Prenatal ultrasonic auxiliary screening method and system for congenital heart disease

Abstract

The invention relates to the technical field of ultrasonic-assisted screening, in particular to an antenatal ultrasonic-assisted screening method and system for congenital heart diseases. The method comprises the following steps: firstly, acquiring a frame image sequence of a four-cavity heart tangent image of a fetus, matching all suspected heart cavity areas among different frame images, and acquiring a matching sequence of all the areas; then, based on the diastole and systole laws of cardiac pulsations, evaluating the cardiac cavity confidence coefficient of each region matching sequence, so as to screen out all cardiac cavity matching sequences; the normal index of each cardiac cavity area in the cardiac cavity matching sequence is further analyzed and evaluated, and then abnormal frame images are screened out from all the frame images; and finally, reconstructing a four-cavity tangent plane diagram based on all abnormal frame diagrams. According to the method, the abnormal heart cavity in each frame of the four-cavity heart tangent diagram is analyzed and screened based on the characteristic that the heart beat causes the regular change of the heart cavity, and then the normal heart cavity and the abnormal heart cavity are distinguished for reconstruction, so that the condition that the reconstruction result cannot reflect the abnormal structure of the fetal heart is avoided, and the auxiliary screening effect of antenatal ultrasound is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasound-assisted screening, and in particular to a prenatal ultrasound-assisted screening method and system for congenital heart disease. Background Art

[0002] Congenital heart disease (CHD) refers to structural heart disease caused by formation disorders or abnormal development of the heart and large blood vessels during embryonic development. It is one of the common congenital malformations, so prenatal ultrasound screening is crucial. In prenatal ultrasound screening, the fetal four-chamber heart section is an important reference for evaluating congenital heart disease, which can help doctors evaluate whether the fetal heart structure is normal, thereby assisting doctors to take necessary intervention measures, reduce fertility risks, and protect the health of mothers and newborns.

[0003] However, due to the small size of the fetal heart, the angle and frequency of the ultrasound probe and other factors, the resolution or clarity of the four-chamber heart section image may be low, and a single-frame four-chamber heart section image cannot show the dynamic activities of the fetal heart. Therefore, it is usually necessary to use multiple frames of four-chamber heart section images for super-resolution reconstruction to improve the resolution and quality of the image, helping doctors to more clearly observe the structure and potential abnormalities of the fetal heart. However, in the super-resolution reconstruction process, the frame image when the heart beats normally may cover the frame image when the heart beats abnormally, resulting in the super-resolution reconstructed image being unable to reflect the actual abnormal structure of the fetal heart, thereby reducing the auxiliary screening effect of prenatal ultrasound. Summary of the invention

[0004] In order to solve the technical problem that the super-resolution reconstructed image in the prior art cannot reflect the real abnormal structure of the fetal heart, thereby resulting in poor prenatal ultrasound-assisted screening effect, the purpose of the present invention is to provide a prenatal ultrasound-assisted screening method and system for congenital heart disease. The technical solution adopted is as follows: The present invention provides a prenatal ultrasound-assisted screening method for congenital heart disease, the method comprising: Obtain a frame sequence of a four-chamber heart section image of a fetus in the abdomen of a pregnant woman and all suspected heart chamber regions in each frame; match all suspected heart chamber regions between different frames in the frame sequence, and use the suspected heart chamber regions as sequence elements to obtain all region matching sequences in the frame sequence, wherein the region matching sequence is consistent with the ordering method of the frame sequence; Based on the area change of the suspected cardiac chamber area, each regional matching sequence is divided into a suspected cardiac chamber diastolic feature sequence and a suspected cardiac chamber contraction feature sequence; in the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the similarity of the area of ​​the suspected cardiac chamber area in each feature sequence and the change of the inter-frame interval of the corresponding frame image, combined with the area difference of the suspected cardiac chamber area between different feature sequences, the cardiac chamber confidence coefficient corresponding to the regional matching sequence is obtained; According to the cardiac chamber confidence coefficient, all cardiac chamber matching sequences are screened out from all region matching sequences, and sequence elements in the cardiac chamber matching sequences are used as cardiac chamber regions; in any feature sequence of each cardiac chamber matching sequence, a normal index of each cardiac chamber region is obtained according to the area of ​​each cardiac chamber region and the frame interval between each cardiac chamber region and the corresponding frame images of the adjacent cardiac chamber regions; in the frame image sequence, abnormal frame images are screened out from all frame images according to the normal index; A reconstructed four-chamber heart view is obtained based on all abnormal frames to assist prenatal ultrasound screening.

[0005] Furthermore, the method for acquiring the suspected cardiac cavity region includes: Each frame of the four-chamber heart section image is binarized, and the binarized frame image is subjected to regional connectivity detection to obtain all connected domains in the background; the corresponding area of ​​each connected domain in the frame image is used as a suspected heart chamber area in the corresponding frame image.

[0006] Furthermore, the method for obtaining the region matching sequence includes: The corresponding image coordinate system is constructed with the center of each frame image as the origin, and the centroid coordinates of each suspected cardiac cavity area in each frame image are obtained; any frame image is taken as the target frame image, any suspected cardiac cavity area in the target frame image is taken as the target area, and the centroid coordinates of the target area are taken as the target coordinates; In each non-target frame image in the frame image sequence, the matching area of ​​the target area in the corresponding non-target frame image is obtained according to the difference between the centroid coordinates of each suspected cardiac cavity area and the target coordinates; the target area and its matching areas in all non-target frame images are sorted in the sorting order of the frame images to construct a region matching sequence.

[0007] Furthermore, the method for acquiring the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence includes: In each of the region matching sequences, the area of ​​each suspected cardiac cavity region is used as a sequence element to obtain an area change sequence corresponding to each of the region matching sequences, wherein the area change sequence is arranged in the same manner as the region matching sequence; Acquire all the maximum values ​​and all the minimum values ​​in the area change sequence, sort the suspected cardiac chamber regions corresponding to the maximum values ​​in the order of obtaining the maximum values ​​to construct a suspected cardiac chamber diastolic feature sequence, and sort the suspected cardiac chamber regions corresponding to the minimum values ​​in the order of obtaining the minimum values ​​to construct a suspected cardiac chamber diastolic feature sequence.

[0008] Furthermore, the method for obtaining the cardiac chamber confidence coefficient includes: In the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the area variance of the suspected cardiac chamber region in each feature sequence and the inter-frame interval of the corresponding frames of the adjacent suspected cardiac chamber regions, the pulsation regularity parameter of the suspected cardiac chamber region in the region matching sequence is obtained; The difference between the average area value of all the suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence and the average area value of all the suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as a reference weight for cardiac chamber discrimination; The cardiac chamber discrimination reference weight is used to weight the pulsation regularity parameter, and a normalized result of the weighted result is used as a cardiac chamber confidence coefficient corresponding to the regional matching sequence.

[0009] Furthermore, the method for obtaining the pulsation regularity parameters includes: The variance of the area of ​​all the suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence is used as a diastolic morphological fluctuation parameter; the variance of the area of ​​all the suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as a contraction morphological fluctuation parameter; the diastolic morphological fluctuation parameter and the contraction morphological fluctuation parameter are fused, and the negative correlation mapping result of the fusion result is used as a cardiac chamber morphological regularity parameter; The inter-frame interval between the frames of the suspected cardiac chamber region adjacent to each other in the suspected cardiac chamber diastolic feature sequence is taken as the suspected diastolic interval, and the difference accumulation value between all the adjacent suspected diastolic intervals is taken as the diastolic interval variation parameter; the inter-frame interval between the frames of the suspected cardiac chamber region adjacent to each other in the suspected cardiac chamber systolic feature sequence is taken as the suspected systolic interval, and the difference accumulation value between all the adjacent suspected systolic intervals is taken as the systolic interval variation parameter; the diastolic interval variation parameter and the systolic interval variation parameter are fused, and the negative correlation mapping result of the fusion result is taken as the beat interval regularity parameter; The cardiac chamber morphology regularity parameters and the beat interval regularity parameters are integrated to obtain the beat regularity parameters of the suspected cardiac chamber region in the region matching sequence.

[0010] Furthermore, the method for acquiring the cardiac chamber matching sequence includes: All the region matching sequences are sorted in descending order based on the cardiac chamber confidence coefficient, and the top four region matching sequences are used as cardiac chamber matching sequences.

[0011] Furthermore, the method for obtaining the normal index includes: The suspected cardiac chamber diastolic feature sequence of each cardiac chamber matching sequence is used as a target feature sequence, the average area of ​​all cardiac chamber regions in the target feature sequence is used as a reference area, and the average value of the inter-frame intervals of the frames to which adjacent cardiac chamber regions belong is used as a reference cardiac chamber beat cycle; In each target feature sequence, a negative correlation mapping result of the area sum value of each cardiac chamber region and the previous adjacent cardiac chamber region and the area difference between the two times of the reference area is used as the first normal pulsation coefficient of each cardiac chamber region in the target feature sequence; In each target feature sequence, a negative correlation mapping result of the inter-frame interval between each cardiac chamber region and the frame image to which the previous adjacent cardiac chamber region belongs and the period difference between the reference cardiac chamber beat period is used as the second normal beat coefficient of each cardiac chamber region in the target feature sequence; The first normal pulsation coefficient and the second normal pulsation coefficient are fused to obtain a normal index of a corresponding cardiac chamber region in a target feature sequence corresponding to the cardiac chamber matching sequence.

[0012] Furthermore, the method for obtaining the abnormal frame image includes: The cardiac chamber region whose normal index is less than a preset threshold is regarded as an abnormal cardiac chamber region, and the frame image including the abnormal cardiac chamber region is regarded as an abnormal frame image.

[0013] The present invention also proposes a prenatal ultrasound-assisted screening system for congenital heart disease, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the prenatal ultrasound-assisted screening method for congenital heart disease when executing the computer program.

[0014] The present invention has the following beneficial effects: The present invention obtains a frame sequence of a four-chamber heart section image of a fetus in the abdomen of a pregnant woman, and matches all suspected heart chamber areas between different frames in the frame sequence to obtain all region matching sequences, wherein each region matching sequence reflects the change of the same cardiac structure tissue, so as to prepare for subsequent analysis to screen out abnormal frames that do not conform to normal beating rules and to reconstruct high-quality and high-resolution four-chamber heart section images; then, based on the area change of the suspected heart chamber area, each region matching sequence is divided into a suspected heart chamber diastolic feature sequence and a suspected heart chamber contraction feature sequence, and then, according to the area similarity of the suspected heart chamber area in each feature sequence and the change of the frame interval between the corresponding frames, combined with the area difference of the suspected heart chamber area between different feature sequences, the heart chamber confidence coefficient of the corresponding region matching sequence is obtained, and the heart chamber confidence coefficient is obtained after excluding other Under the influence of interference from cardiac tissues such as non-cardiac chambers, the possibility that each regional matching sequence is a corresponding matching sequence between different frames of cardiac chambers is quantified, so as to facilitate the subsequent accurate positioning of cardiac chamber regions and analyze the inter-frame changes of cardiac chambers; further, all cardiac chamber matching sequences are screened out according to the cardiac chamber confidence coefficient, and then in any characteristic sequence of each cardiac chamber matching sequence, the normal index of each cardiac chamber region is obtained according to the area of ​​each cardiac chamber region and the inter-frame interval between each cardiac chamber region and the corresponding frame of the adjacent cardiac chamber region; the normal index evaluates the possibility that each cardiac chamber region has a normal beating function, and prepares for the subsequent screening of abnormal frames to reconstruct high-resolution and high-quality four-chamber heart sections; and then the abnormal frames are screened out according to the normal index; and finally, the reconstructed four-chamber heart sections for auxiliary prenatal ultrasound screening are obtained based on all abnormal frames. The present invention is based on the characteristics of regular changes in cardiac chambers caused by cardiac pulsation, analyzes and screens abnormal cardiac chambers in each frame of four-chamber heart sections, and then distinguishes normal cardiac chambers from abnormal cardiac chambers with super-resolution reconstruction, avoiding the situation where the reconstruction results cannot reflect the real abnormal structure of the fetal heart, and improving the auxiliary screening effect of prenatal ultrasound. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flow chart of a method for prenatal ultrasound-assisted screening of congenital heart disease provided by one embodiment of the present invention; Figure 2 A flow chart of a method for obtaining a cardiac chamber confidence coefficient provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a prenatal ultrasound-assisted screening method and system for congenital heart disease proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The specific scheme of the prenatal ultrasound-assisted screening method and system for congenital heart disease provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flow chart of a method for prenatal ultrasound-assisted screening of congenital heart disease provided by an embodiment of the present invention, specifically comprising: Step S1, obtaining a frame sequence of a four-chamber heart section image of a fetus in the pregnant woman's abdomen and all suspected heart chamber areas in each frame; matching all suspected heart chamber areas between different frames in the frame sequence, and using the suspected heart chamber areas as sequence elements to obtain all region matching sequences in the frame sequence, wherein the region matching sequence is consistent with the sorting method of the frame sequence.

[0021] In one embodiment of the present invention, a frame sequence of a four-chamber heart section image of a fetus in a pregnant woman's abdomen is first obtained, and then combined with the normal beating condition of the fetal heart, abnormal frames that do not conform to the normal beating law are analyzed and screened out, thereby reconstructing a high-quality and high-resolution four-chamber heart section image, and assisting relevant medical personnel in assessing the heart structure and preparing for screening for congenital heart disease; The specific process of obtaining the frame image sequence is as follows: relevant medical personnel guide and assist the pregnant woman to be screened to lie on her back on the examination bed. After completing the preparations before the ultrasound examination, the medical personnel hold the ultrasound probe and gently move it to scan the pregnant woman's abdomen, looking for the best scanning position to clearly observe the fetal heart in the abdomen. Then, multiple consecutive frames of four-chamber heart sections of the fetal heart are collected at the scanning position. All four-chamber heart sections are sorted based on the order of collection to construct a frame image sequence to ensure that the heart beats as the frame images change, thereby ensuring the effectiveness of subsequent analysis.

[0022] It should be noted that obtaining a four-chamber heart section image is an existing technology well known to those skilled in the art and will not be described in detail here; the four-chamber heart section image is already a grayscale image, so in subsequent processing, no further grayscale processing is required. If it is a color ultrasound, the implementer can also perform certain preprocessing before analysis.

[0023] Considering that normal heart beats will cause regular changes in the volume of the heart chambers, analyzing the changes in the heart chamber areas in the four-chamber heart section image can help evaluate whether the fetal heart structure and function are abnormal. Therefore, in one embodiment of the present invention, all suspected heart chamber areas in each frame image, i.e., each four-chamber heart section image, are further obtained to prepare for subsequent analysis of heart chamber changes.

[0024] Preferably, in one embodiment of the present invention, considering that the cardiac cavity region is usually a low-echo region, the grayscale value in the four-chamber heart section image is low; and considering that binarization can help distinguish the cardiac cavity and regional cardiac tissue, the background region corresponding to the low grayscale value region can be used as a suspected cardiac cavity region; therefore, the method for obtaining the suspected cardiac cavity region includes: Each frame of the four-chamber heart section image is binarized, and the binarized frame image is subjected to regional connectivity detection to obtain all connected domains in the background; the corresponding area of ​​each connected domain in the frame image is used as a suspected heart chamber area in the corresponding frame image.

[0025] It should be noted that binarization, obtaining the background in the binarized image, and region connectivity detection are all existing technologies well known to those skilled in the art and will not be described in detail.

[0026] Considering that even if the fetal heart beat will cause the morphology of each heart chamber to change, the position distribution of the same heart chamber in multiple frames of four-chamber heart sections acquired continuously at the same scanning position should be highly similar, and will not produce a large deviation due to changes in the patient's vital signs such as breathing and blood flow during the ultrasound examination or errors in the ultrasound equipment. In addition, the position of the fetus in the pregnant woman's abdomen will not change significantly during the short scanning period, that is, it will not cause a large deviation in the position distribution of the heart chamber. Therefore, different suspected heart chamber areas in the frame image sequence can be matched based on the position characteristics of the suspected heart chamber areas, so as to facilitate the subsequent screening of the matching sequence of the corresponding heart chamber areas, and then combine the heart beat characteristics to evaluate its abnormality.

[0027] Preferably, in one embodiment of the present invention, considering that cardiac pulsation may cause the volume of the cardiac chamber to increase or decrease from time to time, that is, the shape of the corresponding area of ​​each cardiac chamber in the four-chamber heart section image will change, but its geometric center will not be significantly shifted; based on this, the method for obtaining the regional matching sequence includes: The corresponding image coordinate system is constructed with the center of each frame image as the origin, and the centroid coordinates of each suspected cardiac cavity area in each frame image are obtained; any frame image is taken as the target frame image, any suspected cardiac cavity area in the target frame image is taken as the target area, and the centroid coordinates of the target area are taken as the target coordinates; In each non-target frame in the frame sequence, the matching area of ​​the target area in the corresponding non-target frame is obtained according to the difference between the centroid coordinates of each suspected cardiac cavity area and the target coordinates; the target area and its matching areas in all non-target frames are sorted according to the sorting order of the frames to construct a region matching sequence.

[0028] As an example, in each non-target frame image in the frame image sequence, the suspected cardiac cavity region including the target coordinates is specifically used as the matching region of the target region in the corresponding non-target frame image; then the target region and its matching region in each non-target frame image are used as a series of regions to be matched between different frames in the frame image sequence, and then all the regions to be matched are sorted according to the sorting order of the frames in the frame image sequence, and the regions to be matched are used as sequence elements to construct a region matching sequence; By changing the target area, all region matching sequences between different frames in the frame sequence can be obtained, wherein each region matching sequence can be regarded as a change sequence of the same cardiac structure and tissue, such as the same heart chamber, between different frames, that is, each region matching sequence reflects the change of the same cardiac structure and tissue.

[0029] In another embodiment of the present invention, in each non-target frame image in the frame image sequence, the centroid coordinates having the smallest Euclidean distance to the target coordinates correspond to the suspected cardiac cavity region as the matching region of the target region in the corresponding non-target frame image.

[0030] It should be noted that each target region corresponds to only one matching region in each non-target frame image, that is, each sequence element in the region matching sequence is a matching region in each frame image.

[0031] It should be noted that the construction of the image coordinate system and the acquisition of the centroid are both existing technologies and will not be described in detail here.

[0032] In another embodiment of the present invention, the implementer may also directly use the SIFT algorithm to perform feature matching on the frame image sequence, thereby obtaining all region matching sequences, which is already a prior art and will not be described in detail here.

[0033] Step S2, based on the area change of the suspected cardiac chamber area, divide each regional matching sequence into a suspected cardiac chamber diastolic feature sequence and a suspected cardiac chamber contraction feature sequence; in the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the similarity of the area of ​​the suspected cardiac chamber area in each feature sequence and the change of the inter-frame interval of the corresponding frame image, combined with the area difference of the suspected cardiac chamber area between different feature sequences, obtain the cardiac chamber confidence coefficient of the corresponding regional matching sequence.

[0034] Considering that the beating characteristics of the heart will cause it to perform alternating contraction and relaxation movements, the shape and area of ​​each heart chamber will also change alternately with the heart beating, but the shape and area of ​​other low-echo tissues except the heart chamber will usually remain unchanged; based on this feature, the possibility of the regional matching sequence being the corresponding matching sequence of the heart chamber can be evaluated, which is convenient for subsequent screening of the heart chamber area; therefore, the embodiment of the present invention first divides each regional matching sequence into a suspected heart chamber diastolic feature sequence and a suspected heart chamber contraction feature sequence based on the area change of the suspected heart chamber area, in preparation for the subsequent analysis of the heart chamber confidence coefficient of each regional matching sequence.

[0035] Preferably, in one embodiment of the present invention, considering that the area of ​​the cardiac cavity changes alternately with the diastole or contraction of the heart, and during diastole, the area of ​​the cardiac cavity tends to be maximum, while during contraction, the area of ​​the cardiac cavity tends to be minimum; based on this, the method for acquiring the suspected cardiac cavity diastole feature sequence and the suspected cardiac cavity contraction feature sequence includes: In each region matching sequence, the area of ​​each suspected cardiac cavity region is used as a sequence element to obtain an area change sequence corresponding to each region matching sequence, and the area change sequence is sorted in the same manner as the region matching sequence; All the maximum values ​​and all the minimum values ​​in the area change sequence are obtained, and the suspected cardiac chamber areas corresponding to the maximum values ​​are sorted in the order of obtaining the maximum values ​​to construct a suspected cardiac chamber diastolic feature sequence; the suspected cardiac chamber areas corresponding to the minimum values ​​are sorted in the order of obtaining the minimum values ​​to construct a suspected cardiac chamber diastolic feature sequence.

[0036] It should be noted that the method for obtaining the maximum and minimum values ​​and the construction of the sequence are both existing technologies and will not be described in detail.

[0037] Considering that the cardiac chamber should have certain regular change characteristics each time with the diastole or contraction of the heart, that is, the time interval between two adjacent diastole or two adjacent contractions should be similar, and the degree of diastole or contraction each time should be similar, it is indirectly explained that the area of ​​the cardiac chamber after each diastole or contraction should also be similar; if in the suspected cardiac chamber diastole feature sequence or the suspected cardiac chamber contraction feature sequence, the area of ​​the suspected cardiac chamber region is relatively similar and the inter-frame interval change of the frame image also has certain regularity, it means that the possibility of the region matching sequence being the cardiac chamber corresponding matching sequence is greater, and the corresponding cardiac chamber confidence coefficient is also greater; At the same time, considering that the shape or area of ​​non-cardiac tissues does not change much, the corresponding suspected cardiac chamber diastolic feature sequence or suspected cardiac chamber contraction feature sequence may also have the regular change characteristics described above. However, there are certain area differences when the cardiac chamber contracts and relaxes. Based on this, the area differences of the suspected cardiac chamber areas between different feature sequences can be further combined to accurately obtain the cardiac chamber confidence coefficient of the corresponding area matching sequence.

[0038] The cardiac chamber confidence coefficient quantifies the possibility that the matching sequence of each region corresponds to the matching sequence of the cardiac chamber between different frames by comprehensively analyzing the difference characteristics and regular change characteristics of the cardiac chamber during diastole and contraction, while excluding the interference of other non-cardiac tissues such as cardiac chambers. This facilitates the subsequent precise positioning of the cardiac chamber area and the analysis of the inter-frame changes of the cardiac chamber, thereby assisting in screening.

[0039] Preferably, in one embodiment of the present invention, the method for obtaining the cardiac chamber confidence coefficient includes: See also Figure 2 , which shows a flow chart of a method for obtaining a cardiac chamber confidence coefficient provided by an embodiment of the present invention, specifically comprising: Step S201, in the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the area variance of the suspected cardiac chamber region in each feature sequence and the frame interval between the corresponding frames of adjacent suspected cardiac chamber regions, the pulsation regularity parameters of the suspected cardiac chamber region in the corresponding region matching sequence are obtained.

[0040] Considering that the variance can reflect the fluctuation of the data and can also help evaluate the similar features of the data to a certain extent, the area similarity of the suspected cardiac chamber area can be evaluated based on the area variance; considering that in each feature sequence, the inter-frame interval between the frames belonging to adjacent suspected cardiac chamber areas reflects the diastolic interval or systolic interval of the suspected cardiac chamber area, if the interval difference of all diastolic intervals or systolic intervals is smaller, it means that the diastolic or systolic is more regular, the pulsation of the suspected cardiac chamber area is more regular, and the subsequent corresponding cardiac chamber confidence coefficient is also larger; based on this, the pulsation regularity parameters of the suspected cardiac chamber area in each area matching sequence can be obtained.

[0041] It should be noted that the characteristic sequence refers to a suspected cardiac chamber diastolic characteristic sequence and a suspected cardiac chamber contractile characteristic sequence. The characteristic sequences in the following text are also referred to in the same way and will not be repeated here.

[0042] In a preferred embodiment of the present invention, the method for obtaining the pulsation regularity parameters includes: The variance of the area of ​​all suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence is used as the diastolic morphological fluctuation parameter; the variance of the area of ​​all suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as the contraction morphological fluctuation parameter; the diastolic morphological fluctuation parameter and the contraction morphological fluctuation parameter are fused, and the negative correlation mapping result of the fusion result is used as the cardiac chamber morphological regularity parameter; The interframe interval between the frames of the adjacent suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence is taken as the suspected diastolic interval, and the difference accumulation value between all adjacent suspected diastolic intervals is taken as the diastolic interval variation parameter; the interframe interval between the frames of the adjacent suspected cardiac chamber regions in the suspected cardiac chamber systolic feature sequence is taken as the suspected systolic interval, and the difference accumulation value between all adjacent suspected systolic intervals is taken as the systolic interval variation parameter; the diastolic interval variation parameter and the systolic interval variation parameter are fused, and the negative correlation mapping result of the fusion result is taken as the beat interval regularity parameter; The cardiac chamber morphology regularity parameters and the beat interval regularity parameters are integrated to obtain the beat regularity parameters of the suspected cardiac chamber region in the corresponding region matching sequence.

[0043] As an example, taking any region matching sequence as an example, the calculation formula of the pulsation regularity parameter is: ; Wherein, Q is the pulsation regularity parameter of the suspected cardiac cavity region in the region matching sequence; It is an exponential function with the natural constant e as the base; is the serial number of the suspected cardiac chamber diastolic feature sequence of the regional matching sequence; is the serial number of the suspected cardiac chamber contraction feature sequence of the regional matching sequence; is the variance of the area of ​​all suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence, and is also the diastolic morphological fluctuation parameter; is the variance of the area of ​​all suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence, and is also the contraction morphology fluctuation parameter; is the parameter of cardiac cavity morphology; It is the accumulated value of the differences between all adjacent suspected diastolic intervals, and is also the diastolic interval variation parameter; It is the accumulated value of the differences between all adjacent suspected contraction intervals, and is also the contraction interval variation parameter; is the beat interval regularity parameter; It is a very small positive parameter. In this example, it is set to 0.001 to prevent the denominator from being 0. The implementer can also define it by themselves.

[0044] In the above formula, the diastolic morphological fluctuation parameters and the systolic morphological fluctuation parameters are added and fused. The smaller the variance is, the more similar the areas in each feature sequence are. The negative correlation of the sum is mapped to the exponential function to adjust the logic and normalize it, so that the cardiac chamber morphological regularity parameters are larger; then the diastolic interval variation parameters and the systolic interval variation parameters are multiplied and combined, so that the smaller the product is, the more similar the intervals between adjacent frames in each feature sequence are, and then the product is added with a very small positive parameter and the inverse operation is performed to adjust the logic, so that the beat interval regularity parameters are larger; finally, the cardiac chamber morphological regularity parameters and the beat interval regularity parameters are multiplied and fused to obtain the beat regularity parameters.

[0045] In other examples, implementers may also adopt other methods such as weighted summation or other negative correlation mapping methods, which are commonly used technical methods and will not be described in detail here.

[0046] Step S202: The difference between the mean area value of all suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence and the mean area value of all suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as a reference weight for cardiac chamber discrimination.

[0047] It should be noted that if the area of ​​the suspected cardiac chamber region in the suspected cardiac chamber diastolic feature sequence is the maximum value in the area change sequence corresponding to the regional matching sequence, then the corresponding area mean will always be greater than or equal to the area mean of all suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence, that is, the cardiac chamber discrimination reference weight should always be greater than or equal to 0. The larger the cardiac chamber discrimination reference weight, the more it has the characteristics of alternating changes in cardiac contraction and diastole, and the greater the possibility that the corresponding regional matching sequences of the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence are the corresponding matching sequences of the cardiac chambers.

[0048] Step S203: weighting the beat regularity parameters using the cardiac chamber discrimination reference weights, and taking the normalized weighted results as the cardiac chamber confidence coefficients of the corresponding region matching sequence.

[0049] As an example, the cardiac chamber discrimination reference weight is multiplied by the pulsation regularity parameter for weighted combination, and then the product is linearly normalized, and the normalized result is used as the cardiac chamber confidence coefficient of the corresponding regional matching sequence; in other examples, the implementer may also use other normalization methods, which are not described here.

[0050] Step S3, based on the cardiac chamber confidence coefficient, all cardiac chamber matching sequences are screened out from all region matching sequences, and sequence elements in the cardiac chamber matching sequences are used as cardiac chamber regions; in any feature sequence of each cardiac chamber matching sequence, the normal index of each cardiac chamber region is obtained based on the area of ​​each cardiac chamber region and the inter-frame interval between each cardiac chamber region and the corresponding frame images of the adjacent cardiac chamber regions; in the frame image sequence, abnormal frame images are screened out from all frame images based on the normal index.

[0051] After obtaining the cardiac chamber confidence coefficient of each regional matching sequence, all cardiac chamber matching sequences can be further screened out from all regional matching sequences based on the cardiac chamber confidence coefficient, so that the sequence elements in the cardiac chamber matching sequence can be used as cardiac chamber regions, and then based on the four cardiac chamber matching sequences, the four cardiac chamber regions in each frame of the four-chamber heart section image can be obtained by corresponding annotation.

[0052] Preferably, in one embodiment of the present invention, considering that the heart mainly includes four chambers, namely the left atrium, the right atrium, the left ventricle and the right ventricle, the four regional matching sequences with the largest cardiac chamber confidence coefficients are more likely to be the cardiac chamber corresponding matching sequences; therefore, the method for obtaining the cardiac chamber matching sequence includes: sorting all regional matching sequences in descending order based on the cardiac chamber confidence coefficients, and taking the top four regional matching sequences as the cardiac chamber matching sequences.

[0053] Considering that congenital heart disease is caused by structural defects or malformations of the heart, the contraction and relaxation of the heart may be affected, and occasionally incomplete or inefficient contraction and relaxation may occur. In this case, the area of ​​the central cavity region in the four-chamber heart section image may not be able to expand to the maximum or contract to the minimum; and due to structural problems, the contraction and relaxation of the heart may be delayed or abnormally affected, resulting in irregular timing of the diastole and systole periods; based on this, the embodiment of the present invention can obtain the normal index of each heart chamber area in any feature sequence of each heart chamber matching sequence; the normal index evaluates the possibility of each heart chamber area having normal beating function, and prepares for the subsequent screening of abnormal frames to reconstruct high-resolution and high-quality four-chamber heart sections.

[0054] Preferably, in one embodiment of the present invention, considering that both the diastole and the contraction of the cardiac chamber have regularity, in all the diastole or contraction processes, if the cardiac chamber area corresponding to any diastole or contraction deviates from its average level, it means that it deviates from the original regularity, and the possibility of abnormality is higher; similarly, if the interval corresponding to adjacent diastole or adjacent contraction deviates from the average level, it also means that it deviates from the original regularity, and the possibility of abnormality is higher; based on this, the method for obtaining the normal index includes: The suspected cardiac chamber diastolic feature sequence of each cardiac chamber matching sequence is used as the target feature sequence, the average area of ​​all cardiac chamber regions in the target feature sequence is used as the reference area, and the average value of the inter-frame intervals of the frames to which the adjacent cardiac chamber regions belong is used as the reference cardiac chamber beat cycle; In each target feature sequence, a negative correlation mapping result of the area difference between each cardiac chamber region and the area sum value of the previous adjacent cardiac chamber region and twice the reference area is used as the first normal beat coefficient of each cardiac chamber region in the target feature sequence; In each target feature sequence, the negative correlation mapping result of the inter-frame interval between each cardiac chamber region and the frame image to which the previous adjacent cardiac chamber region belongs and the cycle difference between the reference cardiac chamber beat cycle is used as the second beat normal coefficient of each cardiac chamber region in the target feature sequence; The first normal pulsation coefficient and the second normal pulsation coefficient are fused to obtain a normal index of a corresponding cardiac chamber region in a target feature sequence of a corresponding cardiac chamber matching sequence.

[0055] It should be noted that in other embodiments of the present invention, the implementer may also use the suspected cardiac chamber contraction feature sequence of the cardiac chamber matching sequence as the target feature sequence to analyze the normal index of the cardiac chamber area; or the normal indexes obtained by the two methods may be weightedly fused to obtain the final normal index. The implementer may choose according to actual needs.

[0056] As an example, the normal index is calculated as: ; Where x is the serial number of the central cavity region of the target feature sequence; is the normal index of the xth cardiac chamber region in the target feature sequence; It is an exponential function with the natural constant e as the base; is the area of ​​the xth heart cavity region in the target feature sequence; is the area of ​​the x-1th cardiac cavity region in the target feature sequence; is the mean area of ​​the central cavity region of the target feature sequence, which is also the reference area; is the inter-frame interval between the frames of the x-th cardiac cavity region and the x-1-th cardiac cavity region in the target feature sequence; is the mean value of the inter-frame interval of the frames of the adjacent cardiac chamber regions in the target feature sequence; It is a very small positive parameter. In this example, it is set to 0.001 to prevent the denominator from being 0. The implementer can also define it by themselves.

[0057] In the calculation formula of the normal index, the absolute value of the difference is specifically used to evaluate the area difference. The smaller the absolute value of the difference, the closer the area of ​​each cardiac chamber region is to the area of ​​other cardiac chamber regions during diastole, that is, the closer it is to the reference area. The negative correlation of the area difference is mapped to the exponential function to adjust the logic and normalize it, so that the normal coefficient of the first beat is larger; then the inter-frame interval of each cardiac chamber region and the frame image to which the previous adjacent cardiac chamber region belongs is regarded as a diastolic interval, and the absolute value of the difference is used to evaluate the difference between it and other diastolic intervals, that is, the reference cardiac chamber beat cycle, so that the smaller the absolute value of the difference, the closer the diastolic interval is to other diastolic intervals, and then the absolute value of the difference is added to the extremely small positive parameter and the inverse operation is performed to adjust the logic, so that the normal coefficient of the second beat is larger; finally, the normal coefficient of the first beat and the normal coefficient of the second beat are multiplied and fused to obtain the normal index.

[0058] It should be noted that the first cardiac chamber region in the suspected cardiac chamber diastolic feature sequence has no previous adjacent cardiac chamber region. In this example, the last cardiac chamber region can be regarded as the previous adjacent cardiac chamber region of the first cardiac chamber region, or it can be excluded from analysis and does not participate in subsequent reconstruction.

[0059] In other examples, implementers may also directly utilize the negative correlation mapping results of the area difference between each cardiac chamber region and the reference area to evaluate the normal coefficient of the first beat; other methods such as weighted summation or other negative correlation mapping methods may also be used, which are all commonly used technical methods and will not be elaborated here.

[0060] After obtaining the normal index of each cardiac chamber area, we can further know whether each cardiac chamber area in the frame image corresponding to each four-chamber heart section image in the frame image sequence has normal beating characteristics, and then we can filter out abnormal frames from all frames according to the normal index to prepare for subsequent reconstruction.

[0061] Preferably, in one embodiment of the present invention, a cardiac chamber area whose normal index is less than a preset threshold is regarded as an abnormal cardiac chamber area, and a frame image containing the abnormal cardiac chamber area is regarded as an abnormal frame image; in this example, the preset threshold is specifically set to 0.7, and the implementer can also define it by himself; when any cardiac chamber area in any frame image is an abnormal cardiac chamber area, the frame image is regarded as an abnormal frame image, and the abnormal frame image reflects the abnormal beating characteristics of the heart, which can help analyze and evaluate whether there are defects and abnormalities in the heart structure.

[0062] Step S4, obtaining a reconstructed four-chamber heart section image for assisting prenatal ultrasound screening based on all abnormal frame images.

[0063] In one embodiment of the present invention, after all abnormal frames are acquired, super-resolution reconstruction can be further performed based on all abnormal frames to obtain a high-resolution and high-quality reconstructed four-chamber heart section image that can assist in prenatal ultrasound screening; the implementer can also synchronously perform super-resolution reconstruction on the remaining normal frames in the frame sequence except for the abnormal frames for reference by relevant medical personnel to assist them in prenatal screening for congenital heart disease.

[0064] It should be noted that super-resolution reconstruction is an existing technology well known to those skilled in the art and will not be described in detail here.

[0065] The present invention also proposes a prenatal ultrasound-assisted screening system for congenital heart disease, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a prenatal ultrasound-assisted screening method for congenital heart disease are implemented.

[0066] In summary, the present invention first obtains a frame sequence of a four-chamber heart section image of the fetus, and matches all suspected heart chamber areas between different frames to obtain all regional matching sequences; then, based on the relaxation and contraction rules during heart beat, analyzes and evaluates the heart chamber confidence coefficient of each regional matching sequence, thereby screening out all heart chamber matching sequences from all regional matching sequences; further analyzes and evaluates the normal index of each heart chamber area in the heart chamber matching sequence, and then screens out abnormal frames from all frames; finally, based on all abnormal frames, obtains a reconstructed four-chamber heart section image for auxiliary prenatal ultrasound screening. Based on the feature that the heart chamber has regular changes due to heart beat, the present invention analyzes and screens the abnormal heart chambers in each frame of the four-chamber heart section image, and then distinguishes between normal heart chambers and abnormal heart chambers to reconstruct with super-resolution, thereby avoiding the situation where the reconstruction result cannot reflect the true abnormal structure of the fetal heart, and improves the auxiliary screening effect of prenatal ultrasound.

[0067] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0068] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A prenatal ultrasound-assisted screening method for congenital heart disease, characterized in that: The method comprises: Obtain a frame sequence of a four-chamber heart section image of a fetus in the abdomen of a pregnant woman and all suspected heart chamber regions in each frame; match all suspected heart chamber regions between different frames in the frame sequence, and use the suspected heart chamber regions as sequence elements to obtain all region matching sequences in the frame sequence, wherein the region matching sequence is consistent with the ordering method of the frame sequence; Based on the area change of the suspected cardiac chamber area, each regional matching sequence is divided into a suspected cardiac chamber diastolic feature sequence and a suspected cardiac chamber contraction feature sequence; in the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the similarity of the area of ​​the suspected cardiac chamber area in each feature sequence and the change of the inter-frame interval of the corresponding frame image, combined with the area difference of the suspected cardiac chamber area between different feature sequences, the cardiac chamber confidence coefficient corresponding to the regional matching sequence is obtained; According to the cardiac chamber confidence coefficient, all cardiac chamber matching sequences are screened out from all region matching sequences, and sequence elements in the cardiac chamber matching sequences are used as cardiac chamber regions; in any feature sequence of each cardiac chamber matching sequence, a normal index of each cardiac chamber region is obtained according to the area of ​​each cardiac chamber region and the frame interval between each cardiac chamber region and the corresponding frame images of the adjacent cardiac chamber regions; in the frame image sequence, abnormal frame images are screened out from all frame images according to the normal index; A reconstructed four-chamber heart view is obtained based on all abnormal frames to assist prenatal ultrasound screening.

2. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for acquiring the suspected cardiac cavity region comprises: Each frame of the four-chamber heart section image is binarized, and the binarized frame image is subjected to regional connectivity detection to obtain all connected domains in the background; the corresponding area of ​​each connected domain in the frame image is used as a suspected heart chamber area in the corresponding frame image.

3. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for obtaining the region matching sequence includes: The corresponding image coordinate system is constructed with the center of each frame image as the origin, and the centroid coordinates of each suspected cardiac cavity area in each frame image are obtained; any frame image is taken as the target frame image, any suspected cardiac cavity area in the target frame image is taken as the target area, and the centroid coordinates of the target area are taken as the target coordinates; In each non-target frame image in the frame image sequence, the matching area of ​​the target area in the corresponding non-target frame image is obtained according to the difference between the centroid coordinates of each suspected cardiac cavity area and the target coordinates; the target area and its matching areas in all non-target frame images are sorted in the sorting order of the frame images to construct a region matching sequence.

4. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for acquiring the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence comprises: In each of the region matching sequences, the area of ​​each suspected cardiac cavity region is used as a sequence element to obtain an area change sequence corresponding to each of the region matching sequences, wherein the area change sequence is arranged in the same manner as the region matching sequence; Acquire all the maximum values ​​and all the minimum values ​​in the area change sequence, sort the suspected cardiac chamber regions corresponding to the maximum values ​​in the order of obtaining the maximum values ​​to construct a suspected cardiac chamber diastolic feature sequence, and sort the suspected cardiac chamber regions corresponding to the minimum values ​​in the order of obtaining the minimum values ​​to construct a suspected cardiac chamber diastolic feature sequence.

5. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for obtaining the cardiac chamber confidence coefficient includes: In the suspected cardiac chamber diastolic feature sequence and the suspected cardiac chamber contraction feature sequence, according to the area variance of the suspected cardiac chamber region in each feature sequence and the inter-frame interval of the corresponding frames of the adjacent suspected cardiac chamber regions, the pulsation regularity parameter of the suspected cardiac chamber region in the region matching sequence is obtained; The difference between the average area value of all the suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence and the average area value of all the suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as a reference weight for cardiac chamber discrimination; The cardiac chamber discrimination reference weight is used to weight the pulsation regularity parameter, and a normalized result of the weighted result is used as a cardiac chamber confidence coefficient corresponding to the regional matching sequence.

6. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 5, characterized in that: The method for obtaining the pulsation regularity parameters includes: The variance of the area of ​​all the suspected cardiac chamber regions in the suspected cardiac chamber diastolic feature sequence is used as a diastolic morphological fluctuation parameter; the variance of the area of ​​all the suspected cardiac chamber regions in the suspected cardiac chamber contraction feature sequence is used as a contraction morphological fluctuation parameter; the diastolic morphological fluctuation parameter and the contraction morphological fluctuation parameter are fused, and the negative correlation mapping result of the fusion result is used as a cardiac chamber morphological regularity parameter; The inter-frame interval between the frames of the suspected cardiac chamber region adjacent to each other in the suspected cardiac chamber diastolic feature sequence is taken as the suspected diastolic interval, and the difference accumulation value between all the adjacent suspected diastolic intervals is taken as the diastolic interval variation parameter; the inter-frame interval between the frames of the suspected cardiac chamber region adjacent to each other in the suspected cardiac chamber systolic feature sequence is taken as the suspected systolic interval, and the difference accumulation value between all the adjacent suspected systolic intervals is taken as the systolic interval variation parameter; the diastolic interval variation parameter and the systolic interval variation parameter are fused, and the negative correlation mapping result of the fusion result is taken as the beat interval regularity parameter; The cardiac chamber morphology regularity parameters and the beat interval regularity parameters are integrated to obtain the beat regularity parameters of the suspected cardiac chamber region in the region matching sequence.

7. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for acquiring the cardiac chamber matching sequence comprises: All the region matching sequences are sorted in descending order based on the cardiac chamber confidence coefficient, and the top four region matching sequences are used as cardiac chamber matching sequences.

8. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for obtaining the normal index includes: The suspected cardiac chamber diastolic feature sequence of each cardiac chamber matching sequence is used as a target feature sequence, the average area of ​​all cardiac chamber regions in the target feature sequence is used as a reference area, and the average value of the inter-frame intervals of the frames to which adjacent cardiac chamber regions belong is used as a reference cardiac chamber beat cycle; In each target feature sequence, a negative correlation mapping result of the area sum value of each cardiac chamber region and the previous adjacent cardiac chamber region and the area difference between the two times of the reference area is used as the first normal pulsation coefficient of each cardiac chamber region in the target feature sequence; In each target feature sequence, a negative correlation mapping result of the inter-frame interval between each cardiac chamber region and the frame image to which the previous adjacent cardiac chamber region belongs and the period difference between the reference cardiac chamber beat period is used as the second normal beat coefficient of each cardiac chamber region in the target feature sequence; The first normal pulsation coefficient and the second normal pulsation coefficient are fused to obtain a normal index of a corresponding cardiac chamber region in a target feature sequence corresponding to the cardiac chamber matching sequence.

9. The method for prenatal ultrasound-assisted screening of congenital heart disease according to claim 1, characterized in that: The method for obtaining the abnormal frame image includes: The cardiac chamber region whose normal index is less than a preset threshold is regarded as an abnormal cardiac chamber region, and the frame image including the abnormal cardiac chamber region is regarded as an abnormal frame image.

10. A prenatal ultrasound-assisted screening system for congenital heart disease, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of a method for prenatal ultrasound-assisted screening of congenital heart disease as described in any one of claims 1 to 9 are implemented.

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