CN117635545A - Amniotic fluid index measurement method, ultrasonic imaging equipment and storage medium - Google Patents
Amniotic fluid index measurement method, ultrasonic imaging equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a method for measuring amniotic fluid index, which comprises the following steps: acquiring a key frame image corresponding to each quadrant in a target object, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a maximum amniotic fluid pool area corresponding to the corresponding quadrant; positioning the position information of the maximum vertical radial line from each key frame image respectively; determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line; and summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object.
Description
Description of the division
The application is a divisional application of Chinese patent with the application date of 2018, 12-month and 14-date, the application number of 201811532805.5 and the invention name of 'a measuring method of amniotic fluid index, ultrasonic imaging equipment and storage medium'.
Technical Field
The application relates to the technical field of image processing, in particular to a amniotic fluid index measurement method, ultrasonic imaging equipment and a storage medium.
Background
Currently, in the ultrasonic examination project aiming at the fetus clinically, the measurement of amniotic fluid index is a very important measurement project, which runs through the whole pregnancy period of a pregnant woman, is an important index for evaluating whether the pregnant woman is pregnant or not, and is very important for the growth and development of the fetus and the health evaluation of the mother.
The conventional amniotic fluid index measurement is to divide an automatic right angle into four different quadrants by taking an umbilical horizontal line and a white abdominal line as marks, measure the vertical radial line of the largest amniotic fluid pool of each quadrant, and calculate the sum of the four vertical radial lines to obtain the amniotic fluid index.
In the actual clinical measurement process, in the image of the largest amniotic fluid pool in each quadrant, a doctor is required to manually select two end points of the vertical diameter line according to clinical experience knowledge so as to further measure the vertical diameter line, so that the measurement efficiency is low, and the measurement accuracy cannot be ensured.
Disclosure of Invention
In order to solve the existing technical problems, the embodiment of the application expects to provide a amniotic fluid index measuring method, ultrasonic imaging equipment and a storage medium, which can automatically measure the vertical radial line length of the maximum amniotic fluid pool area in the key frame image of each quadrant, sum the vertical radial line length to obtain the amniotic fluid index, and improve the amniotic fluid index measuring efficiency and accuracy.
In order to achieve the above purpose, the technical solution of the embodiments of the present application is implemented as follows:
the embodiment of the application provides a method for measuring amniotic fluid index, which comprises the following steps:
acquiring a key frame image corresponding to each quadrant in a target object, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a amniotic fluid pool area corresponding to the corresponding quadrant;
Positioning the position information of the maximum vertical radial line of the amniotic fluid pool area from each key frame image;
determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line;
summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object;
the method for acquiring the key frame image corresponding to each quadrant in the target object comprises the following steps:
acquiring multi-frame images corresponding to each quadrant respectively;
and determining the key frame image from the multi-frame image according to a preset frame determination method.
In the above solution, after the acquiring the multi-frame image corresponding to each quadrant, the method further includes:
and displaying the multi-frame image.
In the above aspect, after the displaying the multi-frame image, the method further includes:
receiving a selection instruction of the multi-frame image;
and determining the key frame image from the multi-frame images according to the selection instruction.
In the above aspect, the determining the key frame image from the multi-frame image according to a preset frame determining method includes:
according to a preset image segmentation algorithm, carrying out amniotic fluid pool region segmentation on the multi-frame image to obtain a first segmentation result;
Determining the largest sheep pool frame image corresponding to each quadrant from the multi-frame images according to the first segmentation result;
and determining the maximum amniotic fluid pool frame image as the key frame image.
In the above aspect, the determining the key frame image from the multi-frame image according to a preset frame determining method includes:
inputting the multi-frame images into a preset image segmentation network to segment the sheep pool area, and obtaining a second segmentation result;
determining the maximum sheep pool frame image corresponding to each quadrant from the multi-frame images according to the second segmentation result;
and determining the maximum amniotic fluid pool frame image as the key frame image.
In the above aspect, the determining the key frame image from the multi-frame image according to a preset frame determining method includes:
inputting the multi-frame images into a preset key frame identification network to obtain the key frame probability corresponding to each frame of image in the multi-frame images;
determining maximum key frame probability frame images corresponding to each quadrant respectively from the multi-frame images;
and determining the maximum key frame probability frame image as the key frame image.
In the above solution, the positioning information of the maximum vertical radial line from each of the key frame images includes:
respectively acquiring the maximum amniotic fluid pool area from each key frame image;
and respectively positioning the position information of the maximum vertical radial line from each maximum amniotic fluid pool area.
In the above solution, the obtaining the maximum amniotic fluid pool area from each of the key frame images includes:
and respectively carrying out amniotic fluid pool area segmentation on each key frame image according to a preset image segmentation algorithm to obtain the maximum amniotic fluid pool area.
In the above solution, the obtaining the maximum amniotic fluid pool area from each of the key frame images includes:
and inputting each key frame image into a preset image segmentation network to segment the goat water pool area, and obtaining the maximum goat water pool area.
An embodiment of the present application provides an ultrasound imaging apparatus including:
an ultrasonic probe;
a transmission/reception selection switch;
a transmission/reception sequence controller which excites the ultrasonic probe to transmit ultrasonic waves to a target object through the transmission/reception selection switch and controls the ultrasonic probe to receive ultrasonic echoes returned from the target object;
A processor for performing the steps of:
acquiring key frame images corresponding to each quadrant in the target object through the ultrasonic probe; the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a amniotic fluid pool area corresponding to the corresponding quadrant; positioning position information of the maximum vertical radial line position of the amniotic fluid pool area pair from each key frame image; determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line; summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index corresponding to the target object; the obtaining the key frame image corresponding to each quadrant in the target object includes: acquiring multi-frame images corresponding to each quadrant respectively; determining the key frame image from the multi-frame image according to a preset frame determination method
And the display is used for displaying each key frame image.
In the above ultrasonic imaging apparatus, the display is further configured to display the multi-frame image.
In the above ultrasonic imaging apparatus, the processor is further configured to receive a selection instruction for the multi-frame image after the display displays the multi-frame image; and determining the key frame image from the multi-frame images according to the selection instruction.
In the above ultrasonic imaging device, the processor is specifically configured to segment the amniotic fluid pool area of the multi-frame image according to a preset image segmentation algorithm, so as to obtain a first segmentation result; determining the largest sheep pool frame image corresponding to each quadrant from the multi-frame images according to the first segmentation result; and determining the maximum amniotic fluid pool frame image as the key frame image.
In the above ultrasonic imaging device, the processor is specifically configured to input each frame of image in the multiple frames of images into a preset image segmentation network to segment a sheep pool area, so as to obtain a second segmentation result; determining the maximum sheep pool frame image corresponding to each quadrant from the multi-frame image sequence according to the second segmentation result; and determining the maximum amniotic fluid pool frame image as the key frame image.
In the above ultrasonic imaging device, the processor is specifically configured to input the multiple frame images into a preset key frame identification network, and obtain a key frame probability corresponding to each frame image in the multiple frame images; determining maximum key frame probability frame images corresponding to each quadrant respectively from the multi-frame images; and determining the maximum key frame probability frame image as the key frame image.
In the above ultrasonic imaging apparatus, the processor is specifically configured to obtain the maximum amniotic fluid pool area from each of the key frame images; and respectively positioning the position information of the maximum vertical radial line from each maximum amniotic fluid pool area.
In the above ultrasonic imaging apparatus, the processor is specifically configured to segment the amniotic fluid pool area of each of the key frame images according to a preset image segmentation algorithm, so as to obtain the maximum amniotic fluid pool area.
In the above ultrasonic imaging apparatus, the processor is specifically configured to input the key frame image into a preset image segmentation network to segment a amniotic fluid pool area, so as to obtain the maximum amniotic fluid pool area.
The embodiment of the application provides a computer readable storage medium, wherein the computer readable storage medium stores an amniotic fluid index measurement program, and the amniotic fluid index measurement program can be executed by a processor to realize the amniotic fluid index measurement method.
Therefore, in the technical scheme of the embodiment of the application, a key frame image corresponding to each quadrant in the target object is obtained, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a maximum amniotic fluid pool area corresponding to the corresponding quadrant; positioning the position information of the maximum vertical radial line from each key frame image respectively; determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line; and summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object. That is, according to the technical scheme provided by the embodiment of the application, the vertical radial line length of the maximum amniotic fluid pool area in the key frame image of each quadrant can be automatically measured, and the amniotic fluid indexes are obtained by summation, so that the efficiency and the accuracy of amniotic fluid index measurement are improved.
Drawings
Fig. 1 is a schematic structural diagram of an ultrasound imaging apparatus according to an embodiment of the present application;
fig. 2 is a flow chart of a method for measuring amniotic fluid index according to an embodiment of the present application;
FIG. 3 is an exemplary single frame image provided in an embodiment of the present application;
FIG. 4 is a schematic diagram of an exemplary amniotic fluid pool area segmentation result according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of exemplary maximum vertical radial position information provided in an embodiment of the present application;
fig. 6 is a schematic view of an exemplary four quadrant maximum vertical radial provided in an embodiment of the present application.
Detailed Description
For a more complete understanding of the features and technical content of the embodiments of the present application, reference should be made to the following detailed description of the embodiments of the present application, taken in conjunction with the accompanying drawings, which are for purposes of illustration only and not intended to limit the embodiments of the present application.
The embodiment of the application provides a method for measuring amniotic fluid index, which is applied to ultrasonic imaging equipment. Fig. 1 is a schematic structural diagram of an ultrasound imaging apparatus according to an embodiment of the present application. As shown in fig. 1, the ultrasonic imaging apparatus 10 includes: an ultrasound probe 101, a transmit/receive selection switch 102, a transmit/receive sequence controller 103, a processor 104, and a display 105.
It should be noted that, in the embodiment of the present application, the transmit/receive sequence controller 103 may excite the ultrasound probe 101 to transmit ultrasound waves to the target object through the transmit/receive selection switch 102, and may also control the ultrasound probe 101 to receive ultrasound echoes returned from the target object, so as to obtain ultrasound echo signals/data, so as to obtain an ultrasound image of the target object, where the ultrasound image may be a two-dimensional ultrasound image or another multi-dimensional ultrasound image.
It should be noted that, in the embodiment of the present application, the ultrasound imaging apparatus may further include: the memory 106, the ultrasound image obtained by the processor 104 may be stored in the memory 106, and the ultrasound image may be displayed on the display 105.
In the embodiment of the present application, the display 105 of the ultrasonic imaging system 10 may be a touch display screen, a liquid crystal display screen, or the like, or may be an independent display device such as a liquid crystal display, a television, or the like, which is independent of the ultrasonic imaging device 10, or may be a display screen on an electronic device such as a mobile phone, a tablet computer, or the like.
In the embodiment of the present application, the memory 106 of the ultrasound imaging apparatus 10 may be a flash memory card, a solid state memory, a hard disk, or the like.
Embodiments of the present application also provide a computer readable storage medium storing an amniotic fluid index measurement program executable by the processor 104 to implement the method for measuring an amniotic fluid index of the present application.
In one embodiment, the computer readable storage medium may be memory 106, which may be a non-volatile storage medium such as a flash memory card, solid state memory, hard disk, or the like.
In the embodiments of the present application, the processor 104 of the ultrasound imaging system device 10 may be implemented by software, hardware, firmware, or a combination thereof, and may use a circuit, a single or multiple application specific integrated circuits (application specific integrated circuits, ASIC), a single or multiple general purpose integrated circuits, a single or multiple microprocessors, a single or multiple programmable logic devices, or a combination of the foregoing circuits or devices, or other suitable circuits or devices, so that the processor 104 may perform the respective steps of the method for measuring amniotic fluid index in the various embodiments.
The following describes in detail a method of measuring amniotic fluid index in the present application based on the above-described ultrasonic imaging apparatus 10.
Fig. 2 is a schematic flow chart of a method for measuring amniotic fluid index according to an embodiment of the present application, where the method is applied to an ultrasonic device, and the ultrasonic device may be a portable ultrasonic device for ultrasonic imaging or a table ultrasonic device. As shown in fig. 2, the process mainly includes the following steps:
s201, acquiring key frame images corresponding to each quadrant in the target object, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a maximum amniotic fluid pool area corresponding to the corresponding quadrant.
In the embodiment of the present application, the processor 104 of the ultrasonic imaging apparatus 10 acquires ultrasonic images corresponding to a plurality of quadrants of the target object through the ultrasonic probe 101, and determines a key frame image corresponding to each quadrant from the ultrasonic images.
It should be noted that in the embodiment of the present application, the target object is uterus of a pregnant woman, amniotic fluid index is measured during the whole gestation period of the pregnant woman, and a doctor can quadrant divide the uterus according to different modes according to actual requirements. The number of quadrants specifically divided is not limited in the embodiments of the present application.
For example, in the embodiment of the present application, the umbilical line and the abdominal line of the pregnant woman may be used as markers, and the target object, i.e. the uterus of the pregnant woman, may be divided into four different quadrants at right angles, so that a keyframe image corresponding to each of the four quadrants needs to be acquired.
It should be noted that, in the embodiment of the present application, the key frame image corresponding to each quadrant is the frame image including the maximum amniotic fluid pool area corresponding to the quadrant.
In the embodiment of the present application, the processor 104 obtains the keyframe image corresponding to each quadrant in the target object through the ultrasound probe 101, and there may be several ways, and several possible implementations are illustrated below, where one possible implementation is: acquiring single-frame images corresponding to each quadrant respectively; determining a single frame image as a key frame image, one possible implementation is: acquiring multi-frame images corresponding to each quadrant respectively; and determining a key frame image from the multi-frame images according to a preset frame determination method.
It can be appreciated that in the embodiment of the present application, a doctor may place the ultrasound probe 101 for a certain quadrant according to a specific angle or position according to clinical experience, the ultrasound probe 101 transmits ultrasound waves to the quadrant, receives ultrasound echoes, and the processor 104 processes the ultrasound echoes to obtain a single frame image of the quadrant, and directly determines the single frame image as a key frame image of the quadrant.
Fig. 3 is an exemplary single frame image provided in an embodiment of the present application. As shown in fig. 3, for a single frame image corresponding to one of a plurality of quadrants in the target object, the processor 104 acquires the single frame image through the ultrasound probe 101, and determines a key frame image corresponding to the corresponding quadrant from the single frame image.
It may be appreciated that, in this embodiment of the present application, the ultrasonic imaging apparatus 10 may also transmit ultrasonic waves for each quadrant for multiple times through the ultrasonic probe 101, and receive ultrasonic echoes for multiple times, and the processor 104 may process the ultrasonic echoes received for multiple times respectively, so as to obtain multiple ultrasonic images corresponding to the quadrant, that is, multiple frame images, and then, the processor may determine a key frame image corresponding to the quadrant from the multiple frame images according to a preset frame determination method. The specific preset frame determination method and the number of multi-frame images can be determined by a doctor according to clinical actual requirements, and the embodiment of the application is not limited.
Specifically, in the embodiment of the present application, the determining, by the processor 104 according to the preset frame determining method, the key frame image from the multi-frame images includes: according to a preset image segmentation algorithm, carrying out amniotic fluid pool region segmentation on the multi-frame image to obtain a first segmentation result; determining the largest sheep pool frame image corresponding to each quadrant respectively from the multi-frame images according to the first segmentation result; and determining the largest sheep pool frame image as a key frame image.
It should be noted that, in this embodiment of the present application, the processor 104 may directly segment the amniotic fluid pool area of each frame image in the multi-frame images corresponding to each quadrant according to the preset image segmentation algorithm, and the segmented images are the first segmentation results, and then, according to the first segmentation results, may directly determine the frame image with the largest amniotic fluid pool area in the multi-frame images corresponding to each quadrant, that is, the largest amniotic fluid pool frame image, where the largest amniotic fluid pool frame image is the key frame image required for calculating the amniotic fluid index later. The specific preset image segmentation algorithm is not limited in this embodiment.
Specifically, in this embodiment of the present application, the preset image segmentation algorithm may be based on a level set segmentation algorithm, a random walk algorithm, a graph segmentation algorithm, a serpentine algorithm, or the like, and the processor 104 may set a closed initial contour for each frame of image in the multi-frame image corresponding to each quadrant, that is, a closed curve, according to the level set segmentation algorithm, and control the closed curve to perform iterative change according to a certain rule or constraint condition, until the closed curve completely includes a dark area, that is, a amniotic fluid pool area in the image, that is, the amniotic fluid pool area is segmented from the image, that is, the first segmentation result is obtained. For each quadrant, the processor 104 may select, from the multiple frame images of the corresponding segmented amniotic fluid pool area, the image of the largest amniotic fluid pool area as the key frame image corresponding to the corresponding quadrant.
For example, in the embodiment of the present application, the umbilical level line and the abdominal white line of the pregnant woman may be used as markers, and the target object, i.e. the uterus of the pregnant woman, may be divided into four different quadrants, i.e. a first quadrant, a second quadrant, a third quadrant and a fourth quadrant, respectively. The processor 104 respectively acquires 10 frames of images corresponding to each quadrant, namely a multi-frame image, then, the processor 104 respectively performs the segmentation of the amniotic fluid pool area on each frame of the 10 frames of images corresponding to each of the four quadrants according to a preset image segmentation algorithm, so as to acquire a first segmentation result, then, the frame image with the largest amniotic fluid pool area is searched from the first segmentation result obtained by segmenting the 10 frames of images corresponding to the first quadrant, namely, the largest amniotic fluid pool frame image corresponding to the first quadrant is determined and is used as a key frame corresponding to the first quadrant, the frame image with the largest amniotic fluid pool area is searched from the first segmentation result obtained by segmenting the 10 frames of images corresponding to the second quadrant, namely, the largest amniotic fluid pool frame image corresponding to the second quadrant is determined and is used as a key frame corresponding to the second quadrant, and likewise, the key frame images corresponding to the third quadrant and the fourth quadrant can be respectively determined according to the same method.
Specifically, in the embodiment of the present application, the determining, by the processor 104 according to the preset frame determining method, the key frame image from the multi-frame images includes: inputting the multi-frame images into a preset image segmentation network to segment the sheep pool area, and obtaining a second segmentation result; determining the maximum sheep pool frame image corresponding to each quadrant respectively from the multi-frame images according to the second segmentation result; and determining the largest sheep pool frame image as a key frame image.
It should be noted that, in the embodiment of the present application, the preset image segmentation network may be obtained by training a large number of frame images and corresponding calibration results, that is, a large number of frame images need to be obtained in advance, and each frame image is marked with a sheep pool area to form a database, and the database is used to train the image segmentation network to be trained for segmenting the sheep pool area, so as to obtain the preset image segmentation network. The segmentation network to be trained can be pre-constructed according to actual requirements. The specific preset image segmentation network is not limited in this embodiment.
Specifically, in the embodiment of the present application, the preset image segmentation network may be a full convolutional neural network, a U-type full convolutional neural network, a regional non-convolutional neural network, and the like. For any one of the above preset image segmentation networks, it mainly includes: the convolution layer, the pooling layer and the up-sampling layer or the deconvolution layer can be used for extracting relevant characteristics of the amniotic fluid pool area from an input image, the pooling layer can be used for further extracting main relevant characteristics of the amniotic fluid pool area, and the convolution layer and the pooling layer can be used for reducing the image during processing, so that an output image with the same size as the input image can be finally output through the up-sampling layer or the deconvolution layer, the amniotic fluid pool area is directly segmented from the output image, and the output image is the second segmentation result. For each quadrant, the processor 104 may select, from the multiple frame images of the corresponding segmented amniotic fluid pool area, the image of the largest amniotic fluid pool area as the key frame image corresponding to the corresponding quadrant.
Specifically, in this embodiment of the present application, the preset image segmentation network may also be a positioning network obtained based on conventional machine learning, where each frame of image in the multi-frame image corresponding to each quadrant is first divided into a plurality of image blocks, the image blocks are extracted with various features, such as extracting local context information, texture information, haar features and the like, the extracted features are integrated and classified, the integrated and classified related features are input into a cascade classifier, for example, a vector machine, an adaptive classifier, a random forest classifier and the like, the integrated features are determined by the classifier, a class of features characterized as a amniotic fluid pool area is determined, the corresponding images are marked, so that the amniotic fluid pool area in the image is segmented, a second segmentation result is obtained, and the processor 104 may further locate the image with the largest amniotic fluid pool area in the multi-frame images corresponding to each quadrant, and determine the image with the largest amniotic fluid pool area as the key frame image of the corresponding quadrant.
For example, in the embodiment of the present application, the umbilical line and the abdominal line of the pregnant woman may be used as markers, and the target object, i.e. the uterus, is divided into four different quadrants, namely, a first quadrant, a second quadrant, a third quadrant and a fourth quadrant, respectively. The processor 104 obtains 20 frames of images corresponding to each quadrant, namely a multi-frame image, through the ultrasonic probe 101, then, the processor 104 inputs each frame of images corresponding to 20 frames of images corresponding to each quadrant of the four quadrants into a preset image segmentation network to respectively carry out the segmentation of the amniotic fluid pool area, so as to obtain a second segmentation result, then, the frame image with the largest amniotic fluid pool area is searched from the second segmentation result obtained by segmenting the 20 frames of images corresponding to the first quadrant, namely, the largest amniotic fluid pool frame image corresponding to the first quadrant is determined and is used as a key frame corresponding to the first quadrant, and the frame image with the largest amniotic fluid pool area is searched from the second segmentation result obtained by segmenting the 20 frames of images corresponding to the second quadrant, namely, the largest amniotic fluid pool frame image corresponding to the second quadrant is determined and is used as the key frame corresponding to the second quadrant.
Fig. 4 is a schematic diagram of an exemplary amniotic fluid pool area segmentation result according to an embodiment of the present application. The processor 104 performs the segmentation of the amniotic fluid pool area on each frame of the multi-frame images according to a preset image segmentation algorithm or a preset image segmentation network, wherein the segmentation result of one frame of image is shown in fig. 4, a dark area marked by a white curve in the figure is included in the image, and the area included in the image is the amniotic fluid pool area corresponding to the dark area.
Specifically, in the embodiment of the present application, the determining, by the processor 104 according to the preset frame determining method, the key frame image from the multi-frame images includes: inputting the multi-frame images into a preset key frame identification network to obtain the key frame probability corresponding to each frame of image in the multi-frame images; determining maximum key frame probability frame images corresponding to each quadrant respectively from multi-frame images; the largest key frame probability frame image is determined as the key frame image.
It should be noted that, in the embodiment of the present application, the preset key frame identification network may be a classification network, which is the same as the preset image segmentation network described above, and is also obtained by training a large number of frame images and corresponding calibration results, and is different from the preset image segmentation network described above, if the calibration result required for training the preset key frame identification network is a mark image or not is a key frame.
Specifically, in the embodiment of the present application, the preset key frame identification network may be VGG-16, VGG-19, ***-Net, and the like. The method comprises the steps of presetting a key frame identification network main structure, specifically, carrying out feature extraction on an input image through a convolution layer, carrying out nonlinear processing on the extracted features through the activation layer, namely, converting the extracted features from linearity into nonlinearity, compressing the nonlinearity features through the pooling layer to obtain compression features so as to reduce the complexity of subsequent processing, connecting the compression features output by the pooling layer through the full connection layer, namely, carrying out linear combination, and finally outputting the probability that the input image is a key frame according to the connected result. For each quadrant, the processor 104 may select one frame image with the highest probability of a key frame from the corresponding multi-frame images as the key frame image of the corresponding quadrant. The specific preset key frame identification network is not limited in this embodiment.
For example, in the embodiment of the present application, the umbilical line and the abdominal line of the pregnant woman may be used as markers, and the target object, i.e. the uterus, is divided into four different quadrants, namely, a first quadrant, a second quadrant, a third quadrant and a fourth quadrant, respectively. The processor 104 obtains 5 frame images corresponding to each quadrant, that is, multi-frame images, through the ultrasonic probe 101, and then, the processor 104 inputs each frame image in the 5 frame images corresponding to each quadrant in the four quadrants into a preset key frame recognition network, so as to output the key frame probability corresponding to each frame. Specifically, the 5-frame images corresponding to the first quadrant are respectively image 1, image 2, image 3, image 4 and image 5, and the processor 104 inputs these images into the preset key frame recognition network, so as to obtain a key frame probability corresponding to image 1 of 0.2, a key frame probability corresponding to image 2 of 0.4, a key frame probability corresponding to image 3 of 0.4, a key frame probability corresponding to image 4 of 0.6 and a key frame probability corresponding to image 5 of 0.8, so that image 5 is determined as the key frame image corresponding to the first quadrant.
Note that, in the embodiment of the present application, after the processor 104 obtains the multi-frame image corresponding to each quadrant through the ultrasound probe 101, the display 105 may display the multi-frame image.
In this embodiment of the present application, since the display 105 may display multiple images, after viewing the multiple images, the doctor may send a selection instruction for the multiple images to the processor 104 through the touch interface or a specific key, and the processor 104 receives the selection instruction for the multiple images and determines a key frame image from the multiple images according to the selection instruction.
In the embodiment of the present application, the target object is divided into four quadrants, namely, a first quadrant, a second quadrant, a third quadrant and a fourth quadrant, and the multi-frame image corresponding to each quadrant is specifically 10 frames of images. The display 105 may display 10 frames of images corresponding to each quadrant. Specifically, after displaying the 10 frames of images corresponding to the first quadrant, the doctor determines that the 3 rd frame of images includes the largest sheep pool corresponding to the first quadrant according to visual inspection, and then sends a selection instruction for selecting the 3 rd frame of images to the processor 104 through the touch interface, the processor 104 receives the selection instruction, and determines that the 3 rd frame of images in the 10 frames of images corresponding to the first quadrant is the key frame image corresponding to the first quadrant according to the selection instruction. Likewise, key frame images corresponding to other quadrants may also be determined.
It may be appreciated that in the embodiment of the present application, the processor 104 determines the keyframe image corresponding to each quadrant, where the keyframe image corresponding to each quadrant includes the largest amniotic fluid pool corresponding to the corresponding quadrant, and the specific method for determining the keyframe may be automatic, that is, performing amniotic fluid pool area segmentation, or manual, that is, subjective determination according to visual display, and the specific method may be determined according to the actual operating environment and measurement requirements.
S202, respectively positioning the position information of the maximum vertical radial line from each key frame image.
In this embodiment, after acquiring the keyframes corresponding to each quadrant, the processor 104 of the ultrasound imaging apparatus 10 may locate the position information of the maximum vertical radial line from each keyframe image, where the maximum vertical radial line does not generally pass through any organization structure.
Specifically, in the embodiment of the present application, the processor 104 locates the position information of the maximum vertical radial line from each key frame image, including: respectively acquiring a maximum amniotic fluid pool area from each key frame image; and respectively positioning the position information of the maximum vertical radial line from each maximum amniotic fluid pool area.
It will be appreciated that in the embodiment of the present application, each key frame image includes a maximum amniotic fluid pool area corresponding to a corresponding quadrant, and thus, the processor 104 may obtain the maximum amniotic fluid pool area corresponding to the corresponding quadrant from each key frame image. If in step S201, a method of determining a key frame image from a plurality of frames of images based on the amniotic fluid pool area segmentation is specifically adopted when the key frame image corresponding to each quadrant is acquired, that is, in step S201, each frame of image of the plurality of frames of images is segmented into the amniotic fluid pool area, and the key frame image is only one frame of image of the plurality of frames of images, that is, in step S201, the key frame image is segmented into the amniotic fluid pool area, so when the processor 104 executes step S202, the maximum amniotic fluid pool area in each key frame image can be obtained directly according to the segmentation result of step S201. Of course, if in step S201, a selection instruction is sent to the doctor to determine a key frame image, or a single frame image is directly determined as a key frame image, the processor 104 needs to divide the amniotic fluid pool area for each key frame image, so as to obtain a maximum amniotic fluid pool area corresponding to each key frame image.
Specifically, in the embodiment of the present application, the processor 104 obtains the maximum amniotic fluid pool area from each key frame image, including: and respectively carrying out amniotic fluid pool area segmentation on each key frame image according to a preset image segmentation algorithm to obtain a maximum amniotic fluid pool area.
Specifically, in the embodiment of the present application, the processor 104 obtains the maximum amniotic fluid pool area from each key frame image, including: and inputting each key frame image into a preset image segmentation network to segment the amniotic fluid pool area, so as to obtain the maximum amniotic fluid pool area.
In the embodiment of the present application, the details of the sheep pond area segmentation according to the preset image segmentation algorithm and the preset image segmentation network have been described in step S201, and are not described herein.
It should be noted that, in the embodiment of the present application, when the processor 104 locates the position information of the maximum vertical radial line, the maximum vertical radial line does not pass through any tissue structure, that is, the area through which the maximum vertical radial line passes does not include any anatomy of the fetus and umbilical cord. The processor 104 locates the location information of the largest vertical diameter line from each of the largest amniotic fluid cell areas, respectively, i.e., locates the two endpoints of the largest vertical diameter line from each of the largest amniotic fluid cell areas, respectively.
Fig. 5 is a schematic diagram of exemplary maximum vertical radial position information according to an embodiment of the present application. As shown in fig. 5, for the keyframe image corresponding to a quadrant of the plurality of quadrants, the processor 104 has determined its corresponding maximum amniotic cell area, i.e., the area included inside the white curve, wherein the endpoint a and the endpoint b are two points through the area that do not contain any fetal anatomy and the vertical distance of the umbilical cord, i.e., the endpoint a and the endpoint b are the location information of the maximum vertical diameter line, and the distance between the endpoint a and the endpoint b, i.e., the distance shown by the dashed line, is the length of the maximum vertical diameter line.
In the embodiment of the present application, the processor 104 locates the position information of the maximum vertical radial line from each maximum amniotic fluid pool area, which may be implemented in an automatic manner or according to receiving related instructions.
It will be appreciated that in embodiments of the present application, the display 105 may display each key frame image and may display a maximum amniotic fluid pool area, in particular, in the form of a marker line in each key frame image. Therefore, the doctor can directly select the two endpoints of the maximum vertical diameter line, namely the position information of the maximum vertical diameter line through touch clicking according to the marked maximum amniotic fluid pool area, and the processor 104 receives the related instruction, so that the position information of the maximum vertical diameter line is positioned according to the related instruction.
It will be appreciated that in the embodiment of the present application, the processor 104 may also use a pattern recognition and machine learning method to automatically locate the position information of the largest vertical radial line from each largest amniotic fluid pool area according to the characteristics of the amniotic fluid pool area and the specific vertical radial line.
S203, determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line.
In the embodiment of the present application, the processor 104 of the ultrasonic imaging apparatus 10 may determine the maximum vertical radial length according to the position information of each maximum vertical radial after locating the position information of the maximum vertical radial from each key frame image.
Specifically, in the embodiment of the present application, the position information of each maximum vertical radial line is two end points of each maximum vertical radial line, and the processor 104 may directly and automatically measure the distance between the two end points of each maximum vertical radial line, so as to obtain the length of each vertical radial line, as shown in fig. 5.
S204, summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object.
In the embodiment of the present application, the processor of the ultrasonic imaging apparatus 10 may sum the lengths of each of the maximum vertical radial lines to determine the amniotic fluid index of the target object after determining the lengths of the maximum vertical radial lines according to the position information of each of the maximum vertical radial lines, respectively.
Fig. 6 is a schematic view of an exemplary four quadrant maximum vertical radial provided in an embodiment of the present application. In the embodiment of the present application, the target object, i.e. the uterus, is divided into four quadrants, namely a first quadrant, a second quadrant, a third quadrant and a fourth quadrant. The processor 104 obtains the key frame image corresponding to the first quadrant as the first image, the key frame image corresponding to the second quadrant as the second image, the key frame image corresponding to the third quadrant as the third image, and the key frame image corresponding to the fourth quadrant as the fourth image, as shown in fig. 6, the processor 104 locates the position information of the first maximum vertical radial line from the first image, the position information of the second maximum vertical radial line from the second image, the position information of the third maximum vertical radial line from the third image, and the position information of the fourth maximum vertical radial line from the fourth image. The processor 104 determines the maximum vertical radial length L1 according to the position information of the first maximum vertical radial, determines the maximum vertical radial length L2 according to the position information of the second maximum vertical radial, determines the maximum vertical radial length L3 according to the position information of the third maximum vertical radial, determines the maximum vertical radial length L4 according to the position information of the fourth maximum vertical radial, and then sums L1, L2, L3 and L4 to obtain the amniotic fluid index of uterus. And a doctor can evaluate whether the pregnant woman is pregnant normally according to the amniotic fluid index.
The embodiment of the application provides a measuring method of amniotic fluid index, which comprises the steps of obtaining a key frame image corresponding to each quadrant in a target object, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a maximum amniotic fluid pool area corresponding to the corresponding quadrant; positioning the position information of the maximum vertical radial line from each key frame image respectively; determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line; and summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object. That is, according to the technical scheme provided by the embodiment of the application, the vertical radial line length of the maximum amniotic fluid pool area in the key frame image of each quadrant can be automatically measured, and the amniotic fluid indexes are obtained by summation, so that the efficiency and the accuracy of amniotic fluid index measurement are improved.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores an amniotic fluid index measurement program, and the amniotic fluid index measurement program can be executed by a processor to realize the amniotic fluid index measurement method. The computer readable storage medium may be a volatile Memory (RAM), such as Random-Access Memory (RAM); or a nonvolatile Memory (non-volatile Memory), such as a Read-Only Memory (ROM), a flash Memory (flash Memory), a Hard Disk (HDD) or a Solid State Drive (SSD); but may be a respective device, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc., comprising one or any combination of the above memories.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable signal processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable signal processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable signal processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable signal processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the present application.
Claims (19)
1. A method of measuring amniotic fluid index, the method comprising:
acquiring a key frame image corresponding to each quadrant in a target object, wherein the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a amniotic fluid pool area corresponding to the corresponding quadrant;
Positioning the position information of the maximum vertical radial line of the amniotic fluid pool area from each key frame image;
determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line;
summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index of the target object;
the obtaining the key frame image corresponding to each quadrant in the target object includes:
acquiring multi-frame images corresponding to each quadrant respectively;
and determining the key frame image from the multi-frame image according to a preset frame determination method.
2. The method of claim 1, wherein after the acquiring the multi-frame image corresponding to each quadrant, the method further comprises:
and displaying the multi-frame image.
3. The method of claim 2, wherein after the displaying the multi-frame image, the method further comprises:
receiving a selection instruction of the multi-frame image;
and determining the key frame image from the multi-frame images according to the selection instruction.
4. The method of claim 1, wherein determining the key frame image from the multi-frame image according to a preset frame determination method comprises:
According to a preset image segmentation algorithm, carrying out amniotic fluid pool region segmentation on the multi-frame image to obtain a first segmentation result;
determining the largest sheep pool frame image corresponding to each quadrant from the multi-frame images according to the first segmentation result;
and determining the maximum amniotic fluid pool frame image as the key frame image.
5. The method of claim 1, wherein determining the key frame image from the multi-frame image according to a preset frame determination method comprises:
inputting the multi-frame images into a preset image segmentation network to segment the sheep pool area, and obtaining a second segmentation result;
determining the maximum sheep pool frame image corresponding to each quadrant from the multi-frame images according to the second segmentation result;
and determining the maximum amniotic fluid pool frame image as the key frame image.
6. The method of claim 1, wherein determining the key frame image from the multi-frame image according to a preset frame determination method comprises:
inputting the multi-frame images into a preset key frame identification network to obtain the key frame probability corresponding to each frame of image in the multi-frame images;
Determining maximum key frame probability frame images corresponding to each quadrant respectively from the multi-frame images;
and determining the maximum key frame probability frame image as the key frame image.
7. The method of claim 1, wherein locating the position information of the largest vertical line from each of the key frame images comprises:
respectively acquiring the maximum amniotic fluid pool area from each key frame image;
and respectively positioning the position information of the maximum vertical radial line from each maximum amniotic fluid pool area.
8. The method of claim 7, wherein the separately obtaining the maximum amniotic fluid pool area from each of the key frame images comprises:
and respectively carrying out amniotic fluid pool area segmentation on each key frame image according to a preset image segmentation algorithm to obtain the maximum amniotic fluid pool area.
9. The method of claim 7, wherein the separately obtaining the maximum amniotic fluid pool area from each of the key frame images comprises:
and inputting each key frame image into a preset image segmentation network to segment the goat water pool area, and obtaining the maximum goat water pool area.
10. An ultrasound imaging apparatus, comprising:
an ultrasonic probe;
a transmission/reception selection switch;
a transmission/reception sequence controller which excites the ultrasonic probe to transmit ultrasonic waves to a target object through the transmission/reception selection switch and controls the ultrasonic probe to receive ultrasonic echoes returned from the target object;
a processor for performing the steps of:
acquiring key frame images corresponding to each quadrant in the target object through the ultrasonic probe; the target object is divided into a plurality of quadrants, and each key frame image respectively comprises a amniotic fluid pool area corresponding to the corresponding quadrant; positioning position information of the maximum vertical radial line position of the amniotic fluid pool area from each key frame image; determining the length of the maximum vertical radial line according to the position information of each maximum vertical radial line; summing the lengths of the maximum vertical radial lines to determine the amniotic fluid index corresponding to the target object; the obtaining the key frame image corresponding to each quadrant in the target object includes: acquiring multi-frame images corresponding to each quadrant respectively; determining the key frame image from the multi-frame image according to a preset frame determination method;
And the display is used for displaying each key frame image.
11. The ultrasonic imaging apparatus of claim 10, wherein,
the display is also used for displaying the multi-frame images.
12. The ultrasonic imaging apparatus of claim 11, wherein,
the processor is also used for receiving a selection instruction of the multi-frame image after the multi-frame image is displayed by the display; and determining the key frame image from the multi-frame images according to the selection instruction.
13. The ultrasonic imaging apparatus of claim 10, wherein,
the processor is specifically configured to segment the amniotic fluid pool area of the multi-frame image according to a preset image segmentation algorithm, so as to obtain a first segmentation result; determining the largest sheep pool frame image corresponding to each quadrant from the multi-frame images according to the first segmentation result; and determining the maximum amniotic fluid pool frame image as the key frame image.
14. The ultrasonic imaging apparatus of claim 10, wherein,
the processor is specifically configured to input each frame of image in the multi-frame images into a preset image segmentation network to segment a sheep pool area, so as to obtain a second segmentation result; determining the maximum sheep pool frame image corresponding to each quadrant from the multi-frame image sequence according to the second segmentation result; and determining the maximum amniotic fluid pool frame image as the key frame image.
15. The ultrasonic imaging apparatus of claim 10, wherein,
the processor is specifically configured to input the multi-frame images into a preset key frame identification network, and obtain a key frame probability corresponding to each frame of image in the multi-frame images; determining maximum key frame probability frame images corresponding to each quadrant respectively from the multi-frame images; and determining the maximum key frame probability frame image as the key frame image.
16. The ultrasonic imaging apparatus of claim 10, wherein,
the processor is specifically configured to obtain the maximum amniotic fluid pool area from each of the key frame images respectively; and respectively positioning the position information of the maximum vertical radial line from each maximum amniotic fluid pool area.
17. The ultrasound imaging apparatus of claim 16, wherein,
the processor is specifically configured to segment the amniotic fluid pool area of each key frame image according to a preset image segmentation algorithm, so as to obtain the maximum amniotic fluid pool area.
18. The ultrasound imaging apparatus of claim 16, wherein,
the processor is specifically configured to input the key frame image into a preset image segmentation network to segment a amniotic fluid pool area, and obtain the maximum amniotic fluid pool area.
19. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a amniotic fluid index measurement program executable by a processor to implement the method of measuring amniotic fluid index according to any one of claims 1 to 9.
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| US7041059B2 (en) * | 2002-08-02 | 2006-05-09 | Diagnostic Ultrasound Corporation | 3D ultrasound-based instrument for non-invasive measurement of amniotic fluid volume |
| WO2006026605A2 (en) * | 2002-06-07 | 2006-03-09 | Diagnostic Ultrasound Corporation | Systems and methods for quantification and classification of fluids in human cavities in ultrasound images |
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