A method for medical image quality detection

Abstract

This invention relates to the field of medical image quality inspection technology and discloses a method for medical image quality inspection. The method collects patient body data before and during medical image inspection, and calculates a comprehensive patient quality influence coefficient based on the patient's body influence coefficient and motion influence coefficient. It also collects equipment data during the medical image inspection to construct an equipment influence coefficient. After the equipment outputs the medical image, it reads both the comprehensive patient quality influence coefficient and the equipment influence coefficient. If either the comprehensive quality influence coefficient or the equipment influence coefficient exceeds a corresponding threshold, a quality warning command is executed. If neither the comprehensive quality influence coefficient nor the equipment influence coefficient exceeds the corresponding threshold, a quality pass command is issued. This ensures that the quality of medical images can be evaluated directly on-site, allowing inspectors to promptly identify problems.

Description

Technical Field

[0001] This invention relates to the field of medical image quality testing technology, specifically a method for medical image quality testing. Background Technology

[0002] Medical imaging primarily includes X-rays, computed tomography (CT) scans, and magnetic resonance imaging (MRI). These methods capture images of the human body's interior for physical examination and play a crucial role in disease detection. Medical imaging helps doctors quickly pinpoint the cause of illness and develop treatment plans by visualizing lesions; therefore, high-quality and accurate medical images are essential.

[0003] In actual radiological examinations, factors such as the skill level of the examiners can lead to deviations in the quality of medical images. Current quality control methods for medical images generally rely on post-examination random sampling and evaluation, followed by instruction to the examiners. This method lacks real-time relevance to the sampled images; by the time a sampled image is found to be substandard, the patient has already left, and re-summarizing them is time-consuming and labor-intensive. Existing technologies rarely offer methods for directly evaluating the quality of medical images on-site, enabling examiners to promptly identify problems and make adjustments for re-shooting. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a medical image quality detection method that has the advantages of timely evaluation of medical image quality, thereby enabling timely detection of imaging defects and solving the aforementioned technical problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for medical image quality detection, comprising the following steps:

[0006] S1: Collect patient body data before medical imaging examination and patient movement data during medical imaging examination;

[0007] S2: Based on a comprehensive analysis of patient body data and image data of the patient during medical imaging examination, the patient body influence coefficient and patient motion influence coefficient are obtained respectively;

[0008] S3: The overall patient quality impact coefficient is calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient.

[0009] S4: Collect equipment data of patients during medical imaging examinations, and construct equipment influence coefficients based on comprehensive analysis of the equipment data of patients during medical imaging examinations;

[0010] S5: After the device outputs medical images, read the patient's overall quality impact coefficient and the device's impact coefficient respectively. If either the overall quality impact coefficient or the device's impact coefficient exceeds the corresponding threshold, execute the quality warning command. If neither the overall quality impact coefficient nor the device's impact coefficient exceeds the corresponding threshold, issue the quality qualified command.

[0011] As a preferred embodiment of the present invention, the specific expression for collecting the patient's physical data before medical imaging examination in step S1 is as follows:

[0012]

[0013] in, This represents the patient's physical data. These represent the times recorded by the patients themselves on the same day. Height values ​​at different times These represent the times recorded by the patients themselves on the same day. The patient's weight values ​​at different times were calculated. The specific expression is as follows:

[0014]

[0015] in, Indicates to Summation, Indicates the patient's BMI value. This indicates the first day recorded by the patient themselves. Individual height value, This indicates the first day recorded by the patient themselves. Individual weight value.

[0016] As a preferred embodiment of the present invention, the specific steps for collecting motion data of the patient during medical imaging examination in step S1 are as follows:

[0017] S1.1: Obtain images of the patient lying flat and construct the patient's body proportion factor;

[0018] S1.2: Monitor the patient's respiratory rate during medical imaging examinations and obtain the respiratory fluctuation factor;

[0019] S1.3: Monitor the patient's limb movements during medical imaging examinations and obtain limb movement factors;

[0020] S1.4: Store the patient's respiratory rate and limb activity factors in the patient motion dataset, as shown in the following expression:

[0021]

[0022] in, Indicates respiratory fluctuation factor. Indicates limb activity factor, This represents the patient motion dataset.

[0023] As a preferred embodiment of the present invention, the specific expression for acquiring the patient's image after lying flat and constructing the patient's body proportion factor in step S1.1 is as follows:

[0024]

[0025] in, Indicates the patient's body size proportion factor. Indicates the area of ​​the patient's body. Indicates the area of ​​the examination bed;

[0026] In step S1.2, the respiratory rate of the patient is monitored during medical imaging examination, and the specific expression of the respiratory fluctuation factor is as follows:

[0027]

[0028] in, This represents the average respiratory rate of the patient during medical imaging examinations. This indicates the maximum respiratory rate of the patient during medical imaging examinations. Indicates respiratory fluctuation factor;

[0029] In step S1.3, the patient's limb movements during medical imaging are monitored, and the specific expression for the limb movement factor is obtained as follows:

[0030]

[0031] in, Indicates limb activity factor, This represents the area of ​​a patient's limb movement, obtained through image comparison. This indicates the area of ​​the patient's body.

[0032] As a preferred embodiment of the present invention, the expressions for the patient's body influence coefficient and patient's motion influence coefficient derived from the comprehensive analysis of patient body data and image data during medical imaging examination in step S2 are as follows:

[0033]

[0034]

[0035] in, Indicates the patient's BMI value. Indicates the patient's body size proportion factor. This represents the maximum BMI value of patients currently stored in the database. Indicates the patient's physical impact coefficient. Indicates the patient's motion influence coefficient. Indicates respiratory fluctuation factor. This indicates the factor of limb movement.

[0036] As a preferred embodiment of the present invention, the expression for the patient's overall quality impact coefficient, calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient in step S3, is as follows:

[0037]

[0038] in, Indicates the patient's physical impact coefficient. Indicates the patient's motion influence coefficient. These represent the weight coefficients that sum to 1. This represents the impact coefficient on the patient's overall quality.

[0039] As a preferred embodiment of the present invention, the specific expression for collecting the device data of the patient during medical imaging examination in step S4 is as follows:

[0040]

[0041] in, Represents the device dataset. They represent the 1st The parameters affecting each device are obtained through the device logs.

[0042] As a preferred embodiment of the present invention, the specific expression for constructing the equipment influence coefficient based on the comprehensive analysis of equipment data during medical imaging examination in step S4 is as follows:

[0043]

[0044] in, Indicates the equipment impact coefficient. Indicates the first Each device affects parameters. This indicates the parameters affecting a total of J devices. Summation, express The absolute value, Indicates the first The standard values ​​corresponding to the parameters affecting each device.

[0045] As a preferred technical solution of the present invention, when the comprehensive quality influence coefficient Exceeding the overall quality impact threshold If the quality warning command is not executed, it will be sent to the doctor via data transmission. The doctor will then determine whether a re-enhancing procedure is necessary. If the overall quality impact coefficient is low... Not exceeding the overall quality impact threshold When the time is right, a comprehensive quality pass result will be issued;

[0046] When the equipment influence coefficient Exceeding the equipment influence coefficient threshold When the equipment's influence coefficient is [a certain value], a quality warning command will be executed. Not exceeding the equipment impact factor threshold If the equipment is deemed to be of acceptable quality, a result indicating that the equipment is qualified will be issued.

[0047] As a preferred technical solution of the present invention, when the comprehensive quality qualification result and the equipment quality qualification result are issued simultaneously, a quality qualification instruction is issued to determine that the current medical image is qualified.

[0048] When the comprehensive quality impact coefficient Exceeding the overall quality impact threshold And when the equipment influence coefficient Exceeding the equipment influence coefficient threshold If the time is right, a repeat command will be issued directly.

[0049] Compared with the prior art, the present invention provides a method for medical image quality detection, which has the following beneficial effects:

[0050] This invention collects patient body data before and during medical imaging examinations, as well as patient movement data. Based on the patient's body influence coefficient and movement influence coefficient, a comprehensive patient quality influence coefficient is calculated. Equipment data during the medical imaging examination is also collected and analyzed to construct an equipment influence coefficient. After the equipment outputs the medical image, both the comprehensive patient quality influence coefficient and the equipment influence coefficient are read. If either the comprehensive quality influence coefficient or the equipment influence coefficient exceeds a corresponding threshold, a quality warning command is executed. If neither the comprehensive quality influence coefficient nor the equipment influence coefficient exceeds the corresponding threshold, a quality pass command is issued. This method ensures that the quality of medical images can be directly evaluated on-site, allowing examiners to promptly identify problems and make adjustments for re-enhancing the image. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Please see Figure 1 A method for detecting the quality of medical images, comprising the following steps:

[0054] S1: Collect patient's physical data before medical imaging examination and patient's motion data during medical imaging examination. Combining the motion data during the examination helps to promptly identify abnormalities caused by the patient's own factors, so as to take corresponding measures to adjust or remedy the situation.

[0055] The specific expression for collecting patient physical data before medical imaging examination in S1 is as follows:

[0056]

[0057] in, This represents the patient's physical data. These represent the times recorded by the patients themselves on the same day. Height values ​​at different times These represent the times recorded by the patients themselves on the same day. The patient's weight values ​​at different times were calculated. The specific expression is as follows:

[0058]

[0059] in, Indicates to Summation, Indicates the patient's BMI value. This indicates the first day recorded by the patient themselves. Individual height value, This indicates the first day recorded by the patient themselves. Individual weight value.

[0060] The specific steps for collecting patient motion data during medical imaging examinations in S1 are as follows:

[0061] S1.1: Obtain images of the patient lying flat and construct the patient's body proportion factor;

[0062] S1.2: Monitor the patient's respiratory rate during medical imaging examinations and obtain the respiratory fluctuation factor;

[0063] S1.3: Monitor the patient's limb movements during medical imaging examinations and obtain limb movement factors;

[0064] S1.4: Store the patient's respiratory rate and limb activity factors in the patient motion dataset, as shown in the following expression:

[0065]

[0066] in, Indicates respiratory fluctuation factor. Indicates limb activity factor, This represents the patient motion dataset.

[0067] The specific expression for obtaining the patient's image while lying flat in S1.1 and constructing the patient's body proportion factor is as follows:

[0068]

[0069] in, Indicates the patient's body size proportion factor. Indicates the area of ​​the patient's body. This indicates the area of ​​the examination bed, which can reflect the impact of the patient's body size.

[0070] In S1.2, the respiratory rate of the patient is monitored during medical imaging examinations, and the specific expression of the respiratory fluctuation factor is as follows:

[0071]

[0072] in, This represents the average respiratory rate of the patient during medical imaging examinations. This indicates the maximum respiratory rate of the patient during medical imaging examinations. Indicates respiratory fluctuation factor;

[0073] S1.3 monitors the patient's limb movements during medical imaging examinations, and the specific expression for the limb movement factor is as follows:

[0074]

[0075] in, Indicates limb activity factor, This indicates the area of ​​limb movement in a patient's body, obtained through image comparison. It reflects the movement of the remaining limbs before and after medical imaging, indicating how the movement of the other limbs affected the medical images. Indicates the area of ​​the patient's body;

[0076] S2: Based on a comprehensive analysis of patient body data and image data during medical imaging examinations, the patient's body influence coefficient and motion influence coefficient are derived. This approach comprehensively considers both body and image data, analyzing the patient's condition from multiple perspectives. Body data provides static physiological information about the patient, while image data reflects the actual imaging process. Combining both allows for a more comprehensive assessment of the impact of patient factors on medical imaging examinations, yielding separate body and motion influence coefficients, clearly distinguishing the individual effects of body and motion factors on the examination.

[0077] S3: The comprehensive quality impact coefficient of the patient is calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient. By calculating a unified coefficient, it is possible to make a decision based on the comparison between this comprehensive coefficient and the threshold in subsequent quality control and early warning judgment without having to consider multiple complex influencing factors separately. This greatly simplifies the decision-making process and improves work efficiency.

[0078] S4: Collect equipment data during patient medical imaging examinations, and construct the equipment influence coefficient based on the comprehensive analysis of the equipment data during patient medical imaging examinations. The equipment influence coefficient is an important indicator for evaluating the impact of equipment on the test results. It can help operators to discover potential problems with the equipment in a timely manner and take corresponding maintenance or adjustment measures to ensure that the equipment is always in the best working condition, thereby ensuring the quality of medical imaging examinations.

[0079] S5: After the device outputs medical images, read the patient's overall quality impact coefficient and the device's impact coefficient respectively. If either the overall quality impact coefficient or the device's impact coefficient exceeds the corresponding threshold, execute the quality warning command. If neither the overall quality impact coefficient nor the device's impact coefficient exceeds the corresponding threshold, issue the quality qualified command.

[0080] The expressions for the patient's body influence coefficient and patient's motion influence coefficient, derived from the comprehensive analysis of patient body data and image data during medical imaging examination in S2, are as follows:

[0081]

[0082]

[0083] in, Indicates the patient's BMI value. The body proportion factor indicates the patient's body size. Patients with higher body weight or more fat distribution may experience reduced tissue contrast in images, affecting the visibility of details. For example, abdominal obesity may affect the clarity of abdominal CT or MRI images. Obese patients may also increase the probability of motion artifacts during imaging, especially in CT scans, increasing image noise and distortion, and reducing image quality and accuracy. This represents the maximum BMI value of patients currently stored in the database. Indicates the patient's physical impact coefficient. Indicates the patient's motion influence coefficient. Indicates respiratory fluctuation factor. This indicates the factor of limb movement.

[0084] The expression for the patient's overall quality impact coefficient, calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient in S3, is as follows:

[0085]

[0086] in, Indicates the patient's physical impact coefficient. Indicates the patient's motion influence coefficient. These represent the weight coefficients that sum to 1. This represents the impact coefficient on the patient's overall quality.

[0087] The specific expression for collecting device data from patients during medical imaging examinations in S4 is as follows:

[0088]

[0089] in, Represents the device dataset. They represent the 1st The parameters affecting each device are obtained through the device logs.

[0090] The specific expression for constructing the equipment influence coefficient in S4 based on the comprehensive analysis of equipment data during patient medical imaging examinations is as follows:

[0091]

[0092] in, Indicates the equipment impact coefficient. Indicates the first Each device affects parameters. This indicates the parameters affecting a total of J devices. Summation, express The absolute value, Indicates the first The standard values ​​corresponding to the parameters affecting each device.

[0093] When the comprehensive quality impact coefficient Exceeding the overall quality impact threshold If the overall quality impact coefficient is too high, a quality warning instruction will be executed. Specifically, the currently collected medical image will be transmitted to the doctor for review. The doctor will then determine whether a re-enhancing procedure is necessary. Not exceeding the overall quality impact threshold When the time is right, a comprehensive quality pass result will be issued;

[0094] When the equipment influence coefficient Exceeding the equipment influence coefficient threshold When the equipment's influence coefficient is [a certain value], a quality warning command will be executed. Not exceeding the equipment impact factor threshold If the equipment is deemed to be of acceptable quality, a result indicating that the equipment is qualified will be issued.

[0095] When both the overall quality pass result and the equipment quality pass result are issued simultaneously, a quality pass instruction is issued to determine that the current medical image is qualified.

[0096] When the comprehensive quality impact coefficient Exceeding the overall quality impact threshold And when the equipment influence coefficient Exceeding the equipment influence coefficient threshold If the time is right, a repeat command will be issued directly.

[0097] Example

[0098] The data recorded in this embodiment is shown in Table 1 below:

[0099] Table 1

[0100]

[0101] At this point, the calculation yields... 0.342, 0.0515, =0.18513 is less than 0.65 and does not exceed the overall quality impact threshold. The overall quality is deemed satisfactory.

[0102] The equipment data for patients undergoing medical imaging examinations are shown in Table 2 below:

[0103] Table 2

[0104]

[0105] At this point, the calculation yields... 0.058 does not exceed the equipment influence coefficient threshold. Issue the equipment quality qualified result.

[0106] After the comprehensive quality qualified result and the equipment quality qualified result are issued simultaneously, issue the quality qualified instruction to determine that the current medical image is qualified.

[0107] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for detecting the quality of medical images, characterized in that: Includes the following steps: S1: Collect patient's physical data before and during medical imaging examinations, as well as the patient's motion data during the medical imaging examinations. The specific expression is as follows: Where STSJ represents patient physical data, SG1,…,SG i ,…,SG I These represent height values ​​recorded by the patient at different times (1 to I) on the same day, TZ1, ..., TZ. i ,…,TZ I These represent the patient's weight values ​​at different times (1 to I) on the same day, recorded by the patient themselves, and the patient's BMI is calculated using the following expression: in, Indicates to Summation, BMI represents the patient's BMI value, SG i TZ represents the i-th height value recorded by the patient on the same day. i This represents the i-th weight value recorded by the patient on the same day; The specific steps for collecting patient motion data during medical imaging examination in step S1 are as follows: S1.1: Obtain the image of the patient lying flat, and construct the patient's body proportion factor from the image of the patient lying flat. The specific expression is as follows: Where HZBLYZ represents the patient body size ratio factor, XSMJ represents the patient area area, and YLC represents the examination bed area area. S1.2: Monitor the patient's respiratory rate during medical imaging examinations and obtain the respiratory fluctuation factor, the specific expression of which is as follows: in, This represents the mean respiratory rate (HXPL) of the patient during medical imaging examinations. max HXBDYZ represents the maximum respiratory rate of a patient during medical imaging examinations; HXBDYZ represents the respiratory fluctuation factor. S1.3: Monitor the patient's limb movements during medical imaging examinations and obtain the limb movement factor, the specific expression of which is as follows: Wherein, ZTHDYZ represents the limb activity factor, HDQYMJ represents the area of ​​the patient's limb activity region obtained through image comparison, and XSMJ represents the area of ​​the patient's region. S1.4: Store the patient's respiratory rate and limb activity factors in the patient motion dataset, as shown in the following expression: YDSJJ=[HXBDYZ,ZTHDYZ] Wherein, HXBDYZ represents the respiratory fluctuation factor, ZTHDYZ represents the limb activity factor, and YDSJJ represents the patient motion dataset; S2: Based on a comprehensive analysis of patient body data and patient motion data during medical imaging examinations, the patient body influence coefficient and patient motion influence coefficient are obtained respectively. S3: The overall patient quality impact coefficient is calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient. S4: Collect equipment data of patients during medical imaging examinations, and construct equipment influence coefficients based on comprehensive analysis of the equipment data of patients during medical imaging examinations; S5: After the device outputs medical images, read the patient's overall quality impact coefficient and the device's impact coefficient respectively. If either the overall quality impact coefficient or the device's impact coefficient exceeds the corresponding threshold, execute the quality warning command. If neither the overall quality impact coefficient nor the device's impact coefficient exceeds the corresponding threshold, issue the quality qualified command.

2. The medical image quality detection method according to claim 1, characterized in that: The expressions for the patient's body influence coefficient and patient's motion influence coefficient obtained in S2 based on the comprehensive analysis of the patient's body data and motion data during medical imaging examination are as follows: YDYXXS=HXBDYZ*(1+ZTHDYZ) Where BMI represents the patient's BMI value, and HZBLYZ represents the patient's body proportion factor. max This represents the maximum BMI value of the patient currently stored in the database. STYXXS represents the patient's physical influence coefficient, YDYXXS represents the patient's exercise influence coefficient, HXBDYZ represents the respiratory fluctuation factor, and ZTHDYZ represents the limb activity factor.

3. The medical image quality detection method according to claim 2, characterized in that: The expression for the patient's overall quality impact coefficient, calculated based on the patient's physical impact coefficient and the patient's movement impact coefficient in S3, is as follows: HZZLYX=ω1*STYXXS+ω2*YDYXXS Wherein, STYXXS represents the patient's physical impact coefficient, YDYXXS represents the patient's exercise impact coefficient, ω1 and ω2 represent weight coefficients that sum to 1, and HZZLYX represents the patient's overall quality impact coefficient.

4. The medical image quality detection method according to claim 3, characterized in that: The specific expression for collecting device data from the patient during medical imaging examination in step S4 is as follows: SBZS=[sbcs1,…,sbcs j ,…,sbcs J ] Where SBZS represents the device dataset, sbcs1,…,sbcs j ,…,sbcs J These represent the impact parameters of devices 1 through J, obtained from device logs.

5. The medical image quality detection method according to claim 4, characterized in that: The specific expression for constructing the equipment influence coefficient based on the comprehensive analysis of equipment data during medical imaging examinations in S4 is as follows: Where SBYXXS represents the equipment influence coefficient, and sbcs j This represents the parameter affecting the j-th device. This indicates the parameters affecting a total of J devices. To perform summation, |sbcs j -sbcs j,0 | indicates sbcs j -sbcs j,0 The absolute value of sbcs j,0 This represents the standard value corresponding to the influence parameter of the j-th device.

6. The medical image quality detection method according to claim 5, characterized in that: When the comprehensive quality impact coefficient HZZLYX exceeds the comprehensive quality impact threshold HZZLYX yz If the situation is as described, a quality warning instruction will be executed. Specifically, the currently collected medical impact data will be transmitted to the doctor for review. The doctor will then determine whether a re-enhancing procedure is necessary. If the overall quality impact coefficient HZZLYX does not exceed the overall quality impact threshold HZZLYX... yz When the time is right, a comprehensive quality pass result will be issued; When the equipment influence coefficient SBYXXS exceeds the equipment influence coefficient threshold SBYXXS yz If the equipment influence coefficient SBYXXS does not exceed the equipment influence coefficient threshold SBYXXS, a quality warning command will be executed. yz If the equipment is deemed to be of acceptable quality, a result indicating that the equipment is qualified will be issued.

7. A method for detecting medical image quality according to claim 6, characterized in that: When both the overall quality pass result and the equipment quality pass result are issued simultaneously, a quality pass instruction is issued to determine that the current medical image is qualified. When the comprehensive quality impact coefficient HZZLYX exceeds the comprehensive quality impact threshold HZZLYX yz Furthermore, when the equipment influence coefficient SBYXXS exceeds the equipment influence coefficient threshold SBYXXS yz If the time is right, a repeat command will be issued directly.

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