CN116797494B - Obstetrical surgery monitoring method, system and related equipment based on image processing - Google Patents
Obstetrical surgery monitoring method, system and related equipment based on image processing Download PDFInfo
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- 230000002787 reinforcement Effects 0.000 claims abstract description 27
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- 235000013372 meat Nutrition 0.000 claims description 64
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Abstract
The application provides an obstetrical operation monitoring method, system and related equipment based on image processing, which are characterized in that an obstetrical operation image is subjected to brightness division and reinforcement treatment, so that an obstetrical operation brightness reinforcement image is determined, an obstetrical operation brightness reinforcement image is subjected to operation knife characteristic conversion, an obstetrical operation knife image characteristic matrix is obtained, an obstetrical operation knife image characteristic deviation coefficient of the obstetrical operation knife image characteristic matrix is determined, so that an obstetrical operation knife image characteristic deviation matrix is determined, an obstetrical operation knife characteristic reinforcement image is determined, an obstetrical operation knife meat-in value and an obstetrical operation knife inclination angle are determined according to the obstetrical operation knife characteristic reinforcement image, an obstetrical operation knife meat-in dangerous value is calculated according to the obstetrical operation knife meat-in dangerous value and the obstetrical operation knife meat-in dangerous threshold interval, and obstetrical operation monitoring is performed on the obstetrical operation according to the obstetrical operation knife meat-in dangerous value and the predetermined obstetrical operation knife meat-in dangerous threshold interval, so that the accuracy of obstetrical operation monitoring can be improved.
Description
Technical Field
The application relates to the technical field of image processing, in particular to an obstetrical operation monitoring method, system and related equipment based on image processing.
Background
Image processing is a process of analyzing, enhancing, reconstructing and the like an image by using a computer and digital technology, and covers digital processing and improvement of static or dynamic images to extract useful information from the images or change characteristics of the images, and can be applied to multiple fields of computer vision, medical imaging, remote sensing, image sensors and the like.
Obstetric monitoring based on image processing is a method for assisting in monitoring and assessing conditions during obstetric surgery using computer vision and image processing techniques, which aims to provide real-time, non-invasive monitoring of the surgical procedure, and as the number of newborns increases, obstetricians may feel tired of the doctor if working for a long time, and may not be able to make accurate judgment during the surgical procedure due to personal negligence, so that the obstetric surgery needs to be monitored, and the prior art directly uses the original video of the monitoring to monitor and analyze the surgery, which reduces the accuracy of the obstetric surgery monitoring.
Disclosure of Invention
Accordingly, there is a need for an image processing-based obstetrical operation monitoring method, system and related device for improving accuracy of obstetrical operation monitoring.
In order to solve the technical problems, the application adopts the following technical scheme:
in a first aspect, the present application provides a method of obstetrical surgical monitoring based on image processing, comprising the steps of:
acquiring obstetrical operation monitoring video, and performing frame extraction on the obstetrical operation monitoring video to obtain an obstetrical operation image;
performing brightness division on the obstetrical operation image to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image, performing reinforcement treatment on the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image to obtain a first brightness reinforcement set of the obstetrical operation image and a second brightness reinforcement set of the obstetrical operation image, and determining an obstetrical operation brightness reinforcement image according to the first brightness reinforcement set of the obstetrical operation image and the second brightness reinforcement set of the obstetrical operation image;
performing scalpel image feature matrix conversion on the obstetrical operation brightness enhancement image to obtain an obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset coefficient of the obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset matrix according to the obstetrical scalpel image feature matrix and the obstetrical scalpel image feature offset coefficient, and further determining an obstetrical scalpel feature enhancement image;
Determining the meat feeding value of the obstetrical scalpel and the inclination angle of the obstetrical scalpel according to the characteristic intensified image of the obstetrical scalpel, and calculating to obtain the meat feeding dangerous value of the obstetrical scalpel according to the meat feeding value of the obstetrical scalpel and the inclination angle of the obstetrical scalpel;
and monitoring the obstetrical operation according to the obstetrical scalpel meat-in dangerous value and a preset obstetrical scalpel meat-in dangerous threshold interval.
In some embodiments, the intensity dividing of the obstetrical surgical image specifically includes:
acquiring brightness values corresponding to all pixel points in the obstetrical operation image;
determining a brightness set dividing interval according to brightness values corresponding to all the pixel points;
and dividing all pixel points in the obstetrical operation image according to the brightness set dividing interval to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image.
In some embodiments, determining the luminance set partition interval specifically includes:
determining an upper boundary value of the brightness set dividing interval;
determining a lower boundary value of the brightness set dividing interval;
and determining a brightness set dividing interval according to the interval upper boundary value and the interval lower boundary value.
In some embodiments, the enhancing the first intensity set of obstetrical surgical images and the second intensity set of obstetrical surgical images specifically comprises:
Determining a first intensity enhancement factor from the first intensity set of obstetrical images;
determining a second intensity enhancement factor from the second intensity set of obstetrical images;
determining a first intensity enhancement set of the obstetrical surgical image from the first intensity enhancement coefficient and the first intensity set of the obstetrical surgical image;
and determining a second brightness enhancement set of the obstetrical operation image according to the second brightness enhancement coefficient and the second brightness set of the obstetrical operation image.
In some embodiments, the first luminance enhancement factor is determined using the steps of:
determining a first intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining the average value of the brightness values corresponding to all the pixel points in the first brightness set of the obstetrical operation image；
Determining a total number of all pixels in the first intensity set of the obstetrical image；
According to the first brightness concentration of the obstetrical operation imageLuminance value corresponding to each pixel>Mean value of brightness values corresponding to all pixels in the first brightness set of the obstetrical operation image +.>And the total number of all pixels in the first intensity set of the obstetrical image +.>Determining a first luminance enhancement factor, wherein the first luminance is strong The coefficient of chemistry is determined using the following formula:
wherein,representing a first luminance enhancement factor, ">Expressed as +.>An exponential function of the base +.>And representing the enhancement coefficient for constraining the brightness value of the first brightness set after enhancement.
In some embodiments, the second brightness enhancement factor is determined using the steps of:
determining the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image；
Determining a second intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining a total number of all pixels in the second intensity set of the obstetrical image；
According to the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation imageSecond intensity set of obstetrical image +.>Luminance value corresponding to each pixel>And the total number of all pixels in the second intensity set of the obstetrical image +.>Determining a second brightness enhancement factor, wherein the second brightness enhancement factor is determined using the formula:
wherein,representing a second luminance enhancement factor, ">As a common logarithm, a base 10 logarithm function is shown.
In some embodiments, monitoring obstetrical surgery specifically includes:
When the obstetrical scalpel meat entering dangerous value is lower than a preset obstetrical scalpel meat entering dangerous threshold value interval, normal operation information is sent out;
when the obstetrical scalpel meat entering dangerous value is in a preset obstetrical scalpel meat entering dangerous threshold value interval, early warning information is sent;
and when the obstetrical scalpel meat entering dangerous value exceeds a preset obstetrical scalpel meat entering dangerous threshold value interval, sending out alarm information.
In a second aspect, the present application provides an obstetric surgical monitoring system based on image processing, comprising:
the obstetrical operation image acquisition module is used for acquiring an obstetrical operation monitoring video, and extracting frames of the obstetrical operation monitoring video to obtain an obstetrical operation image;
the obstetrical operation brightness enhancement image determining module is used for determining an obstetrical operation image first brightness set and an obstetrical operation image second brightness set of the obstetrical operation image, carrying out enhancement processing on the obstetrical operation image first brightness set and the obstetrical operation image second brightness set to obtain an obstetrical operation image first brightness enhancement set and an obstetrical operation image second brightness enhancement set, and determining an obstetrical operation brightness enhancement image according to the obstetrical operation image first brightness enhancement set and the obstetrical operation image second brightness enhancement set;
The obstetrical scalpel characteristic strengthening image determining module is used for converting the obstetrical scalpel brightness strengthening image into an obstetrical scalpel image characteristic matrix, determining an obstetrical scalpel image characteristic deviation coefficient of the obstetrical scalpel image characteristic matrix, determining an obstetrical scalpel image characteristic deviation matrix according to the obstetrical scalpel image characteristic matrix and the obstetrical scalpel image characteristic deviation coefficient, and determining an obstetrical scalpel characteristic strengthening image according to the obstetrical scalpel image characteristic deviation matrix;
the obstetrical scalpel meat entering dangerous value determining module is used for determining an obstetrical scalpel meat entering value and an obstetrical scalpel inclination angle according to the obstetrical scalpel characteristic intensified image, and calculating the obstetrical scalpel meat entering dangerous value according to the obstetrical scalpel meat entering value and the obstetrical scalpel inclination angle;
and the obstetrical operation monitoring module is used for monitoring the obstetrical operation according to the obstetrical scalpel meat-in dangerous value and a preset obstetrical scalpel meat-in dangerous threshold interval.
In a third aspect, the present application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the obstetrical surgical monitoring method based on image processing as described in any of the preceding claims when the computer program is executed by the processor.
In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of the method for obstetrical operation monitoring based on image processing as described in any of the above.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
in the obstetric operation monitoring method, the system and the related equipment based on image processing, firstly, an obstetric operation monitoring video is acquired, frames of the obstetric operation monitoring video are extracted to obtain an obstetric operation image, brightness division is carried out on the obstetric operation image to obtain a first brightness set of the obstetric operation image and a second brightness set of the obstetric operation image, reinforcement processing is carried out on the first brightness set of the obstetric operation image and the second brightness set of the obstetric operation image to obtain a first brightness reinforcement set of the obstetric operation image and a second brightness reinforcement set of the obstetric operation image, the obstetric operation brightness reinforcement image is subjected to operation knife feature conversion according to the first brightness reinforcement set of the obstetric operation image and the second brightness reinforcement set of the obstetric operation image, a characteristic matrix of the obstetric operation knife image is obtained, characteristic offset coefficients of the obstetric operation knife image are determined, the characteristic offset matrix of the obstetric operation knife image is determined according to the characteristic matrix of the obstetric operation knife image and the obstetric operation knife image, further, the characteristic image of the obstetric operation knife is further determined, a value of the obstetric operation knife is obtained, the value is obtained by means of the step of entering a dangerous meat and the value is calculated according to the value, and the value is further calculated by entering the dangerous meat and the obstetric operation monitoring video and the obstetric operation monitoring value, finally, the obstetrical operation is monitored according to the meat entering dangerous value of the obstetrical operation knife, and compared with the prior art, the accuracy of the obstetrical operation monitoring is greatly improved.
Drawings
FIG. 1 is a flow chart of a method for obstetric monitoring based on image processing in some embodiments of the present application;
FIG. 2 is a block diagram of an obstetric surgical monitoring system based on image processing in some embodiments of the present application;
fig. 3 is an internal block diagram of a computer device in some embodiments of the application.
Detailed Description
The core of the application is that an obstetrical operation monitoring video is acquired, the obstetrical operation monitoring video is subjected to frame extraction to obtain an obstetrical operation image, the obstetrical operation image is subjected to brightness division to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image, the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image are subjected to strengthening treatment to obtain a first brightness strengthening set of the obstetrical operation image and a second brightness strengthening set of the obstetrical operation image, the obstetrical operation brightness strengthening image is determined according to the first brightness strengthening set of the obstetrical operation image and the second brightness strengthening set of the obstetrical operation image, the obstetrical operation brightness strengthening image is subjected to operation knife feature conversion to obtain an obstetrical operation knife image feature matrix, the obstetrical operation knife image feature offset coefficient of the obstetrical operation knife image feature matrix is determined, determining an obstetric scalpel image characteristic offset matrix according to the obstetric scalpel image characteristic matrix and the obstetric scalpel image characteristic offset coefficient, further determining an obstetric scalpel characteristic enhanced image, determining an obstetric scalpel meat-in value and an obstetric scalpel inclination angle according to the obstetric scalpel characteristic enhanced image, calculating an obstetric scalpel meat-in dangerous value according to the obstetric scalpel meat-in value and the obstetric scalpel inclination angle, monitoring the obstetric operation according to the obstetric scalpel meat-in dangerous value and a preset obstetric scalpel meat-in dangerous threshold interval, further enhancing the image of the scalpel in the video through an original video of the enhanced monitoring, further obtaining an obstetric scalpel meat-in dangerous value, finally monitoring the obstetric operation according to the obstetric scalpel meat-in dangerous value, comparing with the prior art, the monitoring accuracy of obstetrical operation is greatly improved.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. Referring to fig. 1, which is an exemplary flowchart of an image processing-based obstetric surgical monitoring method 100 according to some embodiments of the present application, the image processing-based obstetric surgical monitoring method 100 mainly includes the steps of:
in step 101, an obstetrical operation monitoring video is acquired, and frame extraction is performed on the obstetrical operation monitoring video to obtain an obstetrical operation image.
In particular, when the operation of the obstetrical operation monitoring is started, the obstetrical operation monitoring video is acquired in real time from the monitoring system, in some embodiments, the obstetrical operation monitoring video is extracted in frames, and the obtaining of the obstetrical operation image can be achieved by adopting the following steps:
acquiring an obstetrical operation monitoring video file;
initializing a frame counter;
decoding the obstetrical operation monitoring video frame by frame to obtain a decoded monitoring video image;
and performing Lab image conversion on the decoded monitoring video image to obtain an obstetrical operation image.
In specific implementation, the obstetrical operation monitoring video can be decoded frame by adopting a Python and OpenCV library in the prior art, the decoded video monitoring image is subjected to Lab image conversion, and the Lab image of the converted video monitoring image is used as an obstetrical operation image.
Examples of frame-by-frame decoding of the obstetrical surgery monitoring video by the Python and OpenCV libraries are as follows:
import cv2
import os
def extract_frames(video_path, output_folder):
create output folder if there is no #)
if not os.path.exists(output_folder):
os.makedirs(output_folder)
# open monitoring video file
video_capture = cv2.VideoCapture(video_path)
# initialization frame counter
frame_count = 0
while True:
Reading video frame by frame #
success, frame = video_capture.read()
if not success:
break
# generating frame File name
frame_filename=os.path.join(output_folder, f"frame_{frame_count:04d}.jpg")
# save frame image
cv2.imwrite(frame_filename, frame)
# update frame counter
frame_count += 1
Release resource #
video_capture.release()
# set video file path and output folder path
video_file = "path_to_your_video.mp4"
output_folder = "path_to_output_frames_folder"
# extraction frame image
extract_frames(video_file, output_folder)
It should be noted that, in the present application, the Lab image conversion may be performed on the decoded monitoring video image using the cv2. Cvttcolor () function of the OpenCV library in the prior art, and in other embodiments, other methods may be used for conversion, which is not limited herein specifically.
In step 102, the obstetrical operation image is subjected to brightness division to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image, the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image are subjected to strengthening treatment to obtain a first brightness strengthening set of the obstetrical operation image and a second brightness strengthening set of the obstetrical operation image, and the obstetrical operation brightness strengthening image is determined according to the first brightness strengthening set of the obstetrical operation image and the second brightness strengthening set of the obstetrical operation image.
It should be noted that, in the present application, the first brightness set of the obstetric image and the second brightness set of the obstetric image are both sets of pixel points in the obstetric image; all the obtained data are stored in the operation database, and can be directly extracted from the database when corresponding data are needed.
In some embodiments, the brightness division of the obstetrical surgical image may be achieved by:
acquiring brightness values corresponding to all pixel points in the obstetrical operation image;
determining a brightness set dividing interval according to brightness values corresponding to all the pixel points;
and dividing all pixel points in the obstetrical operation image according to the brightness set dividing interval to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image.
In specific implementation, brightness values corresponding to all pixel points in the obstetrical operation image are obtained from an operation database; determining a brightness set dividing interval according to brightness values corresponding to all the pixel points; dividing all pixels which are not in the brightness set dividing section and correspond to the brightness values in the obstetrical operation image into a first brightness set of the obstetrical operation image, and dividing all pixels which are not in the brightness set dividing section and correspond to the brightness values in the obstetrical operation image into a second brightness set of the obstetrical operation image.
In some embodiments, determining the brightness set dividing section according to the brightness values corresponding to all the pixel points may be implemented by the following steps:
determining an upper boundary value of the brightness set dividing interval;
determining a lower boundary value of the brightness set dividing interval;
and determining a brightness set dividing interval according to the interval upper boundary value and the interval lower boundary value.
In specific implementation, for example: the upper boundary value of the interval isThe lower boundary value of the interval is +.>The brightness set is divided into sections of。
In some embodiments, the interval upper boundary value and the interval lower boundary value may be determined using the following formulas:
wherein,representing the upper boundary value of the interval>Representing the lower boundary value of the interval>Representing the mean value of the brightness values corresponding to all the pixel points in the obstetrical operation image,/for>For boundary coefficients +.>Representing the total number of all pixels in the obstetrical image,/for>Representing +.f in the obstetric image>And brightness values corresponding to the pixel points.
It should be noted that, the boundary coefficients in the present application may be obtained through analysis of historical experimental data, and may be obtained by other methods in other embodiments, which are not limited herein.
In some embodiments, the enhancing the first intensity set of obstetrical surgical images and the second intensity set of obstetrical surgical images may be performed by:
Determining a first intensity enhancement factor from the first intensity set of obstetrical images;
determining a second intensity enhancement factor from the second intensity set of obstetrical images;
determining a first intensity enhancement set of the obstetrical surgical image from the first intensity enhancement coefficient and the first intensity set of the obstetrical surgical image;
and determining a second brightness enhancement set of the obstetrical operation image according to the second brightness enhancement coefficient and the second brightness set of the obstetrical operation image.
In some embodiments, determining the first intensity enhancement factor from the first intensity set of obstetrical surgical images may be accomplished by:
determining a first intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining the average value of the brightness values corresponding to all the pixel points in the first brightness set of the obstetrical operation image；
Determining a total number of all pixels in the first intensity set of the obstetrical image；
According to the first brightness concentration of the obstetrical operation imageLuminance value corresponding to each pixel>The place of saleThe mean value of the brightness values corresponding to all pixel points in the first brightness set of the obstetrical operation image +.>And the total number of all pixels in the first intensity set of the obstetrical image +. >Determining a first luminance enhancement coefficient, wherein the first luminance enhancement coefficient can be determined using the following formula:
wherein,representing a first luminance enhancement factor, ">Expressed as +.>An exponential function of the base +.>And representing the enhancement coefficient for constraining the brightness value of the first brightness set after enhancement.
In the specific implementation, the brightness values corresponding to all the pixel points in the first brightness set of the obstetrical operation image are obtained, corresponding operation is carried out on the brightness values according to the formula, the index function value after the operation is obtained, and the value of the index function is used as a first brightness enhancement coefficient.
It should be noted that, the strengthening coefficient in the application is adjusted according to experimental data, and the value is different under different application environments.
In some embodiments, determining a second intensity enhancement factor from the second set of intensity of the obstetrical surgical image may be accomplished by:
determining the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image；
Determining a second intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining a total number of all pixels in the second intensity set of the obstetrical image；
According to the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image Second intensity set of obstetrical image +.>Luminance value corresponding to each pixel>And the total number of all pixels in the second intensity set of the obstetrical image +.>Determining a second brightness enhancement factor, wherein the second brightness enhancement factor is determined using the following formula:
wherein,representing a second luminance enhancement factor, ">Is commonly used logarithm and representsA base 10 logarithmic function.
In the specific implementation, the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image are obtained, corresponding operation is carried out on the brightness values according to the formula, the logarithmic function value after operation is obtained, and the value of the logarithmic function is used as the second brightness enhancement coefficient.
In the present application, the logarithmic function of the second brightness enhancement factor is a negative number, so the formula is multiplied by negative one to make the value positive.
In some embodiments, determining the first intensity-enhanced set of obstetrical surgical images and determining the second intensity-enhanced set of obstetrical surgical images may be accomplished by:
traversing all brightness values in a first brightness set of the obstetrical surgery image and a second brightness set of the obstetrical surgery image;
strengthening the brightness values corresponding to all the pixel points in the first brightness set of the obstetrical operation image according to the first brightness strengthening coefficient to obtain a first brightness strengthening set of the obstetrical operation image;
And strengthening the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image according to the second brightness strengthening coefficient to obtain a second brightness strengthening set of the obstetrical operation image.
In specific implementation, acquiring all brightness values in a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image; multiplying all brightness values in the obstetrical operation image first brightness set by a first brightness enhancement coefficient to obtain brightness enhancement values corresponding to each brightness value in the obstetrical operation image first brightness set, and taking the enhanced obstetrical operation image first brightness set as an obstetrical operation image first brightness enhancement set; multiplying all brightness values in the obstetrical operation image second brightness set by the second brightness enhancement coefficient to obtain brightness enhancement values corresponding to each brightness value in the obstetrical operation image second brightness set, and taking the enhanced obstetrical operation image second brightness set as an obstetrical operation image second brightness enhancement set.
In some embodiments, the intensity values for all pixels in the first intensity set of the obstetrical image and the intensity values for all pixels in the second intensity set of the obstetrical image may be determined using the following formulas:
Wherein,representing the first intensity enhancement set of obstetrical surgical image +.>Brightness enhancement values corresponding to the individual pixel points,representing the second intensity enhancement set of obstetrical surgical image +.>Brightness enhancement value corresponding to each pixel, < >>Representing the first intensity concentration of obstetrical surgical image +.>Luminance value corresponding to each pixel, +.>Representing the second intensity concentration of obstetrical surgical image +.>Luminance value corresponding to each pixel, +.>Representing a first luminance enhancement factor, ">Representing a second luminance enhancement factor.
In particular, the obstetrical operation image is first brightnessReplacing the brightness value on the corresponding pixel point in the obstetrical operation image corresponding to the brightness enhancement value by all the brightness enhancement values in the enhancement set; replacing brightness values on corresponding pixel points in the obstetrical operation image corresponding to all brightness enhancement values in the second brightness enhancement set of the obstetrical operation image with brightness enhancement values, and taking the replaced obstetrical operation image as the obstetrical operation brightness enhancement image, for example, a certain pixel point in the obstetrical operation image is expressed as，/>Luminance value representing the pixel, +.>Representing the width of the pixel, +.>Representing the height of the pixel, the brightness value of the pixel after strengthening is +. >The pixel points after the obstetrical operation image reinforcement are expressed as。
In step 103, performing a scalpel image feature matrix conversion on the obstetrical scalpel brightness enhancement image to obtain an obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset coefficient of the obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset matrix according to the obstetrical scalpel image feature matrix and the obstetrical scalpel image feature offset coefficient, and further determining an obstetrical scalpel feature enhancement image.
In some embodiments, the performing the scalpel image feature matrix transformation on the obstetrical operation brightness enhancement image may be implemented by the following steps:
performing RGB conversion on the brightness enhancement image of the obstetrical operation to obtain an enhanced RGB image of the obstetrical operation;
determining a RGB threshold interval of a scalpel;
and determining an obstetrical scalpel image feature matrix according to the RGB threshold interval of the scalpel and the RGB values in the obstetrical surgery strengthening RGB image.
Specifically, during implementation, the obstetrical operation brightness enhancement image can be transferred into an XYZ color space, each pixel value in the XYZ color space is converted into a corresponding value in an RGB color space, and the obstetrical operation brightness enhancement image after conversion is used as an obstetrical operation enhancement RGB image; inputting RGB values in the obstetrical operation strengthening RGB image in the RGB threshold interval of the scalpel into positions corresponding to the transition matrix, inputting other RGB values in the obstetrical operation strengthening RGB image into positions corresponding to the scalpel transition matrix after the RGB values are initially 0, traversing all RGB values in the obstetrical operation strengthening RGB image, and combining the RGB values into the scalpel transition matrix, for example: there is a reinforced RGB image for obstetrical surgery, the RGB value of the first row and first column on the left is 180, the RGB value of the first row and second column on the left is 235, the RGB value of the first column on the second row on the left is 110, the RGB threshold interval of the scalpel is [170,220], and the corresponding scalpel transition matrix is:
It should be noted that, the color of the medical scalpel is usually silver, the silver is a lighter gray, and the medical scalpel is usually formed by relatively approaching the values of the three channels of red, green and blue, that is, the values of R, G, B are approximately equal, so that the average value of the three channels of red, green and blue is mostly RGB, the pixel point with the non-approaching value of the three channels of red, green and blue is eliminated, the pixel value of the pixel point is initially 0, and the pixel point is input into the position corresponding to the transition matrix; in order to make the scalpel transition matrix appear complete, the above exemplary scalpel transition matrix is used instead of other locations in the scalpel transition matrix where there are no specific exemplary pixel values, indicating only gaps, and no specific meaning.
It should be noted that, the RGB threshold interval of the scalpel in the present application may be determined by acquiring a large amount of data of RGB images of the scalpel, which is not described herein.
In some embodiments, the obstetric scalpel image feature offset coefficient of the obstetric scalpel image feature matrix can be determined using the following formula:
wherein,representing the characteristic offset coefficient of the obstetrical scalpel image, +.>Representing the +.f in the obstetrical scalpel image feature matrix >RGB values->Representing the total number of RGB threshold intervals in the brightness enhancement image of obstetrical surgery, ++>The maximum RGB values in the obstetrical surgery brightness enhancement image at the scalpel RGB threshold interval are represented.
In some embodiments, determining the obstetric scalpel image feature offset matrix from the obstetric scalpel image feature matrix and the obstetric scalpel image feature offset coefficient may be obtained using the following formula:
wherein,represents RGB offset values +.>Representing the +.f in the obstetrical scalpel image feature matrix>RGB values->Representing the obstetrical scalpel image characteristic offset coefficient.
In specific implementation, all RGB values in the obstetrical scalpel image feature matrix are traversed, each value is offset by applying the formula, the offset obstetrical scalpel image feature matrix is used as the obstetrical scalpel image feature offset matrix, and the offset RGB values are used as the RGB offset values.
In some embodiments, determining the obstetric scalpel feature enhanced image may be accomplished by:
acquiring all RGB offset values in an obstetrical scalpel image characteristic offset matrix;
and determining the characteristic intensified image of the obstetrical surgical knife according to all the RGB values.
In specific implementation, the RGB offset value is input into a position corresponding to the brightness enhancement image of obstetrical operation; inputting the value with value 0 in the characteristic offset matrix of the obstetrical operation knife image to the position corresponding to the obstetrical operation brightness enhancement image Replacing the original RGB values; repeating the steps until all pixel points in the obstetrical operation brightness enhancement image are replaced, and taking the replaced obstetrical operation brightness enhancement image as an obstetrical operation knife characteristic enhancement image.
In the present application, the offset of the pixel points of the data scalpel is to increase the saturation of the pixel points, so that the pixel points of the scalpel are more prominent in the image, and the RGB values of the pixel points areWhile the pixel is shown as being purely green, other colors may be used instead in other embodiments, and are not limited in this regard.
In step 104, an obstetric scalpel meat entering value and an obstetric scalpel inclination angle are determined according to the obstetric scalpel characteristic intensified image, and an obstetric scalpel meat entering dangerous value is calculated according to the obstetric scalpel meat entering value and the obstetric scalpel inclination angle.
In some embodiments, two video shooting machine positions are installed in an operating room, one machine position is located right above the operating table and can shoot a surgical knife of a surgeon, and videos shot by the machine positions are used as main monitoring videos of obstetrical surgery; the other machine position is located at the horizontal position of the operation table, and can shoot the operation knife of the operator, the video shot by the machine position is used as the auxiliary monitoring video of the obstetrical operation, and the obstetrical operation monitoring video acquired in the step 101 includes: obstetrical surgery main monitoring video and obstetrical surgery auxiliary monitoring video.
In some embodiments, determining the obstetric scalpel penetration value and the obstetric scalpel inclination angle from the obstetric scalpel feature enhanced image may be achieved by:
determining the meat feeding value of the obstetrical surgical knife according to the obstetrical surgical knife characteristic intensified image in the obstetrical surgical main monitoring video;
and determining the inclination angle of the obstetric scalpel according to the obstetric scalpel characteristic intensified image in the obstetric operation auxiliary monitoring video.
In the specific implementation, before the scalpel enters the flesh on the belly of the pregnant woman, obtaining the horizontal length of the scalpel through the obstetrical scalpel characteristic reinforced image obtained by the obstetrical operation main monitoring video, and taking the horizontal length as the initial scalpel length; when a doctor performs an operation by using a scalpel, obtaining the horizontal length of the scalpel at the moment again through the obstetrical scalpel characteristic reinforced image acquired by the obstetrical operation main monitoring video, and taking the horizontal length of the scalpel at the moment as the second length of the scalpel, so that the obstetrical scalpel has a meat entering value = initial scalpel length-second length of the scalpel; and obtaining the obstetrical scalpel inclination angle of the scalpel through the obstetrical scalpel characteristic reinforced image acquired by the obstetrical operation auxiliary monitoring video.
In some embodiments, the calculating the obstetrical scalpel meat penetration risk value according to the obstetrical scalpel meat penetration value and the obstetrical scalpel inclination angle may be performed by:
determining the first in the main monitoring videoSurgical knife length value of moment main monitoring video +.>；
Determining the first of the auxiliary monitoring videosSurgical knife length value of time auxiliary monitoring video>；
Determination of meat wall thickness value from body fat rate of parturient；
Determining an initial length value of a scalpel；
According to the first item in the main monitoring videoSurgical knife length value of moment main monitoring video +.>The>Surgical knife length value of time auxiliary monitoring video>The meat wall thickness value->And saidSurgical knife initial Length value +.>Determining an obstetrical scalpel meat penetration risk value, wherein the obstetrical scalpel meat penetration risk value can be determined by the following formula:
wherein,indicating the risk value of obstetrical scalpel entering meat, +.>Indicating the scalpel penetration correction factor.
In the specific implementation, a scalpel display value in a main monitoring video is obtained and multiplied by a relative reduction multiple of the video in the main monitoring video and reality, so that a length value of a scalpel in reality is obtained, and the length value is used as a scalpel length value of the main monitoring video; obtaining a scalpel display value in the auxiliary monitoring video, multiplying the scalpel display value by a relative reduction multiple of the video in the auxiliary monitoring video and reality, so as to obtain a length value of the scalpel in reality, and taking the length value as a scalpel length value of the auxiliary monitoring video; obtaining the body fat rate of a puerpera, determining the thickness from the surface of the belly to the surface of the viscera of the puerpera according to the body fat rate and a big data technology, and taking the thickness as a meat wall thickness value; the actual length of the scalpel in reality is obtained, and the actual length is taken as an initial length value of the scalpel.
It should be noted that, the scalpel in the present application may be obtained by acquiring the offset angles in the main monitoring video and the auxiliary monitoring video, and combining the forward kinematics and the inverse kinematics, which are not described herein.
In step 105, the obstetrical operation is monitored according to the obstetrical scalpel meat risk value and a predetermined obstetrical scalpel meat risk threshold interval.
In some embodiments, the monitoring of the obstetrical operation according to the obstetrical scalpel penetration risk value and the predetermined obstetrical scalpel penetration risk threshold interval may be achieved by:
when the obstetrical scalpel meat entering dangerous value is lower than a preset obstetrical scalpel meat entering dangerous threshold value interval, normal operation information is sent out;
when the obstetrical scalpel meat entering dangerous value is in a preset obstetrical scalpel meat entering dangerous threshold value interval, early warning information is sent;
and when the obstetrical scalpel meat entering dangerous value exceeds a preset obstetrical scalpel meat entering dangerous threshold value interval, sending out alarm information.
In specific implementation, for example: the preset obstetrical scalpel meat entering danger threshold interval is 3 cm to 8 cm, and when the obstetrical scalpel meat entering danger value is 10 cm, normal operation maintaining information is sent out; when the risk value of the obstetrical scalpel for entering meat is 6 cm, early warning information is sent; when the danger value of the obstetrical scalpel entering the meat is 2 cm, alarm information is sent out.
In some embodiments, the warning level of the warning information is indicated by displaying a green color on the signal light as normal operation information, by gradually changing the color of the signal light from green to yellow to red, and by displaying a red color on the signal light and flashing as warning information as the approaching red color.
Additionally, in another aspect of the present application, in some embodiments, the present application provides an image processing based obstetric surgical monitoring system, referring to fig. 2, which is a schematic diagram of exemplary hardware and/or software of an image processing based obstetric surgical monitoring system according to some embodiments of the present application, the image processing based obstetric surgical monitoring system 200 comprising: the obstetrical operation image obtaining module 201, the obstetrical operation brightness enhancement image determining module 202, the obstetrical operation knife characteristic enhancement image determining module 203, the obstetrical operation knife meat risk value obtaining module 204 and the obstetrical operation monitoring module 205 are respectively described as follows:
the obstetrical operation image acquisition module 201 is mainly used for acquiring an obstetrical operation monitoring video, and extracting frames of the obstetrical operation monitoring video to obtain an obstetrical operation image;
The obstetrical operation brightness enhancement image determining module 202 in the present application, the obstetrical operation brightness enhancement image determining module 202 is mainly configured to determine a first brightness set of an obstetrical operation image and a second brightness set of the obstetrical operation image, perform enhancement processing on the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image to obtain a first brightness enhancement set of the obstetrical operation image and a second brightness enhancement set of the obstetrical operation image, and determine an obstetrical operation brightness enhancement image according to the first brightness enhancement set of the obstetrical operation image and the second brightness enhancement set of the obstetrical operation image;
the obstetrical scalpel characteristic enhanced image determining module 203 in the present application, the obstetrical scalpel characteristic enhanced image determining module 203 is mainly configured to convert the obstetrical scalpel brightness enhanced image into an obstetrical scalpel image characteristic matrix, determine an obstetrical scalpel image characteristic offset coefficient of the obstetrical scalpel image characteristic matrix, determine an obstetrical scalpel image characteristic offset matrix according to the obstetrical scalpel image characteristic matrix and the obstetrical scalpel image characteristic offset coefficient, and determine an obstetrical scalpel characteristic enhanced image according to the obstetrical scalpel image characteristic offset matrix;
The obstetrical scalpel meat-entering risk value obtaining module 204 in the application, wherein the obstetrical scalpel meat-entering risk value obtaining module 204 is mainly used for determining an obstetrical scalpel meat-entering value and an obstetrical scalpel inclination angle according to the obstetrical scalpel characteristic intensified image, and calculating to obtain an obstetrical scalpel meat-entering risk value according to the obstetrical scalpel meat-entering value and the obstetrical scalpel inclination angle;
the obstetrical operation monitoring module 205, in the present application, the obstetrical operation monitoring module 205 is mainly configured to monitor the obstetrical operation according to the obstetrical scalpel meat-in risk value and a predetermined obstetrical scalpel meat-in risk threshold interval.
The various modules in the obstetrical surgical monitoring system based on image processing as described above may be implemented in whole or in part in software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In addition, in one embodiment, the present application provides a computer device, which may be a server, and an internal structure diagram thereof may be as shown in fig. 3. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing obstetrical operation monitoring data based on image processing. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of obstetrical surgical monitoring based on image processing.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, which when executed by the processor performs the steps of the above-described embodiments of an image processing based obstetrical surgical monitoring method.
In one embodiment, a computer readable storage medium is provided, storing a computer program which when executed by a processor implements the steps of the above-described image processing-based obstetric surgical monitoring method embodiment.
In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium and executes the computer instructions to cause the computer device to perform the steps of the obstetrical surgical monitoring method embodiments based on image processing described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
In summary, in the obstetrical operation monitoring system based on image processing and the related device thereof disclosed in the embodiments of the present application, firstly, an obstetrical operation monitoring video is acquired, a frame extraction is performed on the obstetrical operation monitoring video to obtain an obstetrical operation image, brightness division is performed on the obstetrical operation image to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image, reinforcement processing is performed on the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image to obtain a first brightness reinforcement set of the obstetrical operation image and a second brightness reinforcement set of the obstetrical operation image, a knife characteristic conversion is performed on the obstetrical operation brightness reinforcement image to obtain a knife image characteristic matrix, a knife image characteristic offset coefficient of the obstetrical operation knife is determined according to the knife image characteristic matrix of the obstetrical operation knife and the knife image characteristic offset coefficient of the obstetrical operation knife, further, the obstetrical operation characteristic image is determined, the obstetrical operation knife is performed according to the first brightness reinforcement set of the obstetrical operation image and the second brightness reinforcement set of the obstetrical operation image, the obstetrical operation knife is determined, the obstetrical operation knife is further processed according to the inclination value of the obstetrical operation image and the obstetrical operation knife is further calculated according to the inclination value of the obstetrical operation monitoring video, and the obstetrical operation monitoring knife is further calculated according to the inclination value of the obstetrical operation video and the obstetrical operation monitoring knife is further calculated according to the predetermined value, finally, the obstetrical operation is monitored according to the meat entering dangerous value of the obstetrical operation knife, and compared with the prior art, the accuracy of the obstetrical operation monitoring is greatly improved.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (7)
1. An obstetrical operation monitoring method based on image processing, which is characterized by comprising the following steps:
acquiring obstetrical operation monitoring video, and performing frame extraction on the obstetrical operation monitoring video to obtain an obstetrical operation image;
performing brightness division on the obstetrical operation image to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image, and performing reinforcement treatment on the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image to obtain a first brightness reinforcement set of the obstetrical operation image and a second brightness reinforcement set of the obstetrical operation image; the strengthening treatment of the first brightness set of the obstetrical operation image and the second brightness set of the obstetrical operation image specifically comprises the following steps:
Determining a first intensity enhancement factor from the first intensity set of obstetrical images;
determining a second intensity enhancement factor from the second intensity set of obstetrical images;
determining a first intensity enhancement set of the obstetrical surgical image from the first intensity enhancement coefficient and the first intensity set of the obstetrical surgical image;
determining a second intensity enhancement set of the obstetrical surgical image from the second intensity enhancement coefficient and the second intensity set of the obstetrical surgical image;
wherein a first intensity enhancement factor is determined from the first intensity set of obstetrical surgical images; the first brightness enhancement factor is determined by:
determining a first intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining the average value of the brightness values corresponding to all the pixel points in the first brightness set of the obstetrical operation image；
Determining all images in the first intensity set of obstetrical surgical imagesTotal number of pixels；
According to the first brightness concentration of the obstetrical operation imageLuminance value corresponding to each pixel>Mean value of brightness values corresponding to all pixels in the first brightness set of the obstetrical operation image +.>And the total number of all pixels in the first intensity set of the obstetrical image +. >Determining a first brightness enhancement factor, wherein the first brightness enhancement factor is determined using the following formula:
wherein,representing a first luminance enhancement factor, ">Expressed as +.>An exponential function of the base +.>Representing the enhancement factor for constraining the luminance value of the first luminance set after enhancement;
wherein a second intensity enhancement factor is determined from the second set of intensity of the obstetrical surgical image; the second brightness enhancement factor is determined by:
determining the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation image；
Determining a second intensity set of the obstetric imageLuminance value corresponding to each pixel>；
Determining a total number of all pixels in the second intensity set of the obstetrical image；
According to the mean value of the brightness values corresponding to all the pixel points in the second brightness set of the obstetrical operation imageSecond intensity set of obstetrical image +.>Luminance value corresponding to each pixel>And the total number of all pixels in the second intensity set of the obstetrical image +.>Determining a second brightness enhancement factor, wherein the second brightness enhancement factor is determined using the formula:
wherein,representing a second luminance enhancement factor, ">Is a common logarithm, representing a base 10 logarithm function;
Determining an obstetrical operation brightness enhancement image according to the first brightness enhancement set of the obstetrical operation image and the second brightness enhancement set of the obstetrical operation image;
performing scalpel image feature matrix conversion on the obstetrical operation brightness enhancement image to obtain an obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset coefficient of the obstetrical scalpel image feature matrix, determining an obstetrical scalpel image feature offset matrix according to the obstetrical scalpel image feature matrix and the obstetrical scalpel image feature offset coefficient, and further determining an obstetrical scalpel feature enhancement image;
determining the meat feeding value of the obstetrical scalpel and the inclination angle of the obstetrical scalpel according to the characteristic intensified image of the obstetrical scalpel, and calculating to obtain the meat feeding dangerous value of the obstetrical scalpel according to the meat feeding value of the obstetrical scalpel and the inclination angle of the obstetrical scalpel; the obstetrical scalpel meat entering dangerous value obtained by calculating according to the obstetrical scalpel meat entering value and the obstetrical scalpel inclination angle is obtained by the following steps:
determining the first in the main monitoring videoSurgical knife length value of moment main monitoring video +.>；
Determining the first of the auxiliary monitoring videosSurgical knife length value of time auxiliary monitoring video >；
Determination of meat wall thickness value from body fat rate of parturient；
Determining an initial length value of a scalpel；
According to the first item in the main monitoring videoSurgical knife length value of moment main monitoring video +.>The>Surgical knife length value of time auxiliary monitoring video>The meat wall thickness value->And said scalpel initial length value +.>Determining an obstetrical scalpel meat penetration risk value, wherein the obstetrical scalpel meat penetration risk value is determined by the following formula:
wherein,indicating the risk value of obstetrical scalpel entering meat, +.>Indicating the correction coefficient of the scalpel meat;
and monitoring the obstetrical operation according to the obstetrical scalpel meat-in dangerous value and a preset obstetrical scalpel meat-in dangerous threshold interval.
2. The method of claim 1, wherein the intensity dividing of the obstetric image specifically comprises:
acquiring brightness values corresponding to all pixel points in the obstetrical operation image;
determining a brightness set dividing interval according to brightness values corresponding to all the pixel points;
and dividing all pixel points in the obstetrical operation image according to the brightness set dividing interval to obtain a first brightness set of the obstetrical operation image and a second brightness set of the obstetrical operation image.
3. The method of claim 2, wherein determining the luminance set partition interval specifically comprises:
determining an upper boundary value of the brightness set dividing interval;
determining a lower boundary value of the brightness set dividing interval;
and determining a brightness set dividing interval according to the interval upper boundary value and the interval lower boundary value.
4. The method of claim 1, wherein monitoring obstetric surgery specifically comprises:
when the obstetrical scalpel meat entering dangerous value is lower than a preset obstetrical scalpel meat entering dangerous threshold value interval, normal operation information is sent out;
when the obstetrical scalpel meat entering dangerous value is in a preset obstetrical scalpel meat entering dangerous threshold value interval, early warning information is sent;
and when the obstetrical scalpel meat entering dangerous value exceeds a preset obstetrical scalpel meat entering dangerous threshold value interval, sending out alarm information.
5. An obstetric operation monitoring system based on image processing, which is controlled by the method of claim 1, comprising:
the obstetrical operation image acquisition module is used for acquiring an obstetrical operation monitoring video, and extracting frames of the obstetrical operation monitoring video to obtain an obstetrical operation image;
The obstetrical operation brightness enhancement image determining module is used for determining an obstetrical operation image first brightness set and an obstetrical operation image second brightness set of the obstetrical operation image, carrying out enhancement processing on the obstetrical operation image first brightness set and the obstetrical operation image second brightness set to obtain an obstetrical operation image first brightness enhancement set and an obstetrical operation image second brightness enhancement set, and determining an obstetrical operation brightness enhancement image according to the obstetrical operation image first brightness enhancement set and the obstetrical operation image second brightness enhancement set;
the obstetrical scalpel characteristic strengthening image determining module is used for converting the obstetrical scalpel brightness strengthening image into an obstetrical scalpel image characteristic matrix, determining an obstetrical scalpel image characteristic deviation coefficient of the obstetrical scalpel image characteristic matrix, determining an obstetrical scalpel image characteristic deviation matrix according to the obstetrical scalpel image characteristic matrix and the obstetrical scalpel image characteristic deviation coefficient, and determining an obstetrical scalpel characteristic strengthening image according to the obstetrical scalpel image characteristic deviation matrix;
the obstetrical scalpel meat entering dangerous value determining module is used for determining an obstetrical scalpel meat entering value and an obstetrical scalpel inclination angle according to the obstetrical scalpel characteristic intensified image, and calculating the obstetrical scalpel meat entering dangerous value according to the obstetrical scalpel meat entering value and the obstetrical scalpel inclination angle;
And the obstetrical operation monitoring module is used for monitoring the obstetrical operation according to the obstetrical scalpel meat-in dangerous value and a preset obstetrical scalpel meat-in dangerous threshold interval.
6. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program implements the steps of the image processing based obstetric procedure monitoring method of any of claims 1 to 4.
7. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the steps of an image processing based obstetric procedure monitoring method according to any of claims 1 to 4.
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