CN114897879A - Axial scanning path planning method for intelligent fitting of SPECT-CT (single photon emission computed tomography-computed tomography) human body contour - Google Patents

Axial scanning path planning method for intelligent fitting of SPECT-CT (single photon emission computed tomography-computed tomography) human body contour Download PDF

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CN114897879A
CN114897879A CN202210645637.0A CN202210645637A CN114897879A CN 114897879 A CN114897879 A CN 114897879A CN 202210645637 A CN202210645637 A CN 202210645637A CN 114897879 A CN114897879 A CN 114897879A
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江年铭
黄涛
曹卫胜
赵志
王颜辉
侯岩松
刘迈
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Abstract

The application discloses a SPECT-CT human body contour intelligent fitting axial scanning path planning method, which comprises the following steps: step 1, performing initial contour tracking on a patient by using SPECT-CT equipment to acquire an initialization matrix; step 2, calculating the thickness of the human body and the deceleration distance of the probe according to the position data of the first probe and the position data of the second probe at adjacent sampling moments in the initial contour tracking process, and generating an original data matrix based on the thickness of the human body, the deceleration distance of the probe and the bed entering position at each sampling moment; and 3, optimally calculating the thickness of the human body and the deceleration distance of the probe, determining the optimal thickness of the human body and the optimal position of the probe in an iterative mode, updating the initialization matrix according to the calculated optimal position of the probe, and generating a scanning path planning matrix. Through the technical scheme in this application, solved the size partially fat patient and probably extruded problem by equipment when carrying out whole body scanning, optimized the axial scanning route planning of equipment probe.

Description

Axial scanning path planning method for intelligent fitting of SPECT-CT (single photon emission computed tomography-computed tomography) human body contour
Technical Field
The application relates to the technical field of medical equipment, in particular to an axial scanning path planning method for intelligent fitting of a SPECT-CT human body contour.
Background
When a SPECT-CT apparatus is used to scan the whole body of a patient, the general procedure is: the patient lies on the examination bed of the equipment according to the body orientation that the head is outside and the feet are inside, and the step of the patient is close to one side of the SPECT-CT equipment probe; the couch is pushed by the doctor/technician, the patient is pushed to the detection start position inside the SPECT-CT apparatus, and the apparatus is operated to start performing a whole-body scan. During the scanning process, the SPECT-CT equipment probe moves up and down along with the slow exit of the examination bed, and scans from the head of the patient to the feet of the patient to complete the whole body scanning and imaging.
In the scanning process, the SPECT-CT equipment probe moves according to a human body contour tracking mode, and when the examination bed moves outwards, the probe needs to detect again and adjust the distance with the human body, so that the SPECT-CT equipment probe always keeps the same distance with the human body contour, and the closer the SPECT-CT equipment probe is to the human body, the more beneficial the clear imaging of the SPECT-CT equipment is.
The SPECT-CT equipment probe adjusts the distance between the human body and the probe mainly through the feedback of the light curtain signal, and the light curtain is arranged on the outer edge of the collimator of the probe. When the probe is in the work of the human body contour tracking mode, the probe can be gradually close to the human body, after the human body enters the detection range of the probe light curtain, the light curtain signal is shielded, after the outer layer light curtain signal is shielded, the probe stops moving, and when the inner layer light curtain and the outer layer light curtain are shielded, the probe moves towards the direction far away from the human body.
The adjustment mode of the SPECT-CT equipment probe can not smoothly complete the whole-body scanning process for patients with fat body types. After the examination couch moves outwards from the SPECT-CT equipment and images the head and neck of a patient, the probe moves downwards to be close to the head and neck of the patient, the connection part of the probe and the base shaft is already outside the detection range of a light curtain signal, and the position with larger or more changed trend of the body shape curve in the sagittal direction of a human body, such as the abdomen of a patient with fat body, is protruded, so that the connection part of the probe and the base shaft (A shaft) of the equipment shaft can have the risk of pressing the patient, and the normal whole body scanning detection process can not be carried out, even the patient can be pressed.
Disclosure of Invention
The purpose of this application lies in: the problem that the part with large body type change is possibly extruded by equipment when the SPECT-CT equipment is used for whole body scanning is solved, particularly for fat patients, and the axial scanning path planning of a SPECT-CT equipment probe is optimized.
The technical scheme of the application is as follows: an axial scanning path planning method for intelligent fitting of a SPECT-CT human body contour is provided, which comprises the following steps: step 1, performing initial contour tracking on a patient by using SPECT-CT equipment to obtain an initialization matrix representing the position of a probe and the position of a bed plate; step 2, calculating the thickness of the human body and the deceleration distance of the probe according to the position data of the first probe and the position data of the second probe at adjacent sampling moments in the initial contour tracking process, and generating a corresponding original data matrix based on the thickness of the human body, the deceleration distance of the probe and the bed entering position at each sampling moment; and 3, performing optimized calculation on the corresponding human body thickness and the probe deceleration distance in the original data matrix according to the distance mean value of the probe deceleration distance, determining the optimal human body thickness and the optimal position of the probe in an iterative mode, updating the initialization matrix according to the calculated optimal position of the probe, and generating a scanning path planning matrix.
In any of the above technical solutions, further, in step 2, the thickness H of the human body is calculated i And probe deceleration distance deltaY i The corresponding calculation formula is:
ΔY i ＝Y j -Y i
H i ＝Y j -T
in the formula,. DELTA.Y i For the probe deceleration distance corresponding to the previous sampling time, i is 1,2, …, N, Y j Is the second probe position data, Y, corresponding to the current sampling time when the probe is stopped i First probe position data, H, at the time of triggering of the probe light curtain corresponding to the previous sampling moment i The height data of the examining table is T.
In any of the above technical solutions, further, an interval between two adjacent sampling time instants is 10 ms.
In any of the above technical solutions, further, the original data matrix is:
Figure BDA0003683979720000031
in the formula, H i Is the thickness of the human body corresponding to the last sampling time i, delta Y i For the probe deceleration distance, Z, corresponding to the last sampling instant i i Is the position of the bed plate corresponding to the last sampling moment i.
In any of the above technical solutions, further, in step 3, according to the distance average of the probe deceleration distance, the corresponding human body thickness H in the original data matrix is measured i And probe deceleration distance DeltaY i Performing optimization calculation, specifically including:
step 301, selecting any probe deceleration distance delta Y from the original data matrix i Presetting a number of adjacent values, and calculating a distance average value, wherein a corresponding calculation formula is as follows:
Figure BDA0003683979720000032
in the formula,. DELTA.Y i m For the i-th probe deceleration distance DeltaY i The adjacent mth value;
302, according to the distance mean, the thickness H of the human body i And probe deceleration distance DeltaY i And carrying out optimization calculation.
In any of the above technical solutions, further, in step 302, the human body thickness H is calculated according to the distance average i And probe deceleration distance DeltaY i Carrying out optimization calculation, wherein the corresponding calculation formula is as follows:
ΔY i ′＝ΔY i -ΔY i "
H′ i ＝Y i +ΔY i ′-T
in the formula,. DELTA.Y i 'optimized ith probe deceleration distance, H' i For optimized body thickness, Δ Y i For the i-th probe deceleration distance, Δ Y i "is the distance mean value corresponding to the deceleration distance of the ith probe, Y i The first probe position data when the probe light curtain is triggered is shown, and T is the height data of the examination bed.
In any of the above technical solutions, further, an optimal human body thickness H is determined i "sum Probe optimum position Y j ", specifically includes: 311, decelerating the optimized probe by a distance delta Y i ', human thickness H' i Inputting the initial value into a linear regression equation to calculate the deceleration distance of the optimizing probe and the thickness of the optimized human body; step 312, respectively calculating the deceleration distance of the optimizing probe, the distance difference and the thickness difference between the thickness of the optimized human body and the corresponding initial values, and respectively calculating the distance difference, the thickness difference, the current deceleration distance of the optimizing probe and the distance ratio and the thickness ratio of the optimized human body; 313, judging whether the distance ratio and the thickness ratio are both smaller than the error threshold, if so, recording the current deceleration distance of the optimizing probe and the optimized human body thickness as the optimal human body thickness H respectively i ", optimum position of probe Y j Otherwise, inputting the deceleration distance of the current optimizing probe and the thickness of the optimized human body into the linear regression equation again in an iterative mode, and calculating the deceleration distance of the optimizing probe and the thickness of the optimized human body in the next iteration; step 314, calculating the deceleration distance and optimization of the optimizing probe of the next iteration respectivelyAnd (4) performing step 312 according to the deceleration distance of the human body thickness and the last iterative calculation of the optimizing probe, the distance difference value and the thickness difference value of the optimized human body thickness.
In any of the above technical solutions, further, a value of the error threshold is 0.001.
In any of the above technical solutions, further, the scan path planning matrix is:
Figure BDA0003683979720000041
in the formula, Z i The position of the bed plate corresponding to the ith sampling position, Y i "is the optimal position of the probe corresponding to the ith sampling position.
The beneficial effect of this application is:
according to the technical scheme, on the basis that hardware equipment does not need to be added and the structure of the existing equipment is not changed, after the initialization matrix representing the position of the probe and the position of the bed board is obtained through the pre-scanning mode, the corresponding thickness of the human body and the probe deceleration distance are calculated according to the probe position data at the adjacent sampling moments, so that the original data matrix is obtained, and further, the optimal thickness of the human body and the optimal position of the probe are determined in an iteration mode to generate a scanning path planning matrix, the problem that a patient with a fat body type is possibly extruded by equipment when the patient uses SPECT-CT equipment to perform whole body scanning is solved, the conventional scanning mode cannot be influenced, meanwhile, a doctor/technician can be helped to observe a generated technician track before detection, better equipment operation is achieved for the doctor/technician, and medical experience of the patient is improved.
Through data testing, when the axial scanning path planning method is used for scanning people with normal height, the in-bed trajectory recording and generating can be expected to be completed in less than 1 minute, the increased time of in-bed scanning and trajectory generating has no great influence on the whole examination, and for fat patients with large stomachs, the scanning operation is beneficial to obtaining the optimal image quality while ensuring the safety.
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The advantages of the above and/or additional aspects of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow diagram of a SPECT-CT human body contour intelligent fitting axial scan path planning method according to one embodiment of the present application;
FIG. 2 is a schematic diagram of SPECT-CT device scanning principles according to one embodiment of the present application;
FIG. 3 is a schematic diagram of a SPECT-CT device global coordinate system according to an embodiment of the present application;
FIG. 4 is a schematic diagram of sample time data relationships according to an embodiment of the present application;
FIG. 5 is a schematic illustration of body thickness according to an embodiment of the present application;
FIG. 6 is a schematic flow diagram of an intelligent AI algorithm according to one embodiment of the present application;
FIG. 7 is a schematic diagram of a three-dimensional model of a probe and a device axis according to an embodiment of the present application.
Detailed Description
In order that the above objects, features and advantages of the present application can be more clearly understood, the present application will be described in further detail with reference to the accompanying drawings and detailed description. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited by the specific embodiments disclosed below.
As shown in fig. 1, the present embodiment provides a SPECT-CT human body contour intelligent fitting axial scan path planning method, which includes:
step 1, performing initial contour tracking on a patient lying on an examination table by using a pre-scanning mode in SPECT-CT equipment to obtain an initialization matrix representing the position of a probe and the position of a bed plate;
in this embodiment, the patient is set to lie on the examination table of the apparatus with the head on the outside and the feet on the inside, as shown in fig. 2 and 3, a global coordinate system of the SPECT-CT apparatus is established, wherein a curve 200 in fig. 2 is a scan path plan.
The SPECT-CT device starts a pre-scanning mode and controls the examination bed to enter a predetermined detection position specified by a clinical scanning protocol. During the process of controlling the bed entering in the pre-scanning mode, the bed entering condition is monitored by a device operator (such as a doctor), the SPECT-CT device starts the pre-scanning mode, and the bed entering is completed from the head of the patient to the end of the leg reaching the detection position.
In the whole bed entering process, the upper computer monitors and records the current coordinate position of the probe every 10ms, and after the whole bed entering process is completed, the coordinate position of the probe recorded by the upper computer forms a detected probe contour track which is the basis of a subsequent intelligent fitting scanning path, namely an initial axial scanning path.
In this embodiment, the initial axial scanning path is formed by the data acquisition server reading the data of the bed plate position (Z coordinate) and the probe position (Y coordinate) fed back by the position encoder to form a data pair, and the series of data pairs may form an initialization matrix, and the format of the initialization matrix is as follows:
Figure BDA0003683979720000061
where n is the number of sample points, i is 1,2, …, n, Y i For the corresponding probe position, Z, at the ith sampling point i Is the corresponding bed plate position at the ith sampling point (sampling time), wherein the bed plate position is the bed entering position of the upper bed plate of the examination bed at the sampling time with the interval of 10 ms.
In this embodiment, the upper bed plate of the examination bed is driven by the motor to enter the bed from the initial position to the predetermined detection position at a constant speed.
It should be noted that, during the pre-scanning process, corresponding initial parameters also need to be set, and the initial parameters at least include: probe parameters, scanning protocols, and configuration parameters.
Step 2, according to the first probe position data Y of adjacent sampling moments in the initial contour tracing process i And second probe position data Y j Calculating the thickness H of the human body i And probe deceleration distance DeltaY i And based on the thickness H of the human body i Probe deceleration distance delta Y i Generating a corresponding original data matrix according to the bed entering position of each sampling moment;
Figure BDA0003683979720000071
wherein the first probe position data Y i The position data Y of the probe when the light curtain of the probe is triggered at the last sampling moment and the position data Y of the second probe j The probe position when the probe stops at the current sampling moment is the probe position, and the interval between two adjacent sampling moments is 10 ms;
in this embodiment, the communication cycles of the upper computer, the SPECT-CT apparatus gantry, and the examination couch are set to be the same, with an interval of 10 ms. The upper computer triggers a synchronous clock, and then a controller of a scanning frame of the SPECT-CT equipment records first probe position data Y when a probe light curtain is triggered at the frequency of 10ms interval i And second probe position data Y when the probe is stopped j And the controller of the examination bed records the height data T of the examination bed and the position data Z of the bed board of the upper bed at the same time.
As shown in fig. 4 and 5, the upper computer reads the data recorded by the controllers of the SPECT-CT equipment scanning frame and the examination bed respectively in a communication period of 100ms, and then calculates the human body thickness H at the corresponding sampling moment through a formula i And probe deceleration distance DeltaY i The corresponding calculation formula is:
ΔY i ＝Y j -Y i
H i ＝Y j -T
in the formula,. DELTA.Y i For the probe deceleration distance corresponding to the previous sampling time, i is 1,2, …, N, Y j For the second time when the probe corresponding to the current sampling time stopsProbe position data, Y i First probe position data, H, at the time of triggering of the probe light curtain corresponding to the previous sampling moment i Is the thickness of the human body corresponding to the last sampling moment, T is the height data of the examining table, is a set value, Y 1 The initial value is set to 1100 as the system initial coordinate value, and the probe position at the beginning of bed entering.
After the bed entering process is finished, the upper computer combines the corresponding positions of the examining bed in the bed entering process according to all the data obtained by calculation to form an original data matrix of the thickness of the human body and the deceleration distance of the probe, and the format of the original data matrix is as follows:
Figure BDA0003683979720000081
step 3, according to the distance average value of the probe deceleration distance, corresponding human body thickness H in the original data matrix i And probe deceleration distance DeltaY i Performing optimization calculation, and determining the optimal human body thickness H in an iterative manner i "sum Probe optimum position Y j According to the calculated optimal position Y of the probe j And updating the initialization matrix to generate a scanning path planning matrix.
Further, in step 3, according to the distance average value of the probe deceleration distance, the corresponding human body thickness H in the original data matrix is measured i And probe deceleration distance DeltaY i Performing optimization calculation, specifically including:
step 301, selecting any probe deceleration distance delta Y from the original data matrix i Presetting a number of adjacent values, and calculating a distance average value, wherein a corresponding calculation formula is as follows:
Figure BDA0003683979720000082
in the formula,. DELTA.Y i m For the i-th probe deceleration distance DeltaY i The M-th adjacent value, M is 1,2, …, M, where M may be 10.
That is, the ith probe is selectedDeceleration distance Δ Y i Adjacent 10 values are taken to calculate the distance average value, and when enough values are taken on two sides of i, the selected value range is [ i-4, i-3, …, i, i +1, i +2, …, i +5 ]]If the value of one side is insufficient, the value of the other side is used for supplementing 10 values, and the specific process is not repeated.
302, according to the distance mean, the thickness H of the human body i And probe deceleration distance DeltaY i Carrying out optimization calculation, wherein the corresponding calculation formula is as follows:
ΔY i ′＝ΔY i -ΔY i "
H′ i ＝Y i +ΔY i ′-T
in the formula,. DELTA.Y i 'optimized ith probe deceleration distance, H' i For optimized body thickness, Δ Y i For the i-th probe deceleration distance, Δ Y i "is the distance mean value corresponding to the deceleration distance of the ith probe, Y i The first probe position data when the probe light curtain is triggered is shown, and T is the height data of the examination bed.
Specifically, the upper computer draws an axial scanning human body curve path and a detector motion curve through a data matrix, performs curve simulation calculation to obtain the human body thicknesses and detector stopping distances of all beds, and then performs data statistics and average number calculation;
Figure BDA0003683979720000091
wherein, Delta Y i "is the average of the differences between the test value and its linear regression value, M is constant 10, i.e. every 10 Δ Y i Determining a value of Delta Y i "。
The optimized probe stopping distance can then be found:
ΔY i ′＝ΔY i -ΔY i "
and the optimized human body thickness:
H′ i ＝Y i +ΔY i ′-T。
all calculation results form an array to obtain optimized human body thickness data and a probe stop position matrix:
Figure BDA0003683979720000092
on the basis of the above embodiment, in step 3, the optimal human body thickness H is determined in an iterative manner i "sum Probe optimum position Y j ", specifically includes:
311, decelerating the optimized probe by a distance delta Y i ', human thickness H' i Inputting the initial value into a linear regression equation to calculate the deceleration distance of the optimizing probe and the thickness of the optimized human body;
step 312, respectively calculating the deceleration distance of the optimizing probe, the distance difference and the thickness difference between the thickness of the optimized human body and the corresponding initial values, and respectively calculating the distance difference, the thickness difference, the distance ratio and the thickness ratio of the current deceleration distance of the optimizing probe and the thickness of the optimized human body;
313, judging whether the distance ratio and the thickness ratio are both smaller than the error threshold, if so, recording the current deceleration distance of the optimizing probe and the optimized human body thickness as the optimal human body thickness H respectively i ", optimum position of probe Y j Otherwise, inputting the deceleration distance of the current optimizing probe and the thickness of the optimized human body into the linear regression equation again in an iterative mode, and calculating the deceleration distance of the optimizing probe and the thickness of the optimized human body in the next iteration; wherein, the value of the error threshold may be 0.001.
And step 314, respectively calculating the deceleration distance of the optimizing probe and the thickness of the optimizing human body in the next iteration, and the distance difference and the thickness difference between the deceleration distance of the optimizing probe and the thickness of the optimizing human body calculated in the previous iteration, and executing the step 312.
In this embodiment, a detection track can be generated by fitting in combination with the bed-entering speed of the examination bed to approach a special human body contour, thereby forming an axial intelligent scanning path plan.
Combining the optimized human body thickness data and the probe stop position matrix with the bed entering speed, further using an intelligent AI algorithm to fit and generate a detection track to approach a special human body contour, and forming an axial intelligent scanning path plan; in addition, during bed exit detection, Smart scanning (Smart Scan) is performed based on the generated trajectory, and still profile tracking is enabled for safety assistance.
As shown in fig. 6, the description for the above intelligent AI algorithm is as follows: the motion trail relates to the motion of the probe and a plurality of axes of the examination bed: the probe comprises a Z axis, an X axis, a Y axis and an A axis, wherein the A axis and the X axis are in linkage, so that the probe is positioned at different angles on the circumference and can be regarded as a variable, the Z axis is in axial motion, and the axial length range of the whole human body is divided into equal-quota intervals, such as 50 equal parts, according to the direction of the Z axis.
In this embodiment, the calculated optimal human body thickness is H i The optimum position of the probe is Y j ", wherein, H 1 "optimum position of corresponding Probe Y 1 ″，H 2 "corresponds to Y 2 ″，……，H 50 "corresponds to Y 50 And so on. The linear regression equation was established as follows:
Figure BDA0003683979720000111
Figure BDA0003683979720000112
……
Figure BDA0003683979720000113
it should be noted that, through actual operation, a training set is formed by acquiring a good-effect operation track, a linear regression function training is performed in a TensorFlow toolkit, and the deceleration distance of the optimizing probe and the optimized human body thickness (Y) calculated in an iterative process are utilized 1b ′,H 1b ') can obtain the vector a 1,b ，(Y 2b ′,H 2b ') obtain a vector a 2,b And sequentially acquiring all a vector matrixes A. In actual detection, every equal part of human body thickness is used as input, the input is multiplied by the matrix A to obtain a group of optimal axial track node values, and the nodes directly use a piecewise average value function.
As shown in fig. 7, in practical engineering verification, it is found that the size of the SPECT-CT probe is large, and the influence of the shape of the probe on the scan path of the intelligent human body contour fitting is large, and the method must be modified by the following method: when the bed entering probe rises, the bed entering probe rises by D 2 When the point and the probe descend, the angle is D 1 Recording an initial track by points; when the probe ascends during bed withdrawal, the probe is driven to move in a direction D 1 When the point and the probe descend, the angle is D 2 And performing axial intelligent scanning path planning by taking the points as reference points. Requiring horizontal movement before switching reference points D X Distance. The intelligent path planning for exiting the bed will replace the initial path trajectory as output. D X 、D y1 And D y2 The system is configured as an initial parameter for intelligent scanning.
It should be noted that the resolution of the whole-body planar image of the SPECT-CT apparatus is independent of the scan speed, count, but the stability increases with the increase of the count; at the same count, scan stability is independent of scan speed.
When the intelligent AI algorithm plans an axial path, the position coordinates (the probe and the bed plate), the scanning speed (the movement speed of the bed plate) and the count (data points acquired by the probe) can be optimally matched according to the resolution and the scanning stability of the planar imaging, so that the optimal resolution and stability can be obtained under the conditions of different positions, speeds and counts, and the fastest scanning speed under the required resolution and stability can be met.
In addition, for the recorded value of the coordinate position of the upper computer tracked by the profile, path deviation such as an inertia link of mechanical control motion, a delay link of probe trigger movement and the like is considered, and the correction is carried out according to the optimal resolution ratio by combining an algorithm of dynamic step length and track fitting and through automatic control modeling and track analysis of the probe and the bed plate, so that the motion of the probe is closest to the human body and the optimal image quality is achieved.
The data (such as an inertia link of mechanical control motion, a delay link of probe triggering movement and the like) are configured as initial parameters, coordinate values are extracted from the initialization matrix in a segmented mode by combining an initial axial scanning path, the coordinate values according with the intelligent algorithm rule are analyzed and filtered by the intelligent algorithm module, calculation iteration is carried out on the coordinate values, and intelligent path planning is output under a safety mechanism during actual execution.
Through the steps, the scanning path planning matrix finally output by the AI intelligent algorithm is shown as follows:
Figure BDA0003683979720000121
so that the corresponding bed plate position Z at the corresponding ith sampling point is controlled by the control device in the SPECT-CT equipment i Adjusting the position of the probe to Y i The motion of the probe is closest to the human body, the problem that a fat patient is possibly squeezed by equipment when the SPECT-CT equipment is used for whole body scanning is solved, and the axial scanning path planning of the probe of the SPECT-CT equipment is optimized.
The technical scheme of the application is described in detail in the above with reference to the accompanying drawings, and the application provides a SPECT-CT human body contour intelligent fitting axial scanning path planning method, which comprises the following steps: step 1, performing initial contour tracking on a patient by using a pre-scanning mode in SPECT-CT equipment to obtain an initialization matrix representing the position of a probe and the position of a bed plate; step 2, calculating the thickness of the human body and the deceleration distance of the probe according to the position data of the first probe and the position data of the second probe at adjacent sampling moments in the initial contour tracking process, and generating a corresponding original data matrix based on the thickness of the human body, the deceleration distance of the probe and the bed entering position at each sampling moment; and 3, performing optimized calculation on the corresponding human body thickness and the probe deceleration distance in the original data matrix according to the distance mean value of the probe deceleration distance, determining the optimal human body thickness and the optimal position of the probe in an iterative mode, updating the initialization matrix according to the calculated optimal position of the probe, and generating a scanning path planning matrix. Through the technical scheme in this application, solved the size partially fat patient and probably extruded problem by equipment when carrying out whole body scanning, optimized the axial scanning route planning of equipment probe.
The steps in the present application may be sequentially adjusted, combined, and subtracted according to actual requirements.
The units in the device can be merged, divided and deleted according to actual requirements.
Although the present application has been disclosed in detail with reference to the accompanying drawings, it is to be understood that such description is merely illustrative and not restrictive of the application of the present application. The scope of the present application is defined by the appended claims and may include various modifications, adaptations, and equivalents of the invention without departing from the scope and spirit of the application.

Claims (9)

  1. An axial scan path planning method for intelligent fitting of a SPECT-CT human body contour, which is characterized by comprising the following steps:
    step 1, performing initial contour tracking on a patient by using SPECT-CT equipment to obtain an initialization matrix representing the position of a probe and the position of a bed plate;
    step 2, calculating the thickness of a human body and the deceleration distance of the probe according to the position data of the first probe and the position data of the second probe at adjacent sampling moments in the initial contour tracking process, and generating a corresponding initial data matrix based on the thickness of the human body, the deceleration distance of the probe and the bed entering position at each sampling moment;
    and 3, performing optimized calculation on the corresponding human body thickness and the probe deceleration distance in the original data matrix according to the distance average value of the probe deceleration distance, determining the optimal human body thickness and the optimal position of the probe in an iterative mode, updating the initialization matrix according to the calculated optimal position of the probe, and generating a scanning path planning matrix.
  2. 2. The SPECT-CT intelligent human body contour fitting axial scan path planning method of claim 1, wherein in the step 2, the human body thickness H is calculated i And probe deceleration distance DeltaY i The corresponding calculation formula is:
    ΔY i ＝Y j -Y i
    H i ＝Y j -T
    in the formula,. DELTA.Y i The probe deceleration distance corresponding to the last sampling time is set as i equal to 1,2, …, N, Y j Is the second probe position data, Y, corresponding to the current sampling time when the probe is stopped i First probe position data, H, at the time of triggering of the probe light curtain corresponding to the previous sampling moment i The height data of the examining table is T.
  3. 3. The SPECT-CT human contour intelligent fitted axial scan path planning method of claim 2, wherein two adjacent sampling instants are separated by 10 ms.
  4. 4. The SPECT-CT intelligently fitted axial scan path planning method of claim 2 or 3 in which the raw data matrix is:
    Figure FDA0003683979710000021
    in the formula, H i Is the thickness of the human body corresponding to the last sampling time i, delta Y i For the probe deceleration distance, Z, corresponding to the last sampling instant i i Is the position of the bed plate corresponding to the last sampling moment i.
  5. 5. The SPECT-CT human body contour intelligent-fitting axial scan path planning method of claim 1, wherein in the step 3, the corresponding human body thickness H in the raw data matrix is subjected to distance mean of the probe deceleration distance i And probe deceleration distance DeltaY i Performing optimization calculation, specifically including:
    301, selecting any probe deceleration distance delta Y from the original data matrix i Presetting a number of adjacent values, and calculating the distance mean value, wherein the corresponding calculation formula is as follows:
    Figure FDA0003683979710000022
    in the formula,. DELTA.Y i m For the i-th probe deceleration distance DeltaY i The adjacent mth value;
    step 302, according to the distance mean value, the human body thickness H i And said probe deceleration distance DeltaY i And performing optimization calculation.
  6. 6. The SPECT-CT human body contour intelligent fitting axial scan path planning method of claim 5, wherein the step 302 is to measure the human body thickness H according to the distance mean i And said probe deceleration distance DeltaY i Carrying out optimization calculation, wherein the corresponding calculation formula is as follows:
    ΔY i ′＝ΔY i -ΔY i "
    H′ i ＝Y i +ΔY i ′-T
    in the formula,. DELTA.Y i 'optimized ith probe deceleration distance, H' i For optimized body thickness, Δ Y i For the i-th probe deceleration distance, Δ Y i "is the distance mean value corresponding to the deceleration distance of the ith probe, Y i The first probe position data when the probe light curtain is triggered is shown, and T is the height data of the examination bed.
  7. 7. The SPECT-CT human body contour intelligent-fitting axial scan path planning method of claim 5 or 6, wherein an optimal human body thickness H is determined i "sum Probe optimum position Y j ", specifically includes:
    311, the optimized probe deceleration distance Δ Y i ', human thickness H' i Inputting the initial value into a linear regression equation to calculate the deceleration distance of the optimizing probe and the thickness of the optimized human body;
    step 312, respectively calculating the deceleration distance of the optimizing probe, the distance difference and the thickness difference between the thickness of the optimized human body and the corresponding initial values, and respectively calculating the distance difference, the thickness difference, the distance ratio and the thickness ratio of the current deceleration distance of the optimizing probe and the thickness of the optimized human body;
    313, judging whether the distance ratio and the thickness ratio are both smaller than the error threshold, if so, recording the deceleration distance and the optimized human body thickness of the current optimizing probe as the optimal human body thickness H respectively i ", optimum position of probe Y j Otherwise, inputting the deceleration distance of the current optimizing probe and the optimized human body thickness into the linear regression equation again in an iterative mode, and calculating the deceleration distance of the optimizing probe and the optimized human body thickness of the next iteration;
    and step 314, respectively calculating the deceleration distance of the optimizing probe and the thickness of the optimizing human body in the next iteration, and the distance difference and the thickness difference between the deceleration distance of the optimizing probe and the thickness of the optimizing human body calculated in the previous iteration, and executing the step 312.
  8. 8. The SPECT-CT human contour intelligent-fitting axial scan path planning method of claim 7, wherein the error threshold value is 0.001.
  9. 9. The SPECT-CT intelligently fitted axial scan path planning method of claim 1 in which the scan path planning matrix is:
    Figure FDA0003683979710000031
    in the formula, Z i The position of the bed plate corresponding to the ith sampling position, Y i "is the optimal position of the probe corresponding to the ith sampling position.
CN202210645637.0A 2022-06-08 2022-06-08 Axial scanning path planning method for intelligent fitting of SPECT-CT (single photon emission computed tomography-computed tomography) human body contour Pending CN114897879A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115631232A (en) * 2022-11-02 2023-01-20 佛山读图科技有限公司 Method for determining radial position of double-probe detector
CN116269455A (en) * 2023-03-20 2023-06-23 瑞石心禾(河北)医疗科技有限公司 Detection method and system for automatically acquiring human body contour in SPECT (single photon emission computed tomography)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115631232A (en) * 2022-11-02 2023-01-20 佛山读图科技有限公司 Method for determining radial position of double-probe detector
CN116269455A (en) * 2023-03-20 2023-06-23 瑞石心禾(河北)医疗科技有限公司 Detection method and system for automatically acquiring human body contour in SPECT (single photon emission computed tomography)
CN116269455B (en) * 2023-03-20 2023-12-12 瑞石心禾(河北)医疗科技有限公司 Detection method and system for automatically acquiring human body contour in SPECT (single photon emission computed tomography)

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