that the detection information of the sensor at the rear end is corrected. At the same time, the distribution strategy also needs to ensure that registration and navigation of curvatures are achieved (e.g., ensuring that curvature shapes outlined based on the detection information can be used for curvature registration).
The distribution positions of the N sensors meet at least one of the following:
the length of the catheter part between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports in the bronchial tree to be tested; correspondingly, the distribution distance for the N sensors that can form the distribution strategy a= { is long enough to make: the contoured curvature (i.e., the at least partial catheter segment) may cover at least two bifurcation openings of the bronchial tree, as opposed to being of insufficient distance (which may be understood as the distribution distance of N sensors, and also as the length of the catheter portion between the first sensor and the last sensor), because a single bifurcation opening information is missing, it would be difficult to use to register the current curvature information with the reference curvature information;
The length of the catheter part between two adjacent sensors is shorter than the channel length between any two adjacent bifurcation openings in the bronchial tree to be tested; correspondingly, the distribution strategy b= { the distance between adjacent sensors may not be too long, preventing the outlining curvature (i.e. the at least part of the catheter sections) from losing a part of the bifurcation information };
the length of the catheter part between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be tested; correspondingly, a distribution strategy C= { needs to be formed, wherein the respiratory model (i.e. the virtual model) of the lung needs to be considered, the respiratory deformation of the lower lobe of the lung is larger than that of the middle lobe and the upper lobe of the lung, and the sensors need to be distributed in different lung segments as much as possible (for example, when navigating, some of the lower lobes and some of the middle lobes) }.
In a specific example, the distribution positions of the N sensors may satisfy the above distribution policies a, B, and C (i.e., take a N B C) at the same time.
In the above scheme, since the length between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports, the length can be necessarily longer than the longest channel length of the adjacent bifurcation ports, and further, the following can be ensured: the outlined curvature can fully cover at least two bifurcation ports, so that the defect of bifurcation ports is avoided, the requirement of subsequent positioning is met, and the positioning accuracy is improved.
Because the length between adjacent sensors is shorter than the channel length between any two adjacent bifurcation ports, the length can be necessarily shorter than the shortest channel length of the adjacent bifurcation ports, and further, the information of bifurcation ports can be prevented from being lost due to the outlining curvature, and the positioning accuracy is improved.
Because the length between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be detected, the sensors can be ensured not to be positioned in the same lung segment in a concentrated manner, and the positioning accuracy is ensured.
The process of determining the distribution positions of the N sensors according to the physiological channel to be measured may be implemented by the above execution body, may be implemented by other devices so as to be fed back to the execution body, may be implemented manually, or may be implemented by a combination of at least two of the execution body, other devices and a manual.
Specifically, referring to fig. 5, the navigation processing method further includes:
s23: and forming a virtual model of the physiological pipeline to be detected according to the scanning image, and using the virtual model as a determination basis of the N sensor distribution positions.
In one example, after forming the virtual model, the above executing subject or other device may automatically determine the distribution locations of the N sensors based on algorithms of the distribution strategy, as well as the relevant data of the catheter. In another example, after the virtual model is formed, the virtual model may also be fed back to the relevant personnel, who manually determine the final distribution position.
In the above alternatives, since the distribution positions of the N sensors are determined based on the scanned image and the virtual model of the physiological pipeline to be measured, the distribution result can be ensured to fully meet the requirement of the physiological pipeline to be measured.
Referring to fig. 12, the embodiment of the invention further provides a transcatheter navigation processing method, which includes:
s31: determining the corrected detection information of the N sensors by using the detection compensation method of multi-sensor navigation;
s32: and determining the position of the catheter in the physiological pipeline to be detected according to the corrected detection information.
In the above process, the current curvature information may be determined based on the corrected detection information, and the position of the catheter in the physiological conduit to be measured may be determined according to the current curvature information and the reference curvature information.
Wherein the current curvature information characterizes a current curvature of at least a portion of a catheter segment in the catheter; the at least partial conduit section matches the distribution position of the N sensors, for example, the at least partial conduit section may include a conduit section between a first sensor and a last sensor, but is not limited thereto.
The current curvature information may be any information capable of characterizing the curvature of at least a portion of the catheter segment, where the accuracy, manner, number of curvature data, etc. of the curvature characterization may be arbitrarily changed, and in some examples, the three-dimensional curvature may be calculated to obtain the current curvature information, or the curve may be projected onto one or more surfaces, and then the two-dimensional curvature may be calculated to obtain the current curvature information, where the curvature may be the curvature of the catheter contour line or the curvature of the equivalent curve of the catheter.
The reference curvature information characterizes the curvature of each pipeline section in the physiological pipeline to be tested. The curvature may be the curvature of the contour line of the physiological conduit or the curvature of the equivalent curve of the physiological conduit. In particular, it may be determined based on the scanned image and/or the virtual model.
Furthermore, by registering the curvature represented by the current curvature information with the curvature represented by the reference curvature information, the position of the at least part of the pipe section in the physiological pipeline to be detected can be found.
Referring to fig. 13, a detection compensation device 400 for multi-sensor navigation includes:
the acquisition module 401 is configured to acquire actual detection information of the N sensors after the catheter enters the physiological pipeline to be detected, where the detection information characterizes a position and an attitude of a catheter position where the sensor is located;
and the correction module 402 is configured to correct at least part of the actual detection information of the sensors according to the actual detection information of the N sensors and the interval length information between the sensors, so as to obtain corrected detection information, where the interval length information characterizes the length of the catheter portion between the sensors in the catheter.
Optionally, the correction module 402 is specifically configured to:
For any kth sensor, according to detection information of one or more sensors between the kth sensor and an inlet of the physiological channel to be detected and interval length information between the kth sensor and the kth sensor, the actual detection information of the kth sensor is corrected, wherein k is greater than or equal to 2, the kth sensor refers to the kth sensor which is distributed along a target sequence in the N sensors, and the target sequence is opposite to the sequence in which the sensors sequentially enter the physiological channel to be detected.
Optionally, the correction module 402 is specifically configured to:
predicting at least part of detection information of the kth sensor according to the actual detection information or the corrected detection information of the mth sensor and the interval length information between the kth sensor and the mth sensor to obtain the prediction detection information of the kth sensor; wherein m is less than k;
and correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor.
Optionally, m=k-1, and the detection information of at least part of the sensors is sequentially corrected along the target sequence.
Optionally, the predicted detection information includes position information of a predicted position of the kth sensor, and a distance between the predicted position and a position characterized by the detection information of the mth sensor matches interval length information between the kth sensor and the mth sensor.
Optionally, the correction module 402 is specifically configured to:
determining a corresponding extension line according to the actual detection information or the corrected detection information of the mth sensor, wherein the position of the extension line is matched with the position represented by the corresponding detection information, and the extension direction of the extension line is matched with the gesture represented by the corresponding detection information;
and determining the predicted position according to the extension line and the interval length information between the kth sensor and the mth sensor.
Optionally, the predicted detection information further includes posture information of a predicted posture of the kth sensor, and the predicted posture is matched with the posture of the mth sensor.
Optionally, the correction module 402 is specifically configured to:
correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information;
Wherein the correction reference information includes: the first correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the prediction detection information, and/or the second correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the actual detection information.
Optionally, the revised reference information for the different order sensors is different, and:
and in the N sensors, the closer to the inlet of the physiological channel to be detected, the lower the matching degree represented by the first correction reference information of the sensor is, and the higher the matching degree represented by the second correction reference information is.
Optionally, the correction module 402 is specifically configured to:
according to the correction reference information, carrying out weighted summation on the prediction detection information of the kth sensor and the actual detection information of the kth sensor to obtain detection information after correction of the kth sensor; the first correction reference information is a first weighted value corresponding to the prediction detection information, and the second correction reference information is a second weighted value corresponding to the actual detection information.
Optionally, the correction module 402 is specifically configured to:
correcting the actual monitoring information of the kth sensor based on the following formula:
(x k ′，y k ′，z k ，′α k ′，β k ′，γ k ′)＝(1-λ)(x k ，y k ，z k ，α k ，β k ，γ k )+λ(x p ，y p ，z p ，α p ，β p ，γ p )
wherein:
(x k ′，y k ′，z k ，′α k ′，β k ′，γ k ') the detection information after the k sensor correction is characterized;
x k ' characterizing coordinates in the x-axis direction in the detection information corrected by the kth sensor;
y k ' characterizing the coordinates in the y-axis direction in the detection information corrected by the kth sensor;
z k ' characterizing the z-axis coordinate in the detection information corrected by the kth sensor;
α k ' characterizing a rotation angle around an x-axis in the detection information corrected by the kth sensor;
β k ' characterizing a rotation angle around a y-axis in the detection information corrected by the kth sensor;
γ k ' characterizing a rotation angle around a z-axis in the detection information corrected by the kth sensor;
(x k ，y k ，z k ，α k ，β k ，γ k ) Characterizing actual monitoring information of a kth sensor;
x k characterizing the coordinates in the x-axis direction in the actual detection information of the kth sensor;
y k characterizing the coordinate in the y-axis direction in the actual detection information of the kth sensor;
z k characterizing the coordinate in the z-axis direction in the actual detection information of the kth sensor;
α k characterizing the rotation angle around the x axis in the actual detection information of the kth sensor;
β k Characterizing the rotation angle around the y axis in the actual detection information of the kth sensor;
γ k characterizing the rotation angle around the z axis in the actual detection information of the kth sensor;
(x p ，y p ，z p ，α p ，β p ，γ p ) Predictive detection information characterizing a kth sensor;
x p characterizing coordinates in the x-axis direction in the predictive detection information of the kth sensor;
y p characterizing coordinates in a y-axis direction in the predictive detection information of the kth sensor;
z p characterizing the z-axis coordinate in the predictive detection information of the kth sensor;
α p characterizing a rotation angle around an x-axis in the predictive detection information of the kth sensor;
β p characterizing a rotation angle around a y-axis in the predictive detection information of the kth sensor;
γ p characterizing a rotation angle around a z-axis in the predictive detection information of the kth sensor;
λ is the first weighted value;
and 1-lambda is the second weighted value.
Optionally, the distribution positions of the N sensors are determined according to a scanned image of the physiological channel to be measured, and the intervals of the N sensors are matched with the shape of the physiological channel to be measured represented by the scanned image.
Optionally, referring to fig. 14, the detection compensation device 400 for multi-sensor navigation further includes:
And the model determining module is used for forming a virtual model of the physiological pipeline to be detected according to the scanning image, and using the virtual model as a determining basis of the N sensor distribution positions.
Optionally, the physiological channel to be measured is a bronchial tree to be measured,
the distribution positions of the N sensors meet at least one of the following:
the length of the catheter part between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports in the bronchial tree to be tested;
the length of the catheter part between two adjacent sensors is shorter than the channel length between any two adjacent bifurcation openings in the bronchial tree to be tested;
the length of the catheter portion between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be tested.
Referring to fig. 15, a transcatheter navigation processing device 500 includes:
a detection compensation unit 501, configured to determine detection information after correction of the N sensors by using the detection compensation method of multi-sensor navigation;
and the positioning unit 502 is used for determining the position of the catheter in the physiological pipeline to be detected according to the corrected detection information.
Referring to fig. 16, there is provided an electronic device 60 comprising:
a processor 61; the method comprises the steps of,
a memory 62 for storing executable instructions of the processor;
wherein the processor 61 is configured to perform the above-mentioned method via execution of the executable instructions.
The processor 61 is capable of communicating with the memory 62 via the bus 63.
The embodiments of the present invention also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the methods referred to above.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (15)

1. The detection compensation device for the multi-sensor navigation is characterized in that N sensors are arranged on a catheter, and the N sensors are sequentially distributed at different positions in the length direction of the catheter, wherein N is greater than or equal to 2;
a detection compensation device for multi-sensor navigation, comprising:
the acquisition module is used for acquiring actual detection information of the N sensors after the catheter enters the physiological channel to be detected, wherein the actual detection information characterizes the position and the gesture of the catheter position where the sensors are positioned;
the correction module is used for determining a corresponding extension line according to the actual detection information or the corrected detection information of any mth sensor in the N sensors, the position of the extension line is matched with the position represented by the corresponding detection information, and the extension direction of the extension line is matched with the gesture represented by the corresponding detection information; determining position information of a predicted position in predicted detection information of a kth sensor according to the extension line and interval length information between the kth sensor and the mth sensor; the kth sensor refers to kth sensors which are distributed in sequence along a target sequence in the N sensors; wherein m is less than k; the interval length information characterizes the length of a catheter part between sensors in the catheter, wherein k is greater than or equal to 2, and the target sequence is opposite to the sequence of the sensors entering the physiological channel to be detected in sequence; correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor; the distance between the predicted position and the position represented by the detection information of the mth sensor is matched with the interval length information between the kth sensor and the mth sensor, and the corrected detection information represents the position and the posture of the catheter position where the sensor is located.
2. The multi-sensor navigation detection compensation apparatus of claim 1, wherein m = k-1, the actual detection information of the sensors is sequentially modified along the target order.
3. The detection compensation device for multi-sensor navigation according to claim 1, wherein the predicted detection information further includes posture information of a predicted posture of the kth sensor, the predicted posture matching a posture of the mth sensor.
4. The multi-sensor navigation detection compensation apparatus of claim 1,
correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor to obtain corrected detection information of the kth sensor, wherein the method specifically comprises the following steps of:
correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information;
wherein the correction reference information includes: the first correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the prediction detection information, and/or the second correction reference information characterizes the matching degree of the detection information corrected by the corresponding sensor and the actual detection information.
5. The detection compensation device for multi-sensor navigation according to claim 4, wherein the corrected reference information of the sensors of different orders is different, and:
and in the N sensors, the closer to the inlet of the physiological channel to be detected, the lower the matching degree represented by the first correction reference information of the sensor is, and the higher the matching degree represented by the second correction reference information is.
6. The multi-sensor navigation detection compensation apparatus of claim 4,
correcting the actual detection information of the kth sensor according to the predicted detection information of the kth sensor and the set correction reference information, wherein the method specifically comprises the following steps:
according to the correction reference information, carrying out weighted summation on the prediction detection information of the kth sensor and the actual detection information of the kth sensor to obtain detection information after correction of the kth sensor; the first correction reference information is a first weighted value corresponding to the prediction detection information, and the second correction reference information is a second weighted value corresponding to the actual detection information.
7. The multi-sensor navigation detection compensation apparatus of claim 6, wherein,
According to the corrected reference information, the method carries out weighted summation on the predicted detection information of the kth sensor and the actual detection information of the kth sensor to obtain the detection information corrected by the kth sensor, and specifically comprises the following steps:
correcting the actual monitoring information of the kth sensor based on the following formula:
(x k ′,y′ k ，z′ k ，α k ′，β k ′，γ k ′)＝(1-λ)(x k ,y k ，z k ，α k ，β k ，γ k )+λ(x p ,y p ，z p， α p ，β p ，γ p )
wherein:
(x k ′,y′ k ，z′ k ，α k ′，β k ′，γ k ') the detection information after the k sensor correction is characterized;
x k ' characterizing coordinates in the x-axis direction in the detection information corrected by the kth sensor;
y k ' characterizing the coordinates in the y-axis direction in the detection information corrected by the kth sensor;
z k ' characterizing the z-axis coordinate in the detection information corrected by the kth sensor;
α k ' characterizing a rotation angle around an x-axis in the detection information corrected by the kth sensor;
β k ' characterizing a rotation angle around a y-axis in the detection information corrected by the kth sensor;
γ k ' characterizing a rotation angle around a z-axis in the detection information corrected by the kth sensor;
(x k ,y k ，z k ，α k ，β k ，γ k ) Characterizing actual monitoring information of a kth sensor;
x k characterizing the coordinates in the x-axis direction in the actual detection information of the kth sensor;
y k characterizing the coordinate in the y-axis direction in the actual detection information of the kth sensor;
z k Characterizing the coordinate in the z-axis direction in the actual detection information of the kth sensor;
α k characterizing the rotation angle around the x axis in the actual detection information of the kth sensor;
β k characterizing the rotation angle around the y axis in the actual detection information of the kth sensor;
γ k characterizing the rotation angle around the z axis in the actual detection information of the kth sensor;
(x p ,y p ，z p ，α p ，β p ，γ p ) Predictive detection information characterizing a kth sensor;
x p characterizing coordinates in the x-axis direction in the predictive detection information of the kth sensor;
y p characterizing coordinates in a y-axis direction in the predictive detection information of the kth sensor;
z p characterizing the z-axis coordinate in the predictive detection information of the kth sensor;
α p characterizing a rotation angle around an x-axis in the predictive detection information of the kth sensor;
β p characterizing a rotation angle around a y-axis in the predictive detection information of the kth sensor;
γ p characterizing a rotation angle around a z-axis in the predictive detection information of the kth sensor;
λ is the first weighted value;
and 1-lambda is the second weighted value.
8. The multi-sensor navigation detection compensation apparatus according to any one of claims 1 to 7, wherein the distribution positions of the N sensors are determined according to a scanned image of a physiological channel to be detected, and the intervals of the N sensors are matched with the shape of the physiological channel to be detected represented by the scanned image.
9. The detection compensation device for multi-sensor navigation of claim 8, further comprising:
and the model determining module is used for forming a virtual model of the physiological channel to be detected according to the scanning image, and using the virtual model as a determining basis of the N sensor distribution positions.
10. The multi-sensor navigation detection compensation apparatus of claim 8, wherein the physiological channel to be detected is a bronchial tree to be detected,
the distribution positions of the N sensors meet at least one of the following:
the length of the catheter part between the first sensor and the last sensor is longer than the channel length between any two adjacent bifurcation ports in the bronchial tree to be tested;
the length of the catheter part between two adjacent sensors is shorter than the channel length between any two adjacent bifurcation openings in the bronchial tree to be tested;
the length of the catheter portion between the first sensor and the last sensor is longer than the length of any lung segment in the bronchial tree to be tested.
11. A transcatheter navigation processing device, comprising:
a detection compensation unit for determining the detection information corrected by the N sensors using the functions of the detection compensation device for multi-sensor navigation according to any one of claims 1 to 10;
And the positioning unit is used for determining the position of the catheter in the physiological channel to be detected according to the corrected detection information.
12. An electronic device, comprising a processor and a memory,
the memory is used for storing codes;
the processor is configured to execute the code in the memory to implement the functions of the detection compensation device for multi-sensor navigation of any one of claims 1 to 10 or the functions of the catheter navigation processing device of claim 11.
13. A storage medium having stored thereon a computer program which, when executed by a processor, implements the function of the detection compensation device for multi-sensor navigation according to any one of claims 1 to 10, or the function of the catheter navigation processing device according to claim 11.
14. A transcatheter navigation system comprising: the device comprises a catheter, N sensors and a data processing module, wherein the N sensors are arranged on the catheter and are sequentially distributed at different positions in the length direction of the catheter, and the data processing module can be directly or indirectly communicated with the N sensors;
The data processing module is configured to perform the functions of the detection compensation apparatus for multi-sensor navigation according to any one of claims 1 to 10, or the functions of the catheter navigation processing apparatus according to claim 11.
15. The transcatheter navigation system of claim 14, wherein the sensor is a magnetic navigation sensor.
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