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CN120015321A - A system for assessing bilirubin levels - Google Patents

A system for assessing bilirubin levels
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Publication number
CN120015321A
CN120015321ACN202510136905.XACN202510136905ACN120015321ACN 120015321 ACN120015321 ACN 120015321ACN 202510136905 ACN202510136905 ACN 202510136905ACN 120015321 ACN120015321 ACN 120015321A
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patient
module
bilirubin
image
images
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Chinese (zh)
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陈航
汪良超
洪清泉
李晶
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Polk Medical Technology Shanghai Co ltd
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Polk Medical Technology Shanghai Co ltd
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Abstract

Translated fromChinese

本发明涉及黄疸检测技术领域,具体涉及一种用于胆红素水平的评定系统,包括:录入模块,用于录入历史患者眼部图像及测定的胆红素值参数;相机模块,用于采集患者眼部图像,应用采集到的患者眼部图像与录入模块中历史患者眼部图像进行结构化相似度比对;调取模块,用于调取相机模块中结构化相似度比对结果最佳的两幅历史患者眼部图像,基于调取的两幅历史患者眼部图像识别患者胆红素值与眼部图像的差异度比值;本发明区别于现有技术,以机器视觉技术采集用户双眼图像,基于大量的先验数据结合用户双眼图像来评定用户胆红素水平,相较于现有血液检测、传感器检测更加简便快捷,相较于现有的机器视觉观测皮肤的方式更加精准。

The present invention relates to the technical field of jaundice detection, and in particular to a bilirubin level assessment system, comprising: an input module, used for inputting historical patient eye images and measured bilirubin value parameters; a camera module, used for collecting patient eye images, and performing structured similarity comparison between the collected patient eye images and the historical patient eye images in the input module; a retrieval module, used for retrieving two historical patient eye images with the best structured similarity comparison results in the camera module, and identifying the difference ratio between the patient's bilirubin value and the eye image based on the two retrieved historical patient eye images; the present invention is different from the prior art, and uses machine vision technology to collect user binocular images, and assesses the user's bilirubin level based on a large amount of prior data combined with the user's binocular images. Compared with the existing blood test and sensor test, the present invention is simpler and faster, and compared with the existing machine vision skin observation method, it is more accurate.

Description

Assessment system for bilirubin level
Technical Field
The invention relates to the technical field of jaundice detection, in particular to an assessment system for bilirubin level.
Background
Neonatal jaundice refers to a condition characterized by yellow coloration of the skin, mucous membranes, and sclera, which occurs in neonates due to elevated levels of bilirubin in the blood caused by abnormal bilirubin metabolism. About 60% of newborns can show jaundice symptoms, wherein pathological jaundice often exceeds 2-4 weeks, and for newborns, symptoms such as vision disorder, bilirubin stones, malnutrition absorption, liver function damage and immune function damage can be caused if the jaundice is not timely treated, so that healthy growth of babies is affected.
Patent application 202010027602.1 discloses a jaundice monitoring sensor in contact with the skin comprising A) a decomposition light source operating with the sensor light source off, B) a sensor light source operating with the decomposition light source off, C) a detector operating with the sensor light source on, wherein if on, the decomposition light source emits light, decomposition is performed and immobilized (tissue-adhered) bilirubin is removed from the skin in the optical path of the sensor light source while the sensor measures the decomposition rate of immobilized (tissue-adhered) bilirubin, and when the sensor light source is on, light received by the detector generates a sensor signal proportional to the mobile (blood) bilirubin by moving the bilirubin instead of immobilized (tissue-adhered) bilirubin, thereby determining blood bilirubin level.
The application aims to solve the problem that the yellow color of the analysis or imaging skin of all the current non-invasive methods aiming at jaundice detection shows that jaundice exists, but the bilirubin level in blood and the change of the bilirubin level in blood cannot be directly reflected.
However, although the bilirubin level in blood can be accurately measured by the method, a professional sensor is required for obtaining the measurement result, the measurement result is influenced by the detection operation and the performance of the sensor, and once the problems of misoperation or self performance failure occur, the detection result has a great deviation or can not be detected;
to this end, an assessment system for bilirubin levels is proposed.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides an assessment system for bilirubin levels, which solves the technical problems set forth in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
an assessment system for bilirubin levels, comprising:
The device comprises a camera module, a retrieval module, an analysis module, a correction module and an output module, wherein the camera module is used for acquiring eye images of a historical patient and measured bilirubin value parameters, the camera module is used for acquiring the eye images of the patient, comparing the acquired eye images of the patient with the eye images of the historical patient in the input module by using the structural similarity, the retrieval module is used for retrieving two eye images of the historical patient with the best structural similarity comparison result in the camera module, identifying the difference ratio of the bilirubin value of the patient to the eye image based on the two retrieved eye images of the historical patient, the analysis module is used for analyzing the similarity between the eye images of the patient acquired by the camera module and the two eye images of the patient retrieved by the retrieval module, determining bilirubin value intervals corresponding to the eye images of the patient acquired by the camera module based on the similarity analysis result, the correction module is used for receiving the bilirubin value intervals corresponding to the patient eye images determined by the analysis module, determining the bilirubin value intervals based on interval attribute, and outputting the bilirubin value intervals processed by the correction module.
Still further, the input module is internally provided with a sub-module, comprising:
The binding unit is used for monitoring the eye images of the patient and the measured bilirubin value parameters in the recording module and binding the eye images of the patient which are continuously recorded and the measured bilirubin value parameters;
the camera module is provided with sub-module in the subordinate, includes:
The preprocessing unit is used for receiving the eye images of the patient acquired by the camera module, converting the eye images of the patient into gray images and outputting the gray images;
the comparison unit is used for receiving the patient eye images converted into gray images, which are output by the operation of the preprocessing unit, and carrying out structural similarity comparison on each patient eye image stored in the input module as a comparison target and the received gray images;
The input module synchronously stores the eye images of the patient and the bilirubin value parameters which are mutually bound based on the input time sequence after inputting and binding the eye images of the patient and the bilirubin value parameters based on the binding unit, the eye images of the patient and the bilirubin value parameters which are measured and input in the input module are sourced from the background of the EMR system, and when the calling module calls the eye images of the patient in the input module, the bilirubin value parameters which are correspondingly bound to the eye images of the patient are synchronously called;
When the comparison unit operates and applies the patient eye images stored in the input module as the comparison targets, the patient eye images stored in the input module are compared sequentially based on time sequence, and when the patient eye images in the input module are applied to the comparison operation, the comparison operation is executed after the patient eye images are synchronously processed by the preprocessing unit and converted into gray images.
Still further, the structural similarity comparison logic of the patient eye image and the gray scale image in the comparison unit is expressed as:
Setting a gray value interval representing pupils and irises, setting a gray value interval representing scleras, dividing pupil, iris area images and sclera area images in the eye images and gray images of a patient based on the gray value interval representing pupils and irises and the gray value interval representing scleras, and capturing pupil and iris area image center points and sclera area image center points;
;
wherein: structural similarity of the eye image and the gray scale image of the patient; coordinates determined based on pixel positions for a pupil and iris region image center point in the gray level image; coordinates determined based on pixel positions for a pupil and iris region image center point in a patient eye image; coordinates determined based on pixel positions for a center point of the sclera region image in the gray scale image; coordinates determined based on pixel locations for a center point of an image of a sclera region in an image of a patient's eye;
Wherein, the structural similarity of the eye image and the gray level image of the patientThe smaller the value is, the higher the structural similarity between the eye image of the patient and the gray level image is, otherwise, the lower the structural similarity between the eye image of the patient and the gray level image is, the structural similarity between the gray level image and each eye image of the patient is calculated based on the above, and the retrieval module operates the two historic eye images with the optimal comparison result, namelyAnd (5) the eye image of the patient corresponding to the two calculation results with the minimum value.
Still further, the recognition logic for the differential ratio of the bilirubin value of the patient to the eye image in the recall module is expressed as:
;
wherein: A differential ratio of bilirubin value of the patient to an eye image; the similarity of the two eye images of the patient, which are fetched for the operation of the fetching module, in the color distribution layer; Operating bilirubin values corresponding to the two transferred patient eye images for the transferring module; Dividing the color tone into equal dividing sections, dividing the saturation into equal dividing sections and dividing the brightness into equal dividing sections; The pixel frequency of the patient eye image A and the patient eye image B in the ith tone interval is given; The pixel frequency of the patient eye image A and the patient eye image B in the jth saturation interval is given; In the first place for patient eye image A and patient eye image BPixel frequency of each brightness interval;
wherein, the difference ratio of bilirubin value of patient to eye imageIn units of (A),Is the unit percentage;
The analysis logic and the analysis logic respectively of the similarity between the eye images of the patient acquired by the camera module in the analysis module and the eye images of the two patients acquired by the acquisition moduleIs the same, the analysis result is recorded asC represents the patient's eye image acquired by the current camera module, and further determinesThe size relation of the three;
At the position ofThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:;
Greater thanThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:
Less thanThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:
Still further, the method further comprises the steps of,Respectively, the minimum value and the maximum value in brackets.
Further, the logic for deciding the output and correction of bilirubin value intervals based on the interval attributes in the correction module is as follows:
the interval attribute decision determines whether the bilirubin value interval contains;
Bilirubin value interval comprisesThe bilirubin value interval is sent to an output module, and the output module executes the output operation of the bilirubin value interval;
Bilirubin value interval does not includeCorrecting the bilirubin value interval;
The logic for correcting bilirubin value interval in the correction module is expressed as:
Identifying the structural similarity between the patient eye image acquired by the camera module and the patient eye image A and the patient eye image B;
the structural similarity between the patient eye image acquired by the camera module and the patient eye image A is higher, and then:
Corrected to;
The structural similarity between the patient eye image acquired by the camera module and the patient eye image B is higher, and then:
Corrected to;
Among them, the + -choice among bilirubin value interval obeys:, middle + -is taken + -from,Middle + -taking-;;
middle + -getting-,Middle + -is taken+;
Wherein,Is constant and is customized by the user of the system end1, And constantThe bilirubin value interval after correction is still within the bilirubin value interval before correction.
Still further, the inside binding unit that is connected with through wireless network interaction of logging module, logging module is connected with the camera module through wireless network interaction, camera module subordinate is connected with preprocessing unit and comparison unit through wireless network interaction, camera module is connected with through wireless network interaction and is called the module, it is connected with logging module through wireless network interaction to call the module, it has analysis module, correction module and output module to call the module through wireless network interaction.
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
The invention provides a bilirubin level assessment system, which is different from the prior art in the operation process, collects images of both eyes of a user by using a machine vision technology, assesses the bilirubin level of the user based on a large amount of priori data combined with the images of both eyes of the user, is simpler, more convenient and quicker than the existing blood detection and sensor detection, is more accurate than the existing machine vision skin observation mode, can continuously improve the system assessment precision based on the continuous accumulation of the priori data, and feeds back to the user at the system end in a bilirubin value interval mode, thereby being more convenient for the user at the system end to make diagnosis and more rapidly make and decide a treatment scheme.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a configuration of an assessment system for bilirubin levels.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Examples:
An assessment system for bilirubin levels of the present embodiment, as shown in FIG. 1, comprises:
The input module is used for inputting historical patient eye images and measured bilirubin value parameters;
the inside submodule piece that is provided with of logging module includes:
The binding unit is used for monitoring the eye images of the patient and the measured bilirubin value parameters in the recording module and binding the eye images of the patient which are continuously recorded and the measured bilirubin value parameters;
after the historic patient eye images and the bilirubin value parameters are recorded and bound based on the binding unit, the recording module synchronously stores the mutually bound patient eye images and bilirubin value parameters based on recording time sequence sequencing, the historic patient eye images recorded in the recording module and the measured bilirubin value parameters are derived from an EMR system background, and when the calling module calls the patient eye images in the recording module, the bilirubin value parameters corresponding to the binding of the patient eye images are synchronously called;
the camera module is used for collecting eye images of the patient, and carrying out structural similarity comparison on the collected eye images of the patient and the historical eye images of the patient in the input module;
the camera module is provided with the submodule in the subordinate, includes:
The preprocessing unit is used for receiving the eye images of the patient acquired by the camera module, converting the eye images of the patient into gray images and outputting the gray images;
the comparison unit is used for receiving the patient eye images converted into gray images, which are output by the operation of the preprocessing unit, and carrying out structural similarity comparison on each patient eye image stored in the input module as a comparison target and the received gray images;
When the comparison unit operates and applies the patient eye images stored in the input module as the comparison targets, the patient eye images stored in the input module are compared sequentially based on time sequence, and when the patient eye images in the input module are applied to the comparison operation, the comparison operation is executed after the patient eye images are synchronously processed by the preprocessing unit and converted into gray images;
the extraction module is used for extracting two historical patient eye images with the best structural similarity comparison result in the camera module, and identifying the difference ratio value of the bilirubin value of the patient to the eye images based on the extracted two historical patient eye images;
the structural similarity comparison logic of the patient eye image and the gray scale image in the comparison unit is expressed as follows:
Setting a gray value interval representing pupils and irises, setting a gray value interval representing scleras, dividing pupil, iris area images and sclera area images in the eye images and gray images of a patient based on the gray value interval representing pupils and irises and the gray value interval representing scleras, and capturing pupil and iris area image center points and sclera area image center points;
;
wherein: structural similarity of the eye image and the gray scale image of the patient; coordinates determined based on pixel positions for a pupil and iris region image center point in the gray level image; coordinates determined based on pixel positions for a pupil and iris region image center point in a patient eye image; coordinates determined based on pixel positions for a center point of the sclera region image in the gray scale image; coordinates determined based on pixel locations for a center point of an image of a sclera region in an image of a patient's eye;
Wherein, the structural similarity of the eye image and the gray level image of the patientThe smaller the value is, the higher the structural similarity between the eye image of the patient and the gray level image is, otherwise, the lower the structural similarity between the eye image of the patient and the gray level image is, the structural similarity between the gray level image and each eye image of the patient is calculated based on the above, and the retrieval module operates the two historic eye images with the optimal comparison result, namelyThe eye image of the patient corresponding to the two calculation results with the minimum value;
the structural similarity of the eye image and the gray level image of the patient is calculated through the logic formula, and necessary operation data support is provided for the operation of the subsequent modules of the system in the embodiment.
The recognition logic of the difference ratio of the bilirubin value of the patient and the eye image in the calling module is expressed as follows:
;
wherein: A differential ratio of bilirubin value of the patient to an eye image; the similarity of the two eye images of the patient, which are fetched for the operation of the fetching module, in the color distribution layer; Operating bilirubin values corresponding to the two transferred patient eye images for the transferring module; Dividing the color tone into equal dividing sections, dividing the saturation into equal dividing sections and dividing the brightness into equal dividing sections; The pixel frequency of the patient eye image A and the patient eye image B in the ith tone interval is given; The pixel frequency of the patient eye image A and the patient eye image B in the jth saturation interval is given; In the first place for patient eye image A and patient eye image BPixel frequency of each brightness interval;
wherein, the difference ratio of bilirubin value of patient to eye imageIn units of (A),The meaning of units of K can be regarded as the amount of change in bilirubin value for each percent similarity, i.e., where H represents the bilirubin value.
Through the logic formula, the difference ratio of the bilirubin value of the patient to the eye image is calculated, and necessary data support is provided for the subsequent determination of the bilirubin value interval by the system in the embodiment.
The analysis module is used for analyzing the similarity between the patient eye images acquired by the camera module and the two patient eye images acquired by the acquisition module respectively, and determining bilirubin value intervals corresponding to the patient eye images acquired by the camera module based on the similarity analysis result;
Analysis logic and for similarity between patient eye images acquired by the camera module in the analysis module and two patient eye images acquired by the acquisition module respectivelyIs the same, the analysis result is recorded asC represents the patient's eye image acquired by the current camera module, and further determinesThe size relation of the three;
At the position ofThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:;
Greater thanThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:
Less thanThe bilirubin value interval corresponding to the eye image of the patient acquired by the camera module is as follows:;
the correction module is used for receiving the bilirubin value interval corresponding to the patient eye image determined in the analysis module, and deciding the output and correction of the bilirubin value interval based on the interval attribute;
the logic for deciding the output and correction of bilirubin value intervals based on interval attributes in the correction module is as follows:
the interval attribute decision determines whether the bilirubin value interval contains;
Bilirubin value interval comprisesThe bilirubin value interval is sent to an output module, and the output module executes the output operation of the bilirubin value interval;
Bilirubin value interval does not includeCorrecting the bilirubin value interval;
The logic for correcting bilirubin value interval in the correction module is expressed as:
Identifying the structural similarity between the patient eye image acquired by the camera module and the patient eye image A and the patient eye image B;
the structural similarity between the patient eye image acquired by the camera module and the patient eye image A is higher, and then:
Corrected to;
The structural similarity between the patient eye image acquired by the camera module and the patient eye image B is higher, and then:
Corrected to;
Among them, the + -choice among bilirubin value interval obeys:, middle + -is taken + -from,Middle + -taking-;;
middle + -getting-,Middle + -is taken+;
Wherein,Is constant and is customized by the user of the system end1, And constantThe bilirubin value interval after correction is still in the bilirubin value interval before correction;
Through the logic expression, the bilirubin value interval assessed by the user is determined and further corrected, so that the bilirubin value interval is finally output by the system.
The output module is used for outputting the bilirubin value interval processed by the correction module;
The input module is internally connected with a binding unit through wireless network interaction, the input module is connected with a camera module through wireless network interaction, the lower level of the camera module is connected with a preprocessing unit and a comparison unit through wireless network interaction, the camera module is connected with a calling module through wireless network interaction, the calling module is connected with the input module through wireless network interaction, and the calling module is connected with an analysis module, a correction module and an output module through wireless network interaction.
In this embodiment, the recording module operates to record the historical patient eye images and the measured bilirubin value parameters, the binding unit synchronously monitors the patient eye images and the measured bilirubin value parameters in the recording module, the camera module further collects the patient eye images, the collected patient eye images and the historical patient eye images in the recording module are applied to perform structural similarity comparison, the preprocessing unit synchronously receives the patient eye images collected by the camera module, converts the patient eye images into gray level images and outputs the gray level images, the comparison unit receives the patient eye images converted into gray level images output by the preprocessing unit in real time, each patient eye image stored in the recording module is used as a comparison target to perform structural similarity comparison with the received gray level images, the two historical patient eye images with optimal structural similarity comparison results in the camera module are called by the calling module, the difference ratio of the patient bilirubin values to the eye images is identified based on the two historic patient eye images collected by the calling module, the patient eye images of the analysis module are respectively matched with the two patient eye images collected by the calling module, the bilirubin values of the two patient eye images in the calling module are further determined based on the difference ratio of the bilirubin value of the two patient eye images in the receiving module in the receiving section, the bilirubin value of the bilirubin zone is further determined by the bilirubin value of the receiving section of the image by the receiving section of the bilirubin value of the image by the camera module, and the bilirubin value is output by the image by the corresponding to the image by the matching section of the receiving section of the image by the matching module.
Through the system in the embodiment, a large amount of priori data is used as a reference to acquire the eye images of the user to evaluate the bilirubin level of the user, and compared with the prior art, the bilirubin level evaluation system is quicker, has relatively higher accuracy and has good robustness.
As shown in figure 1 of the drawings,Respectively, the minimum value and the maximum value in brackets.
In summary, in the operation process of the system in the above embodiment, unlike the prior art, the machine vision technology is used to collect images of both eyes of the user, and based on a large amount of prior data, the bilirubin level of the user is assessed by combining the images of both eyes of the user.
The foregoing embodiments are merely for illustrating the technical solution of the present invention, but not for limiting the same, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that modifications may be made to the technical solution described in the foregoing embodiments or equivalents may be substituted for parts of the technical features thereof, and such modifications or substitutions may be made without departing from the spirit and scope of the technical solution of the embodiments of the present invention.

Claims (10)

Wherein: structural similarity of the eye image and the gray scale image of the patient; coordinates determined based on pixel positions for a pupil and iris region image center point in the gray level image; coordinates determined based on pixel positions for a pupil and iris region image center point in a patient eye image; coordinates determined based on pixel positions for a center point of the sclera region image in the gray scale image; Coordinates determined based on pixel positions for a center point of a sclera region image in an eye image of a patient, wherein the structural similarity of the eye image of the patient and a gray scale imageThe smaller the value is, the higher the structural similarity between the eye image of the patient and the gray level image is, otherwise, the lower the structural similarity between the eye image of the patient and the gray level image is, the structural similarity between the gray level image and each eye image of the patient is calculated based on the above, and the retrieval module operates the two historic eye images with the optimal comparison result, namelyAnd (5) the eye image of the patient corresponding to the two calculation results with the minimum value.
wherein: A differential ratio of bilirubin value of the patient to an eye image; the similarity of the two eye images of the patient, which are fetched for the operation of the fetching module, in the color distribution layer; Operating bilirubin values corresponding to the two transferred patient eye images for the transferring module; Dividing the color tone into equal dividing sections, dividing the saturation into equal dividing sections and dividing the brightness into equal dividing sections; The pixel frequency of the patient eye image A and the patient eye image B in the ith tone interval is given; The pixel frequency of the patient eye image A and the patient eye image B in the jth saturation interval is given; In the first place for patient eye image A and patient eye image BPixel frequency of each brightness interval;
CN202510136905.XA2025-02-072025-02-07 A system for assessing bilirubin levelsPendingCN120015321A (en)

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