Automatic organ wound identification control system

Abstract

The invention relates to the technical field of wound identification, in particular to an organ wound automatic identification control system, which comprises a data acquisition module, an image segmentation module, a data processing module, a data processing module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring organ wound image data of a user and historical organ wound image data of the user; the segmentation module is used for determining whether to segment the organ trauma image according to the uniformity of the organ trauma in the organ trauma image data; the trauma identification module is used for determining the type of the organ trauma according to the organ trauma image data; the control module is used for determining to upload the organ trauma image to different databases according to the type of the organ trauma and the change value of the organ trauma degree under the third type within the preset time; and the adjusting module is used for determining whether to adjust the parameters of the automatic identification control process of the organ trauma according to the accuracy degree of the automatic identification control result of the organ trauma. According to the invention, the accuracy of identifying the type of the organ trauma is improved by accurately analyzing the image data of the organ trauma.

Description

Technical Field

[0001] The present invention relates to the technical field of wound identification, and in particular to an automatic organ wound identification control system. Background Art

[0002] With the continuous development of medical imaging technology and the popularization of advanced algorithms, external organ trauma recognition and control system technology has become a research direction that has attracted much attention in the medical field. This technology combines computer vision, deep learning and medical image processing technology to achieve rapid and accurate recognition and quantitative evaluation of external organ trauma, providing important diagnostic support and treatment guidance for medical staff. However, traditional external organ trauma recognition and control technology not only has a slow processing speed, but also has difficulty in capturing changes in trauma in a timely manner, which affects the decision-making and treatment process of medical staff.

[0003] Chinese patent application publication number: CN117409002A discloses a visual recognition detection system for trauma and its detection method, the system includes an image acquisition module, an image preprocessing module, a visual neural network module, a trauma analysis module, a data storage management module, and a result display module; the invention can perform automated trauma detection, reduce errors in subjective judgment, improve the efficiency and accuracy of trauma identification and measurement, and play a positive role in assisting medical decision-making.

[0004] It can be seen that the existing technology has the problem of inaccurate analysis of organ trauma image data, which leads to inaccurate determination of organ trauma types and failure to timely detect potentially dangerous organ trauma. Summary of the invention

[0005] To this end, the present invention provides an automatic organ trauma identification and control system to overcome the problem in the prior art that the analysis of organ trauma image data is not accurate enough, resulting in inaccurate determination of organ trauma types and failure to timely detect potentially dangerous organ trauma.

[0006] To achieve the above object, the present invention provides an organ injury automatic identification and control system, comprising:

[0007] A data acquisition module, which is used to acquire the user's organ trauma image data and the user's historical organ trauma image data, and pre-process the organ trauma image data;

[0008] An image segmentation module, which is connected to the data acquisition module and is used to determine whether to segment the organ trauma image according to the uniformity of the trauma in the organ trauma image data;

[0009] a trauma identification module, which is connected to the image segmentation module and is used to determine the type of organ trauma according to the degree of organ trauma in the organ trauma image data, the malignant transformation rate of the organ trauma, and whether the organ has historical trauma, wherein the types of organ trauma include a first type, a second type, and a third type;

[0010] A control module connected to the trauma identification module, for determining whether to upload the organ trauma image to different databases according to the type of organ trauma and the change value of the degree of organ trauma under the third type within a preset time;

[0011] An adjustment module, connected to the control module, for determining whether to adjust the parameters of the organ injury automatic identification control process according to a comparison result of the accuracy of the organ injury automatic identification control result and a preset accuracy;

[0012] Among them, the control module determines to upload the organ trauma image to the first database, the second database and the third database by comparing the type of organ trauma and the change value of the degree of organ trauma under the third type within the preset time with the preset change value, and the preset change value includes a first preset change value and a second preset change value.

[0013] Furthermore, the image segmentation module determines the segmentation of the organ trauma image according to the comparison result that the uniformity of the organ trauma in the organ trauma image data is greater than or equal to a preset uniformity.

[0014] Furthermore, the trauma identification module determines the type of organ trauma by:

[0015] The trauma identification module determines that the type of the organ trauma is the first type according to the comparison result that the degree of trauma of the organ is greater than or equal to the preset degree of trauma;

[0016] The trauma recognition module determines the malignant transformation rate of the organ trauma according to the comparison result that the trauma degree of the organ is less than the preset trauma degree.

[0017] Furthermore, the trauma identification module determines the type of the organ trauma according to a comparison result of the malignant transformation rate of the organ trauma and a preset malignant transformation rate under the condition of determining the malignant transformation rate of the organ trauma, wherein:

[0018] The trauma identification module determines that the type of the organ trauma is the first type according to the malignant transformation rate of the organ trauma being greater than or equal to the preset malignant transformation rate;

[0019] The trauma identification module determines whether the organ has a historical trauma according to the malignant transformation rate of the organ trauma being less than a preset malignant transformation rate.

[0020] Furthermore, the trauma identification module determines the type of the organ trauma according to whether the organ has a historical trauma, under the condition of determining whether the organ has a historical trauma.

[0021] The trauma identification module determines that the type of the organ trauma is the second type according to the existence of historical trauma to the organ;

[0022] The trauma identification module determines that the type of the organ trauma is the third type based on the absence of historical trauma to the organ.

[0023] Furthermore, the control module determines to upload the organ trauma image to different databases according to the comparison result between the change value of the organ trauma degree and the preset change value, wherein:

[0024] The control module determines to upload the organ trauma image to the first database according to a comparison result that the change value of the organ trauma degree within the preset time is less than the first preset change value;

[0025] The control module determines to upload the organ trauma image to the second database according to a comparison result that the change value of the organ trauma degree within the preset time is greater than or equal to the first preset change value and less than the second preset change value;

[0026] The control module determines to upload the organ trauma image to the third database according to the comparison result that the change value of the organ trauma within the preset time is greater than or equal to the second preset change value.

[0027] Furthermore, the preset change value of the organ trauma is determined according to a preset trauma degree.

[0028] Furthermore, the adjustment module determines adjustment of the parameters of the automatic organ trauma identification control process according to a comparison result that the accuracy of the automatic organ trauma identification control result is less than a preset accuracy, wherein the parameters of the automatic organ trauma identification control process include a preset uniformity and a preset malignancy rate.

[0029] Furthermore, the adjustment amount of the preset uniformity is negatively correlated with the fluctuation degree of the error types when uploading organ trauma images to different databases during the automatic identification and control process of organ trauma within several preset cycles, and the adjustment amount of the preset malignancy rate is positively correlated with the fluctuation degree of the error types when uploading organ trauma images to different databases during the automatic identification and control process of organ trauma within several preset cycles.

[0030] Furthermore, the value of the preset fluctuation degree is the average value of the fluctuation degrees of error types in uploading organ trauma images to different databases during the organ trauma automatic identification control process within a number of preset cycles.

[0031] Compared with the prior art, the beneficial effect of the present invention is that the present invention determines whether to segment the organ trauma image according to the uniformity of the organ trauma in the organ trauma image data. If the trauma in the organ trauma image data is relatively uniform, the organ trauma image is not segmented to improve the accuracy of the subsequent trauma analysis. If the trauma in the organ trauma image data is uneven, the image can more accurately determine the location and range of the trauma by segmenting the organ trauma image, which helps to improve the accuracy of the subsequent trauma analysis, including the type and severity of the trauma. Segmenting the organ trauma can make the quantitative evaluation of the trauma more convenient. Through segmentation, the size, shape and other parameters of the trauma area can be calculated, thereby providing more quantitative data for analysis. Organ trauma image segmentation can help doctors better understand the patient's trauma situation, thereby formulating a more personalized treatment plan. Traumas of different sizes and locations may require different treatment strategies. The segmented organ trauma image can provide a clearer visualization effect, which helps doctors and researchers better understand the characteristics of the trauma and discover details that may be overlooked. The segmented organ trauma image can be more easily integrated with other medical data, such as clinical data, biomarkers, etc., to achieve comprehensive trauma analysis and prediction.

[0032] Furthermore, the present invention determines the type of organ trauma according to the degree of organ trauma and a preset degree of trauma through a trauma recognition module. If the degree of trauma is greater than or equal to the preset degree of trauma, it indicates that the organ trauma is of the first type requiring emergency treatment. If the degree of trauma is less than the preset degree of trauma, the type of organ trauma is secondary determined by detecting the malignant transformation rate of the organ trauma. The above method improves the accuracy of organ trauma image data analysis and thus improves the accuracy of organ trauma type determination, so as to timely discover potentially dangerous organ trauma.

[0033] Furthermore, the present invention determines the type of organ trauma according to the comparison result of the malignant transformation rate of the organ trauma with the preset malignant transformation rate through the trauma recognition module. If the malignant transformation rate is greater than or equal to the preset malignant transformation rate, it indicates that the organ trauma is of the first type that is prone to malignant transformation and requires emergency treatment. If the malignant transformation rate is less than the preset malignant transformation rate, the organ trauma type is determined by detecting whether the organ has historical trauma. The above method improves the accuracy of the analysis of the organ trauma image data and thus improves the accuracy of the determination of the organ trauma type, so as to timely discover potentially dangerous organ trauma.

[0034] Furthermore, the present invention further determines the type of organ trauma according to whether the organ has a history of trauma through a trauma recognition module. If the organ has a history of trauma, it means that the organ trauma may have a dangerous hidden danger. The trauma recognition module determines that the organ trauma type is the second type with a dangerous hidden danger. If the organ has no history of trauma, it means that the organ trauma type is the third type that does not require emergency treatment by a doctor. The above method improves the accuracy of the analysis of organ trauma image data and thus improves the accuracy of organ trauma type determination, so as to timely discover potentially dangerous organ trauma.

[0035] Furthermore, the present invention uploads first and second types of organ trauma images that require a doctor to determine whether treatment is required to the first database through a control module. The control module determines to upload a third type of organ trauma image to a different database based on the change of the organ trauma within a preset time. If the change value of the organ trauma degree within the preset time is greater than or equal to the second preset change value, it means that the organ trauma has deteriorated due to bacterial infection or other external factors. At this time, the organ trauma image is uploaded to the second database. If the change value of the organ trauma degree within the preset time is greater than or equal to the first preset change value and less than the second preset change value, the display clarity of the organ trauma image is enhanced to more accurately judge the change of the organ trauma. If the change value of the organ trauma degree within the preset time is less than the first preset change value, it means that the organ trauma can recover naturally without doctor's treatment. At this time, the organ trauma image is uploaded to the first database. The above method improves the accuracy of organ trauma image data analysis and thus improves the accuracy of organ trauma type determination and timely discovers potentially dangerous organ trauma.

[0036] Furthermore, the present invention determines the accuracy of the organ trauma automatic identification control result according to the accuracy of the control module uploading the organ trauma image to different databases, and determines whether to adjust the parameters of the organ trauma automatic identification control process based on the comparison result of the accuracy with the preset accuracy. The above method improves the accuracy of the organ trauma image data analysis and thus improves the accuracy of the organ trauma type determination, so as to timely discover potentially dangerous organ trauma.

[0037] Furthermore, the present invention determines the adjustment method of the automatic identification control process of organ trauma according to the fluctuation degree of errors uploaded to different databases by the control module through the adjustment module. If the fluctuation degree is less than the preset fluctuation degree, it means that in the automatic identification control process of organ trauma, due to the presence of an area with a very small trauma degree greater than the preset trauma degree in the process of organ trauma image segmentation, the organ trauma that does not require emergency treatment is misjudged as the first type, resulting in low accuracy of the automatic identification control result of organ trauma. At this time, the preset uniformity is increased by the first adjustment coefficient. If the fluctuation degree is greater than or equal to the preset fluctuation degree, it means that the number of misjudgments of the third type of organ trauma is large. At this time, the preset malignant transformation rate is reduced by the second adjustment coefficient, thereby reducing the number of organ traumas of the third type, thereby reducing the number of misjudgments of the third type of organ trauma. The above method improves the accuracy of the analysis of organ trauma image data and thus improves the accuracy of organ trauma type determination, so as to timely discover potentially dangerous organ trauma. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a schematic diagram of the structure of an automatic organ injury identification control system according to an embodiment of the present invention;

[0039] Figure 2 This is a working diagram of an image segmentation module in an automatic organ injury recognition control system according to an embodiment of the present invention;

[0040] Figure 3 The figure is a working flow chart of the adjustment module in the automatic organ injury identification and control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0042] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0043] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0044] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0045] See also Figure 1-Figure 3 As shown, Figure 1 This is a schematic diagram of the structure of an automatic organ injury identification control system according to an embodiment of the present invention; Figure 2 This is a working diagram of an image segmentation module in an automatic organ injury recognition control system according to an embodiment of the present invention; Figure 3 The figure is a working flow chart of the adjustment module in the automatic organ injury identification and control system according to an embodiment of the present invention.

[0046] The automatic organ injury identification and control system according to the embodiment of the present invention comprises:

[0047] A data acquisition module, which is used to acquire the user's organ trauma image data and the user's historical organ trauma image data, and pre-process the organ trauma image data;

[0048] An image segmentation module, which is connected to the data acquisition module and is used to determine whether to segment the organ trauma image according to the uniformity of the trauma in the organ trauma image data;

[0049] a trauma identification module, which is connected to the image segmentation module and is used to determine the type of organ trauma according to the degree of organ trauma in the organ trauma image data, the malignant transformation rate of the organ trauma, and whether the organ has historical trauma, wherein the types of organ trauma include a first type, a second type, and a third type;

[0050] A control module connected to the trauma identification module, for determining whether to upload the organ trauma image to different databases according to the type of organ trauma and the change value of the degree of organ trauma under the third type within a preset time;

[0051] The adjustment module is connected to the control module and is used to determine whether to adjust the parameters of the organ injury automatic identification control process according to the comparison result of the accuracy of the organ injury automatic identification control result and the preset accuracy.

[0052] The preset change value of the organ injury degree in the embodiment of the present invention includes a first preset change value and a second preset change value.

[0053] Specifically, the image segmentation module determines whether to segment the organ trauma image according to the comparison result of the uniformity S of the organ trauma in the organ trauma image data and the preset uniformity S0;

[0054] If S≥S0, the image segmentation module determines to segment the organ trauma image;

[0055] If S<S0, the image segmentation module determines not to segment the organ trauma image;

[0056] The value range of the preset uniformity level S0 is set to 0-0.3, and the value of the preset uniformity level S0 is preferably 0.2, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0057] Specifically, the uniformity S of the organ injury in the organ injury image data is calculated by the following formula, set:

[0058]

[0059] Among them, M represents the difference between the maximum and minimum values ​​of the organ trauma density, M0 represents the average value of the organ trauma density, α represents the influence coefficient of the organ trauma density on the trauma uniformity, and its value is preferably 0.56, D represents the maximum chromaticity value of the organ trauma, D0 represents the average chromaticity value of the organ trauma, and β represents the influence coefficient of the chromaticity value of the organ trauma on the trauma uniformity, and its value is set to 0.44.

[0060] The organ injury density in the embodiment of the present invention may be determined according to the gray value in the organ injury image.

[0061] The present invention determines whether to segment the organ trauma image according to the uniformity of the organ trauma in the organ trauma image data. If the trauma in the organ trauma image data is relatively uniform, the organ trauma image is not segmented to improve the accuracy of the subsequent trauma analysis. If the trauma in the organ trauma image data is uneven, the image can more accurately determine the location and range of the trauma by segmenting the organ trauma image, which helps to improve the accuracy of the subsequent trauma analysis, including the type and severity of the trauma. Segmenting the organ trauma can make the quantitative evaluation of the trauma more convenient. Through segmentation, the size, shape and other parameters of the trauma area can be calculated, thereby providing more quantitative data for analysis. Organ trauma image segmentation can help doctors better understand the patient's trauma situation, thereby formulating a more personalized treatment plan. Traumas of different sizes and locations may require different treatment strategies. The segmented organ trauma image can provide a clearer visualization effect, which helps doctors and researchers better understand the characteristics of the trauma and discover details that may be overlooked. The segmented organ trauma image can be more easily integrated with other medical data, such as clinical data, biomarkers, etc., to achieve comprehensive trauma analysis and prediction.

[0062] Specifically, under the condition that the type of organ trauma is determined, the trauma recognition module determines the type of organ trauma according to the comparison result of the organ trauma degree Y and the preset trauma degree Y0;

[0063] If Y≥Y0, the trauma identification module determines that the organ trauma type is the first type;

[0064] If Y<Y0, the trauma identification module determines to detect the malignant transformation rate of the organ trauma;

[0065] Among them, the value range of the preset trauma degree Y0 is set to 9-20, and the value of the preset trauma degree Y0 is preferably 15, but the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0066] The degree of trauma in the embodiments of the present invention can be determined according to the Injury Severity Score (ISS).

[0067] The present invention determines the organ trauma type according to the organ trauma degree and the preset trauma degree through the trauma recognition module. If the trauma degree is greater than or equal to the preset trauma degree, it indicates that the organ trauma is of the first type requiring emergency treatment. If the trauma degree is less than the preset trauma degree, the organ trauma type is secondary determined by detecting the malignant transformation rate of the organ trauma. The above method improves the accuracy of the analysis of the organ trauma image data and thus improves the accuracy of the determination of the organ trauma type, so as to timely discover potentially dangerous organ trauma.

[0068] Specifically, under the condition of determining the malignant transformation rate of the organ trauma, the trauma identification module determines the type of the organ trauma according to the comparison result of the malignant transformation rate A of the organ trauma and the preset malignant transformation rate A0;

[0069] If A≥A0, the trauma identification module determines that the type of the organ trauma is the first type;

[0070] If A<A0, the trauma identification module determines whether the organ has a historical trauma;

[0071] The value range of the preset malignant transformation rate A0 is set to 0.5-1, and the value of the preset malignant transformation rate is preferably 0.7, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0072] The malignant transformation rate in the present invention is the ratio of the number of malignant transformations of organ injuries of several patients with the same degree of injury as the organ injury to the total number of organ injuries of several patients, and the malignant transformation requires emergency treatment by doctors.

[0073] The present invention determines the type of organ trauma according to the comparison result of the malignant transformation rate of the organ trauma and the preset malignant transformation rate through the trauma recognition module. If the malignant transformation rate is greater than or equal to the preset malignant transformation rate, it indicates that the organ trauma is of the first type that is prone to malignant transformation and requires emergency treatment. If the malignant transformation rate is less than the preset malignant transformation rate, the organ trauma type is determined by detecting whether the organ has historical trauma. The above method improves the accuracy of the analysis of the organ trauma image data and thus improves the accuracy of the determination of the organ trauma type, so as to timely discover the organ trauma with potential dangers.

[0074] Specifically, the trauma identification module determines the type of the organ trauma according to whether the organ has a historical trauma, under the condition of determining whether the organ has a historical trauma.

[0075] If the organ has a historical trauma, the trauma identification module determines that the type of the organ trauma is the second type;

[0076] If the organ has no historical trauma, the trauma identification module determines that the type of the organ trauma is the third type.

[0077] The present invention further determines the type of organ trauma according to whether the organ has a history of trauma through a trauma recognition module. If the organ has a history of trauma, it means that the organ trauma may have a dangerous hidden danger. The trauma recognition module determines that the organ trauma type is the second type with a dangerous hidden danger. If the organ has no history of trauma, it means that the organ trauma type is the third type that does not require emergency treatment by a doctor. The above method improves the accuracy of the analysis of organ trauma image data and thus improves the accuracy of the determination of the organ trauma type, so as to timely discover potentially dangerous organ trauma.

[0078] Specifically, the control module uploads the organ trauma images to different databases according to the types of organ trauma;

[0079] The control module determines to upload the organ trauma image to the third database according to whether the type of the organ trauma is the first type or the second type;

[0080] The control module determines to perform a secondary determination on uploading the organ injury image to a different database according to the type of the organ injury being the third type.

[0081] Specifically, the control module determines to upload the organ trauma image to different databases according to the comparison result of the change value B of the organ trauma within a preset time and the preset change value Bi under the condition of determining to perform a secondary determination on uploading the organ trauma image to different databases;

[0082] If B<B0, the control module determines to upload the organ trauma image to the first database;

[0083] If B0≤B<B1, the control module determines to upload the organ trauma image to the second database;

[0084] If B≥B1, the control module determines to upload the organ trauma image to the third database;

[0085] Among them, i=0,1; the value of the first preset change value B0 is preferably -3, and the value of the second preset change value B1 is preferably 0, but the above values ​​are not limited to this, and those skilled in the art can also adjust the values ​​according to actual needs.

[0086] The preset time in the embodiment of the present invention is set to one twentieth of the time it takes for the organ injury to fully recover, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0087] In the embodiment of the present invention, the organ trauma image data stored in the first database are organ trauma images that require a doctor's confirmation whether to perform emergency treatment, the organ trauma images stored in the second database are organ trauma images that require enhanced display clarity of the organ trauma images, and the organ trauma images stored in the third database are historical organ trauma images of the user.

[0088] The present invention uploads first and second types of organ trauma images that require a doctor to determine whether treatment is required to a first database through a control module. The control module determines to upload a third type of organ trauma image to a different database based on the change of the organ trauma within a preset time. If the change value of the organ trauma degree within the preset time is greater than or equal to the second preset change value, it means that the organ trauma has deteriorated due to bacterial infection or other external factors. At this time, the organ trauma image is uploaded to the second database. If the change value of the organ trauma degree within the preset time is greater than or equal to the first preset change value and less than the second preset change value, the display clarity of the organ trauma image is enhanced to more accurately judge the change of the organ trauma. If the change value of the organ trauma degree within the preset time is less than the first preset change value, it means that the organ trauma can recover naturally without doctor's treatment. At this time, the organ trauma image is uploaded to the first database. The above method improves the accuracy of organ trauma image data analysis and thus improves the accuracy of organ trauma type determination and timely discovers potentially dangerous organ trauma.

[0089] Specifically, the adjustment module determines whether to adjust the parameters of the automatic organ trauma identification control process under the condition of determining whether to adjust the parameters of the automatic organ trauma identification control process according to the comparison result of the accuracy degree P of the automatic organ trauma identification control result and the preset accuracy degree P0;

[0090] If P<P0, the adjustment module determines that the parameters of the organ trauma automatic identification control process need to be adjusted;

[0091] If P≥P0, the adjustment module determines that there is no need to adjust the parameters of the organ trauma automatic identification control process;

[0092] Among them, the value range of the preset accuracy level P0 is set to 0.7-1, and the value of the preset accuracy level is preferably 0.82, but the above value is not limited thereto, and those skilled in the art can also adjust the value according to actual needs.

[0093] In the embodiment of the present invention, the accuracy of the organ trauma automatic identification control result is one third of the sum of the accuracy of uploading organ trauma images to different databases, the accuracy of uploading organ trauma images to the third database is the ratio of the number of organ trauma images that need medical treatment in the third database to the total number of organ trauma images in the third database, the accuracy of uploading organ trauma images to the second database is the ratio of the number of organ trauma images in the second database that are uploaded to the first database or the third database when they are uploaded to the database next time to the total number of organ trauma images in the second database, and the accuracy of uploading organ trauma images to the third database is the ratio of the number of organ trauma images in the third database that do not require emergency treatment during subsequent spot checks to the total number of organ trauma images in the third database.

[0094] The present invention determines the accuracy of the organ trauma automatic identification control result according to the accuracy of the control module uploading the organ trauma image to different databases, and determines whether to adjust the parameters of the organ trauma automatic identification control process based on the comparison result of the accuracy with the preset accuracy. The above method improves the accuracy of the organ trauma image data analysis and thus improves the accuracy of the organ trauma type determination, so as to timely discover potentially dangerous organ trauma.

[0095] Specifically, under the condition that the adjustment module determines that the parameters of the organ trauma automatic identification control process need to be adjusted, the adjustment module determines the adjustment method according to the comparison result of the fluctuation degree R of the error type of the organ trauma image uploaded by the control module to different databases within a preset period and the preset fluctuation degree R0;

[0096] If R<R0, the adjustment module determines to adjust the preset uniformity by the first adjustment coefficient K1;

[0097] If R≥R0, the adjustment module determines to adjust the preset malignancy rate by a second adjustment coefficient K2;

[0098] Among them, the value of the preset fluctuation degree R0 is the average value of the fluctuation degree of the error type when uploading the organ trauma image to different databases during the automatic identification control of organ trauma within several preset cycles, but the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0099] In the embodiment of the present invention, the preset period can be set to 3 days, and the fluctuation degree of the error type of uploading organ trauma images to different databases within the preset period can be calculated according to the change frequency of the error type within the preset period. For example, the number of changes in the error type of uploading organ trauma images to different databases within the preset period is 35 times, and the number of errors in uploading organ trauma images to different databases within the preset period is 50 times, then the fluctuation degree is 0.7.

[0100] Specifically, the first adjustment coefficient K1 is calculated and set by the following formula:

[0101]

[0102] The second adjustment coefficient K2 is calculated and set by the following formula:

[0103]

[0104] The adjusted preset uniformity level S0' is set to S0'=K1×S0;

[0105] The adjusted preset malignant rate A0' is set to A0'=K2×A0.

[0106] The error types of uploading organ trauma images to different databases described in the embodiment of the present invention include a first error type corresponding to erroneously uploading organ trauma images to a first database, a second error type corresponding to erroneously uploading organ trauma images to a second database, and a third error type corresponding to erroneously uploading organ trauma images to a third database.

[0107] The present invention determines the adjustment method of the automatic identification control process of organ trauma according to the fluctuation degree of the error type of organ trauma uploaded to different databases by the control module through the adjustment module. If the fluctuation degree is less than the preset fluctuation degree, it means that in the automatic identification control process of organ trauma, due to the presence of an area with a very small trauma degree greater than the preset trauma degree in the process of organ trauma image segmentation, the organ trauma that does not require emergency treatment is misjudged as the first type, resulting in low accuracy of the automatic identification control result of organ trauma. At this time, the preset uniformity is increased by the first adjustment coefficient. If the fluctuation degree is greater than or equal to the preset fluctuation degree, it means that the third type of organ trauma misjudgment amount is large. At this time, the preset malignant transformation rate is reduced by the second adjustment coefficient, thereby reducing the number of the third type of organ trauma, thereby reducing the number of misjudgments of the third type of organ trauma. The above method improves the accuracy of the analysis of organ trauma image data and thus improves the accuracy of organ trauma type determination, so as to timely discover potentially dangerous organ trauma.

[0108] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An automatic organ injury identification and control system, characterized in that: include: A data acquisition module, which is used to acquire the user's organ trauma image data and the user's historical organ trauma image data, and pre-process the organ trauma image data; An image segmentation module, which is connected to the data acquisition module and is used to determine whether to segment the organ trauma image according to the uniformity of the trauma in the organ trauma image data; a trauma identification module, which is connected to the image segmentation module and is used to determine the type of organ trauma according to the degree of organ trauma in the organ trauma image data, the malignant transformation rate of the organ trauma, and whether the organ has historical trauma, wherein the types of organ trauma include a first type, a second type, and a third type; A control module connected to the trauma recognition module, for determining whether to upload the organ trauma image to different databases according to the type of organ trauma and the change value of the degree of organ trauma under the third type within a preset time; An adjustment module, connected to the control module, for determining whether to adjust the parameters of the organ injury automatic identification control process according to a comparison result of the accuracy of the organ injury automatic identification control result and a preset accuracy; Among them, the control module determines to upload the organ trauma image to the first database, the second database and the third database by comparing the type of organ trauma and the change value of the degree of organ trauma under the third type within the preset time with the preset change value, and the preset change value includes a first preset change value and a second preset change value.

2. The organ injury automatic identification and control system according to claim 1, characterized in that: The image segmentation module determines the segmentation of the organ trauma image according to the comparison result that the uniformity of the organ trauma in the organ trauma image data is greater than or equal to the preset uniformity.

3. The organ injury automatic identification and control system according to claim 2, characterized in that: The trauma identification module determines the type of organ trauma by: The trauma identification module determines that the type of the organ trauma is the first type according to the comparison result that the degree of trauma of the organ is greater than or equal to the preset degree of trauma; The trauma recognition module determines the malignant transformation rate of the organ trauma according to the comparison result that the trauma degree of the organ is less than the preset trauma degree.

4. The organ injury automatic identification and control system according to claim 3, characterized in that: The trauma identification module determines the type of the organ trauma according to the comparison result of the malignant transformation rate of the organ trauma and the preset malignant transformation rate under the condition of determining the malignant transformation rate of the organ trauma, wherein: The trauma identification module determines that the type of the organ trauma is the first type according to the malignant transformation rate of the organ trauma being greater than or equal to the preset malignant transformation rate; The trauma identification module determines whether the organ has a historical trauma according to the malignant transformation rate of the organ trauma being less than a preset malignant transformation rate.

5. The organ injury automatic identification and control system according to claim 4, characterized in that: The trauma identification module determines the type of the organ trauma according to whether the organ has a historical trauma, under the condition of determining whether the organ has a historical trauma. The trauma identification module determines that the type of the organ trauma is the second type according to the existence of historical trauma to the organ; The trauma identification module determines that the type of the organ trauma is the third type based on the absence of historical trauma to the organ.

6. The organ injury automatic identification and control system according to claim 5, characterized in that: The control module determines to upload the organ trauma image to different databases according to the comparison result between the change value of the organ trauma degree and the preset change value, wherein: The control module determines to upload the organ trauma image to the first database according to a comparison result that the change value of the organ trauma degree within the preset time is less than the first preset change value; The control module determines to upload the organ trauma image to the second database according to a comparison result that the change value of the organ trauma degree within the preset time is greater than or equal to the first preset change value and less than the second preset change value; The control module determines to upload the organ trauma image to the third database according to the comparison result that the change value of the organ trauma within the preset time is greater than or equal to the second preset change value.

7. The organ injury automatic identification and control system according to claim 6, characterized in that: The preset change value of the organ trauma is determined according to a preset trauma degree.

8. The organ injury automatic identification and control system according to claim 7, characterized in that: The adjustment module determines the adjustment of the parameters of the automatic organ trauma identification control process according to the comparison result that the accuracy of the automatic organ trauma identification control result is less than the preset accuracy, wherein the parameters of the automatic organ trauma identification control process include a preset uniformity and a preset malignancy rate.

9. The organ injury automatic identification and control system according to claim 8, characterized in that: The adjustment amount of the preset uniformity is negatively correlated with the fluctuation degree of the error types of uploading organ trauma images to different databases during the automatic identification and control process of organ trauma within several preset cycles, and the adjustment amount of the preset malignancy rate is positively correlated with the fluctuation degree of the error types of uploading organ trauma images to different databases during the automatic identification and control process of organ trauma within several preset cycles.

10. The organ injury automatic identification and control system according to claim 8, characterized in that: The value of the preset fluctuation degree is the average value of the fluctuation degrees of the error types in uploading the organ trauma images to different databases during the organ trauma automatic recognition control process within a plurality of preset cycles.

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