CN109186508B - Median filtering method for thickness measurement - Google Patents
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Abstract
The invention belongs to the technical field of thickness measurement, and discloses a median filtering method for thickness measurement, which comprises the following steps of S1: firstly, carrying out N times of pre-measurement on the surface of a measured object through a distance measuring device to obtain N measured values si; step S2: creating a first-in first-out queue with the capacity of n to store the measured values, and when the number of the measured values in the queue reaches n, discarding the measured value which enters the queue at the earliest time by the queue and putting a new measured value into the queue; step S3: acquiring a median a in a queue in a rapid median filtering mode; step S4: and (3) pre-measuring the background distance b in the use of the distance measuring device, wherein the thickness value L of the measured object is b-a. The invention can well avoid the measurement error which happens occasionally, and the selected median value can be used as an accurate measurement value to calculate the thickness of the measured object so as to send out the proper voltage kvp of the working tube.
Description
Technical Field
The invention belongs to the technical field of thickness measurement, particularly relates to the field of thickness measurement median filtering, and particularly relates to a thickness measurement median filtering method.
Background
X-ray is a type of radiation, commonly referred to as X-ray, which is an energetic electromagnetic wave or radiation. When electrons moving at high speed collide with any form of substance, X-rays may occur. X-rays are transparent and have different penetration abilities to substances with different densities. Medical X-rays are used to project images of the anatomy to aid diagnosis; or irradiating the lesion for treatment. The requirement for accurately acquiring the X-ray radiation quality required by a patient to be shot has been long, the X-ray radiation quality is mainly reflected in an X-ray bulb tube, the working tube voltage kvp of an X-ray source and the working current product mA & s, the X-ray tube determines the energy level of X-rays emitted by the X-ray bulb tube, and higher tube voltage corresponds to higher X-ray energy level and stronger X-ray penetrating power; the latter is the product of current and time, which jointly determines the amount of X-rays emitted, higher current, longer time and more corresponding amount of rays, wherein the working tube voltage kvp of the X-ray source determines the X-ray penetration, and the overhigh working tube voltage kvp can generate higher energy level and more amount of rays, which can naturally cause more damage to the patient; and too low working tube voltage kvp will produce lower energy level and less radiation dose, and no clear and accurate image can be produced. Meanwhile, because the body surface of the radiation area of the patient is not a plane and has certain height fluctuation, namely the thickness of each part is different, if the same working tube voltage kvp is adopted, a part of image is unclear, and a part of body part possibly suffers from overlarge ray damage, so that the size of the working tube voltage kvp can be adjusted in real time according to the change of the body thickness, and the problem to be solved in the existing X-ray imaging technology is solved.
At present, no system similar to thickness measurement exists in the existing X-ray imaging equipment, and the working tube voltage kvp is adjusted according to the measured thickness, so as to solve the problems, the thickness measurement technology and accuracy of a body part are key, when the thickness is measured, if the thickness is measured only once, the working tube voltage kvp is possibly caused by the measurement error of the equipment to be seriously inconsistent with the working tube voltage kvp corresponding to the real thickness, great damage is caused to a human body or imaging is not clear, so that multiple times of measurement are required, and the median value of multiple times of measurement data is taken, so that a reliable thickness measurement value is obtained; meanwhile, in the existing median processing method, if the measured data is more, the processing time corresponding to the algorithm is also increased, so that the processing result cannot keep up with the updating frequency of the X-ray emitted by the equipment, or the updating frequency of the X-ray emitted is reduced, and the working efficiency of the equipment is further reduced.
Disclosure of Invention
The invention provides a median filtering method for thickness measurement, which is mainly used for measuring the thicknesses of different body parts of a patient in an X-ray imaging technology and is used for solving the technical problems that in the prior art, when the thickness is measured, the working tube voltage kvp is seriously inconsistent with the working tube voltage kvp corresponding to the real thickness due to the measurement error of equipment, and the human body is greatly damaged or the imaging is very unclear; meanwhile, the method can also solve the problem that the processing time corresponding to the median processing method of the existing thickness measuring equipment is increased, so that the processing result cannot keep pace with the updating frequency of the X-ray emitted by the equipment, or the updating frequency of the X-ray emitted is reduced, and the working efficiency of the equipment is further reduced.
The technical scheme adopted by the invention is as follows:
a median filtering method for thickness measurement, in order to solve the problem that in the prior art, when measuring the thickness, the voltage kvp of a working tube is seriously inconsistent with the voltage kvp of the working tube corresponding to the real thickness due to the measurement error of equipment, which causes great damage to the human body or makes the imaging very unclear, comprises the following steps,
step S1: firstly, carrying out N times of pre-measurement on the surface of a measured object through a distance measuring device to obtain N measured values si, wherein si represents the distance from the distance measuring device to the surface of the measured object, i represents a measurement serial number, and the value range is i-1, 2, … and N;
step S2: creating a first-in first-out queue with the capacity of n to store measured values, when the number of the measured values in the queue reaches n, discarding the measured value which enters the queue at the earliest time by the queue, and putting a new measured value into the queue, namely discarding the old measured value and adding the new measured value, so that the latest n measured values are stored in the queue;
step S3: obtaining a median a in the queue in a rapid median filtering mode, wherein the median a is an accurate value of the N pre-measured values;
step S4: and (3) pre-measuring the background distance b in the use of the distance measuring device, wherein the thickness value L of the measured object is b-a.
Measuring a part for multiple times, selecting a median value from a plurality of measured values, so that occasional measurement errors can be well avoided, calculating the thickness of the measured object by using the selected median value as an accurate measured value, and sending out a proper working tube voltage kvp, for example, a distance measuring device measures one point on the surface of the measured object for 5 times, wherein the results of the 5 times of measurement are 27, 28, 29 and 30 in sequence, the capacity of a created queue is 3, the first two data are discarded according to a first-in first-out principle, the three measured values of 29, 29 and 30 in the queue are left, then filtering the median value to obtain a median value a which is 29, and then obtaining the thickness of the measured object through a pre-measured background distance; of course, in normal measurement, the measured data is much more than 5 times, generally 20-50 times, and the queue capacity is much more than 3, generally several tens to several hundreds of times.
Further, in order to solve the technical problem that the processing time corresponding to the median processing method of the existing thickness measuring device is also increased, which causes the processing result to not keep pace with the updating frequency of the X-ray emitted by the device, or the updating frequency of the X-ray emitted is reduced, which further causes the reduction of the working efficiency of the device, in step S3, the sorting step of the fast median filtering algorithm specifically includes,
step S301: presetting the value range [ M, M ] of the pre-measured value]Creating an array A with the capacity of M-M +1, initializing all elements to 0, and when a new measurement value MkAdd Am to queuekIncrease by 1 when an old measurement mjIs discarded, Am is discardedjDecrease by 1; the array A records the occurrence times of various measured values from M to M;
step S302: for this array, the local sums are accumulated from front to back simultaneously
If it isi-1< n/2, andiif n/2, the measured value i + m-1 is the median value.
By means of rapid median filtering, the time of algorithm operation can be greatly shortened, particularly when a large amount of data is processed, the median can be rapidly obtained, and the working efficiency is improved; it is assumed that there are five measured values 27, 28, 29, 30, i.e. n is 5, and the value of the array a is in the range of [25, 30 ]]Then, after inputting five measurements, the array A becomes [0, 0, 1, 1, 2, 1]It is found that when i is 3,i-1＜n/2，i> n/2, thereby giving a median value of 29. Typically, when making measurements of a body part of a patient, the value of the array A is typically in the range of [20, 80 ]]During measurement, the measured values are integers in centimeter units, so that 61 value-taking points exist in a value-taking range, during measurement, the number of measurement times of one measurement period may be hundreds, if a traditional median filtering method is adopted, continuous sequencing and operation are required, and the capacity of an array is hundreds, so that the time consumption of the algorithm is long, and after the rapid median filtering is adopted, the capacity of the array is 61 unchanged, and Am in the array is changedjThe fast median filtering provides a way of temporal complexity O (1),the arithmetic operation time is greatly reduced, and the working efficiency is greatly improved.
Furthermore, in order to further improve the processing efficiency of the algorithm, the rapid sequencing algorithm continuously adjusts and reduces the value range [ M, M ] according to the new and old measured values, and the step of reducing the value range comprises,
step S3011: when a new measured value mkWhen joining the queue, m is compared simultaneouslykAnd the size of M, if M > MkIf M is greater than M, the value range [ M, M ] will be obtained]Is transformed into [ m ]k，M]When the capacity of the array A becomes M-Mk+ 1; when another new measurement value m is takenpWhen joining the queue, m is compared simultaneouslypAnd mkIf m is large or smallk＞mpIf m is greater than m, the value range [ m ] will be obtainedk，M]Is transformed into [ m ]p，mk]When the capacity of the array A becomes mk-mp+ 1; if M > Mp＞mkThen the value range [ m ] will be takenk，M]Is transformed into [ m ]k，mp]When the capacity of the array A becomes mp-mk+1；
Step S3012: when there is a new measured value mnWhen joining the queue, repeat step S3011 compare mnAnd mpOr mkThe capacity range and the capacity size of the array are determined again.
For example, when measuring, assume the value range of the array A as [20, 80 ]]However, for some locations, the thickness range may be determined to be changed to 50-60, and a large number of Am's of 0's will be present in array AkTherefore, the operation time of the processor is wasted, and if the range can be rapidly reduced to the actual measurement range, the processor saves much time when performing the median filtering; therefore, the step of narrowing the value range is realized by assuming that the value range of the original array A is [20, 80 ]]When a new measurement m1 is added to the queue, m1 is 50, then m1 is greater than 20, and thus the value range of the array a becomes [50, 80%](ii) a When a new measurement value m2 is added into the queue, assuming that m2 is 60 and m2 is 50-80, the value range of the array A is changed to [50, 60%](ii) a Assuming that m2 is 40 and m2 is less than 50, the value range of the array A becomes [40, 50%](ii) a When a new one is addedAfter measuring m3, assuming that m3 is 70 and m3 is greater than 50, the value range of the array a becomes [40, 70%](ii) a Therefore, the value range of the array A is continuously adjusted until the value range is accurate to the minimum range, and the median filtering speed in the range is greatly reduced.
Further, M and M are integer values, and the new measurement value MkTo take a value range of [ M, M]Is an integer value of (1).
Further, the measured object is placed on the flat plate during measurement, and the background distance b represents the vertical distance between the ranging transmitting head of the ranging device and the flat plate.
Furthermore, when the distance measuring device carries out the pre-measurement on the surface of the measured object, the same point on the surface of the measured object is subjected to the pre-measurement for N times, and a measurement median value is obtained; and moving the distance measuring device to another point to perform N times of pre-measurement and obtain a corresponding measurement median value.
Further, the distance measuring device may be any one of a visible light distance measuring device, a near visible light distance measuring device, and a sonar distance measuring device.
The invention has the beneficial effects that:
(1) the invention can well avoid occasional measurement errors by measuring a part for many times and selecting a median value from a plurality of measurement values, the selected median value can be used as an accurate measurement value to calculate the thickness of a measured object to send out proper working tube voltage kvp, and the condition that the imaging is not clear due to great damage to a human body caused by overhigh radiation or due to overlow radiation quality is avoided.
(2) The rapid median filtering method of the invention provides a mode with time complexity of O (1), and particularly when a large amount of data is processed, the median can be rapidly obtained, so that the arithmetic operation time is greatly reduced, and the working efficiency is greatly improved.
(3) The median filtering method can continuously adjust the value range of the array A until the value range is accurate to the minimum range, and the range is quickly reduced to the actual measurement range, so that the median filtering speed in the range can be greatly reduced, and much time can be saved when a processor performs median filtering.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a flow chart of the ordering steps of the fast median filtering algorithm of the present invention;
FIG. 3 is a flow chart of steps for narrowing the filter span according to the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments.
Example 1:
as shown in fig. 1, a method of median filtering for thickness measurements includes the steps of,
step S1: firstly, carrying out N times of pre-measurement on the surface of a measured object through a distance measuring device to obtain N measured values si, wherein si represents the distance from the distance measuring device to the surface of the measured object, i represents a measurement serial number, and the value range is i-1, 2, … and N;
step S2: creating a first-in first-out queue with the capacity of n to store measured values, when the number of the measured values in the queue reaches n, discarding the measured value which enters the queue at the earliest time by the queue, and putting a new measured value into the queue, namely discarding the old measured value and adding the new measured value, so that the latest n measured values are stored in the queue;
step S3: obtaining a median a in the queue in a rapid median filtering mode, wherein the median a is an accurate value of the N pre-measured values;
step S4: and (3) pre-measuring the background distance b in the use of the distance measuring device, wherein the thickness value L of the measured object is b-a.
Measuring a part for multiple times, selecting a median value from a plurality of measured values, so that occasional measurement errors can be well avoided, calculating the thickness of the measured object by using the selected median value as an accurate measured value, and sending out a proper working tube voltage kvp, for example, a distance measuring device measures one point on the surface of the measured object for 5 times, wherein the results of the 5 times of measurement are 27, 28, 29 and 30 in sequence, the capacity of a created queue is 3, the first two data are discarded according to a first-in first-out principle, the three measured values of 29, 29 and 30 in the queue are left, then filtering the median value to obtain a median value a which is 29, and then obtaining the thickness of the measured object through a pre-measured background distance; of course, in normal measurement, the measured data is much more than 5 times, generally 20-50 times, and the queue capacity is much more than 3, generally several tens to several hundreds of times.
Example 2:
as shown in fig. 2, on the basis of the above embodiment, as a further preferable solution, in step S3, the sorting step of the fast median filtering algorithm specifically includes,
step S301: presetting the value range [ M, M ] of the pre-measured value]Creating an array A with the capacity of M-M +1, initializing all elements to 0, and when a new measurement value MkAdd Am to queuekIncrease by 1 when an old measurement mjIs discarded, Am is discardedjDecrease by 1; the array A records the occurrence times of various measured values from M to M;
step S302: for this array, the local sums are accumulated from front to back simultaneously
If it isi-1< n/2, andiif n/2, the measured value i + m-1 is the median value.
By means of rapid median filtering, the time of algorithm operation can be greatly shortened, particularly when a large amount of data is processed, the median can be rapidly obtained, and the working efficiency is improved; it is assumed that there are five measured values 27, 28, 29, 30, i.e. n is 5, and the value of the array a is in the range of [25, 30 ]]Then, after inputting five measurements, the array A becomes [0, 0, 1, 1, 2, 1]It is found that when i is 3,i-1＜n/2，i> n/2, thereby giving a median value of 29. Typically, when making measurements of a body part of a patient, the value of the array A is typically in the range of [20, 80 ]]In the measurement, the measured values are integers in centimeters, so that there are 61 value taking points in the value range, and in the measurement, the number of measurement times in one measurement period may be hundreds, if according to the transmissionThe traditional median filtering method needs to carry out continuous sequencing and operation, and the capacity of the array is hundreds, so that the time consumption of the algorithm is long, after the rapid median filtering method is adopted, the capacity of the array is unchanged by 61, and Am in the array is changedjThe rapid median filtering provides a mode with time complexity of O (1), so that the arithmetic operation time is greatly reduced, and the working efficiency is greatly improved.
Example 3:
as shown in fig. 3, on the basis of the above embodiment, as a further preferred scheme, in order to further improve the processing efficiency of the algorithm, the fast sorting algorithm continuously adjusts and reduces the value range [ M, M ] according to the new and old measured values, and the step of reducing the value range includes,
step S3011: when a new measured value mkWhen joining the queue, m is compared simultaneouslykAnd the size of M, if M > MkIf M is greater than M, the value range [ M, M ] will be obtained]Is transformed into [ m ]k，M]When the capacity of the array A becomes M-Mk+ 1; when another new measurement value m is takenpWhen joining the queue, m is compared simultaneouslypAnd mkIf m is large or smallk＞mpIf m is greater than m, the value range [ m ] will be obtainedk，M]Is transformed into [ m ]p，mk]When the capacity of the array A becomes mk-mp+ 1; if M > Mp＞mkThen the value range [ m ] will be takenk，M]Is transformed into [ m ]k，mp]When the capacity of the array A becomes mp-mk+1；
Step S3012: when there is a new measured value mnWhen joining the queue, repeat step S3011 compare mnAnd mpOr mkThe capacity range and the capacity size of the array are determined again.
For example, when measuring, assume the value range of the array A as [20, 80 ]]However, for some locations, the thickness range may be determined to be changed to 50-60, and a large number of Am's of 0's will be present in array AkThus, the processor's computation time is wasted, and if the range can be quickly narrowed to the actual measurement range, the processor performs an on-going filteringWhen waves are generated, much time can be saved; therefore, the step of narrowing the value range is realized by assuming that the value range of the original array A is [20, 80 ]]When a new measurement m1 is added to the queue, m1 is 50, then m1 is greater than 20, and thus the value range of the array a becomes [50, 80%](ii) a When a new measurement value m2 is added into the queue, assuming that m2 is 60 and m2 is 50-80, the value range of the array A is changed to [50, 60%](ii) a Assuming that m2 is 40 and m2 is less than 50, the value range of the array A becomes [40, 50%](ii) a When a new measurement m3 is added, assuming that m3 is 70 and m3 is greater than 50, the value range of the array A becomes [40, 70%](ii) a Therefore, the value range of the array A is continuously adjusted until the value range is accurate to the minimum range, and the median filtering speed in the range is greatly reduced.
The fast median filtering can be realized by a programming program in a processor, and the following is an example of programming codes of the fast median filtering:
example 4:
on the basis of the above embodiment, as a further preferable scheme, M and M are integer values, and the new measured value MkTo take a value range of [ M, M]The integer value of (1); the measured object is placed on the flat plate during measurement, and the background distance b represents the vertical distance between a ranging transmitting head of the ranging device and the flat plate; when the distance measuring device carries out pre-measurement on the surface of a measured object, carrying out pre-measurement on the same point on the surface of the measured object for N times, and obtaining a measurement median; moving the ranging device to another pointPerforming N times of prediction measurement and obtaining a corresponding measurement median; the distance measuring device is any one of a visible light distance measuring device, a near visible light distance measuring device and a sonar distance measuring device.
The invention is not limited to the above alternative embodiments, and any other various forms of products can be obtained by anyone in the light of the present invention, but any changes in shape or structure thereof, which fall within the scope of the present invention as defined in the claims, fall within the scope of the present invention.
Claims (5)
1. A method of median filtering thickness measurements, characterized by: comprises the following steps of (a) carrying out,
step S1: firstly, carrying out N times of pre-measurement on the surface of a measured object through a distance measuring device to obtain N measured values si, wherein si represents the distance from the distance measuring device to the surface of the measured object, i represents a measurement serial number, and the value range is i-1, 2, … and N;
step S2: creating a first-in first-out queue with the capacity of n to store measured values, when the number of the measured values in the queue reaches n, discarding the measured value which enters the queue at the earliest time by the queue, and putting a new measured value into the queue, namely discarding the old measured value and adding the new measured value, so that the latest n measured values are stored in the queue;
step S3: obtaining a median a in the queue in a rapid median filtering mode, wherein the median a is an accurate value of the N pre-measured values;
the sorting step of the fast median filtering algorithm specifically comprises,
step S301: presetting the value range [ M, M ] of the pre-measured value]Creating an array A with the capacity of M-M +1, initializing all elements to 0, and when a new measurement value MkAdd Am to queuekIncrease by 1 when an old measurement mjIs discarded, Am is discardedjDecrease by 1; the array A records the occurrence times of various measured values from M to M;
step S302: for this array, the local sums are accumulated from front to back simultaneously
If it isi-1< n/2, andiif the measured value is more than n/2, the measured value i + m-1 is the median value;
wherein, the rapid median filtering algorithm continuously adjusts and reduces the value range [ M, M ] according to the new and old measured values, the step of reducing the value range comprises,
step S3011: when a new measured value mkWhen joining the queue, m is compared simultaneouslykAnd the size of M, if M > MkIf M is greater than M, the value range [ M, M ] will be obtained]Is transformed into [ m ]k，M]When the capacity of the array A becomes M-Mk+ 1; when another new measurement value m is takenpWhen joining the queue, m is compared simultaneouslypAnd mkIf m is large or smallk＞mpIf m is greater than m, the value range [ m ] will be obtainedk，M]Is transformed into [ m ]p，M]When the capacity of the array A becomes M-Mp+ 1; if M > Mp＞mkThen the value range [ m ] will be takenk，M]Is transformed into [ m ]k，mp]When the capacity of the array A becomes mp-mk+1；
Step S3012: when there is a new measured value mnWhen joining the queue, repeat step S3011 compare mnAnd mpOr mkRe-determining the capacity range and the capacity size of the array;
step S4: and (3) pre-measuring the background distance b in the use of the distance measuring device, wherein the thickness value L of the measured object is b-a.
2. The method of claim 1, wherein the median filtering is performed on the thickness measurement: m and M are integer values, and the new measured value MkTo take a value range of [ M, M]Is an integer value of (1).
3. A method of median filtering of thickness measurements according to any of claims 1-2, characterized by: the measured object is placed on the flat plate during measurement, and the background distance b represents the vertical distance between the ranging transmitting head of the ranging device and the flat plate.
4. A method of median filtering of thickness measurements according to any of claims 1-2, characterized by: when the distance measuring device carries out pre-measurement on the surface of a measured object, firstly carrying out N times of pre-measurement on the same point on the surface of the measured object, and obtaining a measurement median; and moving the distance measuring device to another point to perform N times of pre-measurement and obtain a corresponding measurement median value.
5. The method of claim 4, wherein the median filtering is performed by: the distance measuring device adopts any one of a visible light distance measuring device, a near visible light distance measuring device or a sonar distance measuring device.
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