A method, device, medium, and program product for low-power display of medical images.

Abstract

This invention discloses a low-power display method, device, medium, and program product for medical images, relating to the field of image processing. The method includes: acquiring an initial medical image; performing identification processing on the initial medical image using a preset key diagnostic recognition model to determine key diagnostic areas in the initial medical image; based on the initial medical image, identifying areas outside the key diagnostic areas as non-key diagnostic areas; reducing the brightness and contrast of the non-key diagnostic areas to obtain a weakened image of the non-key diagnostic areas; generating an adjusted medical image based on the weakened images of the key and non-key diagnostic areas; and sending the adjusted medical image to a medical image display module. This invention, through the above method, can effectively reduce the power consumption of the display module while ensuring continuous high-definition display of medical images, achieving the goal of low-power display of medical images.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a low-power display method, device, medium, and program product for medical images. Background Technology

[0002] With the continuous development of medical technology, the requirements for resolution and clarity of medical images are becoming increasingly stringent. Currently, 4K and even 8K ultra-high-definition displays have emerged. Ultra-high-definition medical display modules can meet doctors' needs for observing image details, improving the accuracy and efficiency of diagnosis. At the same time, medical image display modules often need to operate for extended periods to support continuous monitoring and surgical procedures.

[0003] Based on the factors mentioned above, the power consumption of medical image display modules often remains at a high level. Therefore, reducing the power consumption of medical image display modules is crucial. This not only helps reduce energy consumption and costs but also reduces device heat generation, improves device stability and lifespan. Furthermore, for portable medical devices, low power consumption means longer battery life, thereby improving the efficiency and quality of medical services while ensuring patient safety and comfort.

[0004] Therefore, there is an urgent need for a technical solution that can reduce the power consumption of the display module while ensuring the continuous high-definition display of medical images. Summary of the Invention

[0005] To address the aforementioned technical problems and deficiencies, the purpose of this invention is to provide a low-power display method, device, medium, and program product for medical images, which can effectively reduce the power consumption of the display module while ensuring continuous high-definition display of medical images, thereby achieving the goal of low-power display of medical images.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a low-power display method for medical images, comprising: acquiring an initial medical image; performing identification processing on the initial medical image using a preset key diagnostic recognition model to determine key diagnostic areas in the initial medical image; determining areas outside the key diagnostic areas as non-key diagnostic areas based on the initial medical image; performing brightness and contrast reduction processing on the non-key diagnostic areas to obtain a weakened image of the non-key diagnostic areas; generating an adjusted medical image based on the weakened images of the key and non-key diagnostic areas; and sending the adjusted medical image to a medical image display module.

[0007] This invention utilizes a key diagnostic recognition model to process initial medical images and identify key diagnostic areas, ensuring accurate identification of the critical regions most relevant to doctors. Next, areas outside the key diagnostic areas are designated as non-key diagnostic areas. These non-key diagnostic areas undergo brightness and contrast reduction processing to obtain a weakened image. This reduces display power consumption in non-key areas, as reduced brightness and contrast decrease the energy consumed by the display module in these areas. Then, an adjusted medical image is generated based on the weakened images of the key and non-key diagnostic areas. The key diagnostic areas maintain high-definition display to meet doctors' needs for observing image details, while the processed non-key diagnostic areas reduce power consumption without affecting the overall diagnosis. Finally, the adjusted medical image is sent to the medical image display module, achieving low-power display of medical images while maintaining consistently high-definition display.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, brightness reduction and contrast reduction processing are performed on non-critical diagnostic areas to obtain a weakened image of non-critical diagnostic areas, including: confirming the current ambient light brightness of the environment in which the medical image display module is located; and performing brightness reduction and contrast reduction processing on non-critical diagnostic areas according to the current ambient light brightness to obtain a weakened image of non-critical diagnostic areas.

[0009] The technical solution described in the above embodiments dynamically adjusts the brightness and contrast of non-critical diagnostic areas by considering the ambient light intensity of the medical image display module, thereby achieving energy savings. This method ensures that the display's energy consumption is optimized under different lighting conditions while maintaining image readability. This adaptive adjustment is particularly important in situations with significant ambient light variations, such as mobile medical devices or outdoor medical applications.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the brightness of non-critical diagnostic areas is reduced based on the current ambient light intensity, including: reducing the brightness of non-critical diagnostic areas using a brightness adjustment formula, the brightness adjustment formula including:

[0011] ;

[0012] in, I ( p () represents pixels in the non-critical diagnostic area. p The original brightness, I ′( p () is a pixel. p The adjusted brightness L env This refers to the current ambient light level. L refIt is based on ambient light brightness. I max It is the maximum possible brightness value of the image. a It is the experimental coefficient.

[0013] The technical solution described in the above embodiments reduces the brightness of non-critical diagnostic areas using a specific brightness adjustment formula. This formula considers ambient light brightness, original pixel brightness, and the maximum image brightness value. This brightness-based adjustment helps reduce energy consumption while maintaining the visibility of critical information in the image. Especially in bright environments, it reduces the backlight requirement of the display, thereby lowering overall power consumption.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, contrast reduction processing is applied to non-critical diagnostic areas based on the current ambient light intensity, including: applying contrast reduction processing to non-critical diagnostic areas using a contrast adjustment formula, the contrast adjustment formula including:

[0015]

[0016] in, C ( p () represents pixels in the non-critical diagnostic area. p The original contrast, C ′( p () is a pixel. p Adjusted contrast L env This refers to the current ambient light level. L ref It is based on ambient light brightness. C max It is the maximum possible contrast value of the image. b These are experimental parameters.

[0017] The technical solution described in the above embodiments provides a contrast adjustment formula for reducing the contrast of non-critical diagnostic areas, while taking into account ambient light intensity and the maximum contrast value of the image. This adjustment helps optimize the visual quality of the image without excessive energy consumption, ensuring that the details and depth of the image are appropriately displayed under different lighting conditions, thereby improving the visual effect of the image and the accuracy of diagnosis.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after acquiring the initial medical image, the method further includes: determining the degree of change in the image content of the initial medical image; and adjusting the screen refresh rate of the medical image display module according to the degree of change in the image content.

[0019] By employing the technical solution described in the above embodiments, power consumption is further reduced by monitoring the degree of change in image content and adjusting the screen refresh rate accordingly. This method is particularly suitable for processing dynamic medical images, such as real-time monitoring or video streams. By reducing unnecessary screen refreshes, energy consumption can be significantly reduced while ensuring image smoothness and real-time performance.

[0020] In conjunction with some embodiments of the first aspect, in some embodiments, adjusting the screen refresh rate of the medical image display module according to the degree of change in image content includes: adjusting the screen refresh rate using a refresh rate adjustment formula, the refresh rate adjustment formula including:

[0021]

[0022] in, R ′ is the adjusted screen refresh rate. R base It is the base screen refresh rate, Δ I ( τ ) is in time τ The degree of change in image content between two consecutive frames. I threshold It is a preset threshold. T It is a time window that takes into account changes in image content. α and β It's about adjusting the parameters.

[0023] The technical solution described in the above embodiments uses a refresh rate adjustment formula to reasonably adjust the screen refresh rate, taking into account the cumulative effect of image content changes over time. This method can more accurately capture the dynamic characteristics of image changes, making the refresh rate adjustment more precise and reasonable, thereby effectively reducing the power consumption of the display device while maintaining image quality.

[0024] In conjunction with some embodiments of the first aspect, in some embodiments, after determining the area outside the critical diagnostic area as a non-critical diagnostic area based on the initial medical image, the method further includes: performing brightness enhancement and contrast enhancement processing on the critical diagnostic area according to the current ambient light intensity.

[0025] The technical solution of the above embodiments, after determining the non-critical diagnostic areas, also considers enhancing the brightness and contrast of the critical diagnostic areas based on ambient light. This enhancement helps improve the visibility of critical areas under low light or specific visual conditions, ensuring that doctors can clearly see important diagnostic information, thereby improving the accuracy of diagnosis and the effectiveness of treatment.

[0026] In a second aspect, embodiments of the present invention provide an electronic device, including: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors calling the computer instructions to cause the electronic device to perform the method described in the first aspect or the second aspect, and any possible implementation thereof.

[0027] Thirdly, the present invention provides a computer-readable storage medium including instructions that, when executed on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect, and any possible implementation thereof.

[0028] Fourthly, the present invention provides a computer program product comprising instructions that, when the computer program product is run on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect, and any possible implementation thereof.

[0029] Understandably, the electronic device provided in the second aspect, the storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the method provided by this invention. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0030] One or more technical solutions provided by this invention have at least the following technical effects or advantages:

[0031] 1. Balance between energy saving and display effect: This invention achieves an optimized balance between energy saving and display effect. By distinguishing between critical and non-critical diagnostic areas and selectively reducing the brightness and contrast of non-critical areas, while dynamically adjusting the screen refresh rate according to the ambient light, this invention effectively reduces the power consumption of the display module, extends the service life of the device, and reduces energy consumption while ensuring that critical medical image information is clearly visible.

[0032] 2. Environmental Adaptability: By monitoring ambient light levels in real time and dynamically adjusting image brightness, contrast, and refresh rate accordingly, this invention ensures a comfortable visual experience under varying lighting conditions. This adaptive adjustment not only improves image readability but also reduces unnecessary high-brightness displays in bright environments, thereby further reducing energy consumption.

[0033] 3. Dynamic Image Quality Optimization: By real-time monitoring of changes in image content and adjusting the refresh rate accordingly, as well as enhancing the brightness and contrast of key diagnostic areas, this invention can optimize the image display process by reducing unnecessary processing and data transmission while maintaining image quality. This not only improves the user experience but also ensures that key information from medical images is accurately conveyed under various conditions, thereby improving diagnostic accuracy and treatment effectiveness. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0035] Figure 1 This is a flowchart of a low-power display method for medical images according to an embodiment of the present invention;

[0036] Figure 2 This is a flowchart of another low-power display method for medical images according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the architecture of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0038] The terminology used in the following embodiments of the present invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the invention, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in the invention refers to any or all possible combinations comprising one or more of the listed items.

[0039] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of the present invention, unless otherwise stated, "a plurality of" means two or more.

[0040] It should also be noted that, unless otherwise explicitly specified and limited, the terms "setting" and "connection" in the embodiments of the present invention should be interpreted broadly. For example, "connection" 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 an indirect connection through an intermediate medium; it can be a connection within two components; it can be a wired communication connection or a wireless communication connection. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances. The embodiments of the present invention will be described in detail below.

[0041] This invention provides a low-power display method for medical images, such as... Figure 1 As shown, it includes the following steps:

[0042] Step 201: Obtain the initial medical image.

[0043] Initial medical images can be acquired using medical imaging equipment such as computed tomography (CT), magnetic resonance imaging (MRI), X-ray machines, and ultrasound equipment. These medical imaging devices capture structural and functional information about the human body according to specified medical needs, generating digital images containing the details required for diagnosis. These images are then stored and transmitted digitally through a connected data processing system for analysis and diagnosis by doctors and clinical staff.

[0044] Step 202: The initial medical image is processed by a preset key diagnostic recognition model to determine the key diagnostic areas in the initial medical image.

[0045] The critical diagnostic area refers to specific regions in medical images that have a decisive impact on diagnostic and treatment decisions. These regions typically contain important pathological features or anatomical structures, such as tumors, blood vessels, diseased tissues, or bone structures. They are crucial for doctors to conduct medical activities such as condition assessment, disease diagnosis, treatment planning, and surgical navigation. Therefore, they need to be displayed at high resolution and high contrast to ensure that doctors can accurately identify and analyze this critical information.

[0046] In this embodiment, the key diagnostic identification model is trained to accurately identify key diagnostic regions. This model automatically analyzes the initial medical image, using image processing techniques such as edge detection, feature extraction, segmentation, and classification to determine the key diagnostic regions within the image. The model outputs a probability map or directly marks the key regions.

[0047] The training process for the key diagnostic identification model is a machine learning workflow involving large amounts of data and complex computations, designed to enable the model to accurately identify key diagnostic regions from medical images. The following is a detailed description of the training process:

[0048] 1) Data collection and preprocessing:

[0049] A large amount of medical image data is collected as training sample data, which may come from different imaging modalities, such as CT, MRI, X-ray, etc.

[0050] Image preprocessing, including denoising, standardization, and resizing, is performed to improve the efficiency and effectiveness of model training.

[0051] 2) Labeling:

[0052] Key diagnostic areas in the images are labeled by professional doctors or technicians. This may include marking the boundaries of lesions and identifying specific anatomical structures.

[0053] The annotation process provides the model with the "correct answer" needed for training, that is, the output that the model needs to learn.

[0054] 3) Selecting a model architecture:

[0055] Choosing the right deep learning architecture, such as convolutional neural networks (CNNs), can lead to excellent performance in image recognition tasks.

[0056] 4) Training:

[0057] The model is trained using labeled data. During training, the model learns features through forward propagation and adjusts the weights through backpropagation to minimize the difference between the predictions and the actual labels.

[0058] Techniques such as cross-validation are used to evaluate the model's performance and avoid overfitting.

[0059] 5) Performance evaluation:

[0060] Use independent test sets to evaluate the model's accuracy, sensitivity, specificity, and other metrics.

[0061] Adjust model parameters or redesign network structure based on evaluation results.

[0062] 6) Optimization:

[0063] Based on the performance evaluation results, the model can be tuned, which may include changing the learning rate, increasing regularization, adjusting the number or depth of network layers, etc.

[0064] 7) Verification and Testing:

[0065] The model will be further validated and tested in real-world medical settings to ensure it performs well on real-world data.

[0066] 8) Deployment and Monitoring:

[0067] The trained model is deployed to a clinical environment and its performance is continuously monitored in order to identify and correct any problems in a timely manner.

[0068] Step 203: Based on the initial medical images, the area outside the critical diagnostic area is identified as the non-critical diagnostic area.

[0069] Specifically, by dividing the image into regions, all parts of the initial medical image except for the critical diagnostic areas can be automatically marked as non-critical diagnostic areas. For example, each pixel in the image can be assigned an attribute label, with pixels belonging to the critical diagnostic areas marked as "critical" and the rest marked as "non-critical." In this way, the areas outside the critical diagnostic areas can be clearly identified as non-critical diagnostic areas, providing an accurate basis for subsequent processing operations on different areas.

[0070] Step 204: Reduce the brightness and contrast of the non-critical diagnostic areas to obtain a weakened image of the non-critical diagnostic areas.

[0071] Specifically, after identifying non-critical diagnostic areas, a processing mechanism needs to be established to specifically adjust the image attributes of these areas. For brightness reduction, an appropriate brightness adjustment coefficient can be set. Determining this coefficient requires comprehensive consideration of multiple factors, such as the overall brightness distribution of the initial medical image and the brightness difference between critical and non-critical diagnostic areas. For example, if the overall brightness of the initial medical image is high, a larger brightness reduction coefficient can be selected to ensure a significant reduction in the brightness of non-critical diagnostic areas.

[0072] Next, each pixel within the non-critical diagnostic area is traversed. For each pixel, a new brightness value is calculated based on the brightness adjustment factor. For example, if the original brightness value of a pixel is 250 and the brightness adjustment factor is 0.7, then the adjusted brightness value becomes 175.

[0073] A similar method can be used to reduce contrast. First, determine a contrast adjustment factor, and then adjust the grayscale difference between pixels in the non-critical diagnostic area according to this factor. For example, if two adjacent pixels originally have grayscale values ​​of 180 and 200, resulting in high contrast, after contrast adjustment, assuming the contrast adjustment factor is 0.6, their grayscale difference will decrease, and the new grayscale values ​​may become 185 and 190, thus reducing the contrast.

[0074] By sequentially adjusting the brightness and contrast of all pixels in the non-critical diagnostic areas, the images in these areas can be made relatively dark and blurry. This effectively reduces the power consumption of the display module in non-critical areas without affecting the clear display of the critical diagnostic areas, ultimately resulting in a weakened image in these areas. This processing method satisfies doctors' needs for observing image details in critical diagnostic areas while also achieving the goal of reducing power consumption, which is of great significance for improving the performance and efficiency of medical image display modules.

[0075] Step 205: Generate adjusted medical images based on the attenuated images of critical and non-critical diagnostic areas.

[0076] Specifically, the key diagnostic areas are first identified, and the non-key diagnostic areas, which have been weakened after brightness and contrast reduction processing, are then distinguished. The key diagnostic areas are left unchanged to ensure image detail and clarity in these critical regions.

[0077] Next, the attenuated images of the non-critical diagnostic areas are placed in positions corresponding to the critical diagnostic areas. During this process, it's crucial to ensure a seamless transition between the attenuated images of the critical and non-critical diagnostic areas, resulting in a natural and smooth overall image. Through precise image fusion techniques, the attenuated images of the critical and non-critical diagnostic areas are integrated to ultimately generate the adjusted medical image.

[0078] This adjusted medical image not only highlights important information in key diagnostic areas but also reduces power consumption in non-critical areas, providing an effective solution for medical image display modules to reduce power consumption while ensuring image quality.

[0079] Step 206: Send the adjusted medical image to the medical image display module.

[0080] Specifically, the first step is to ensure the integrity and accuracy of the adjusted medical image data. This can be achieved by performing data verification on the images to confirm that no data loss or corruption occurred during the generation and processing of the images.

[0081] Then, the adjusted medical images are transmitted to the medical image display module using a suitable data transmission channel. This transmission channel can be a wired connection, such as a data cable or fiber optic cable, or a wireless connection, such as Bluetooth or Wi-Fi. During transmission, it is crucial to ensure the stability and speed of data transmission to avoid problems such as image stuttering or distortion.

[0082] Once the image data is successfully transmitted to the medical image display module, the module will parse and display the received image data. Based on the characteristics of the image and its own display parameters, the display module will present the adjusted medical image in a clear and accurate manner for doctors to observe and diagnose.

[0083] This embodiment aims to achieve a balance between high-definition display and low power consumption in medical images. First, a key diagnostic recognition model is used to identify the critical diagnostic areas, ensuring accurate identification of the areas of greatest concern to doctors. Next, areas outside the critical diagnostic areas are designated as non-critical diagnostic areas. These non-critical areas undergo brightness and contrast reduction processing to obtain a weakened image. This reduces display power consumption in non-critical areas, as reduced brightness and contrast decrease the energy consumed by the display module in these areas. Then, an adjusted medical image is generated based on the weakened images of the critical and non-critical diagnostic areas. The critical diagnostic areas maintain high-definition display to meet doctors' needs for image detail observation, while the processed non-critical diagnostic areas reduce power consumption without affecting the overall diagnosis. Finally, the adjusted medical image is sent to the medical image display module, achieving the goal of low-power display of medical images while maintaining consistently high-definition display.

[0084] The following is combined Figure 2 The method of this invention, as described in specific embodiments, includes the following steps:

[0085] Step 301: Obtain the initial medical image.

[0086] Then proceed to steps 302 and 309 respectively.

[0087] Step 302: The initial medical image is processed by a preset key diagnostic recognition model to determine the key diagnostic areas in the initial medical image.

[0088] This step is the same as step 202, and will not be repeated here.

[0089] Step 303: Based on the initial medical images, the area outside the critical diagnostic area is identified as the non-critical diagnostic area.

[0090] This step is the same as step 203, and will not be repeated here.

[0091] Step 304: Confirm the current ambient light level of the environment in which the medical image display module is located.

[0092] Specifically, an ambient light sensor is installed near the medical image display module. This sensor detects the intensity of ambient light and converts it into electrical signals. These signals are then processed and analyzed to determine the specific value of the current ambient light brightness. For example, the ambient light sensor can measure the ambient light brightness at regular intervals (e.g., every few seconds) and send the results to the image processing system.

[0093] Alternatively, other devices or technologies can be used to indirectly determine ambient light levels. For example, a camera can be used to photograph the surrounding environment, and then image analysis algorithms can be used to estimate the ambient light levels. Regardless of the method used, the goal is to accurately obtain the current ambient light level of the environment in which the medical image display module is located, so that non-critical diagnostic areas can be processed more appropriately in subsequent steps based on this information.

[0094] Step 305: Reduce the brightness and contrast of the non-critical diagnostic area according to the current ambient light intensity to obtain a weakened image of the non-critical diagnostic area.

[0095] Once the current ambient light level is obtained, brightness and contrast reduction can be applied to non-critical diagnostic areas based on this information. If the current ambient light level is high, the degree of brightness and contrast reduction in non-critical diagnostic areas can be appropriately increased.

[0096] For example, when the ambient light is very strong, to avoid the non-critical diagnostic areas becoming too glaring and distracting the doctor, the brightness of these areas can be reduced to a lower level, and the grayscale difference between pixels can be further reduced to decrease contrast. Conversely, if the ambient light is low, the reduction in brightness and contrast can be relatively reduced to ensure that the non-critical diagnostic areas still provide some visual information and are not completely illegible. This process can be achieved by adjusting the brightness and contrast parameters of each pixel within the non-critical diagnostic areas.

[0097] To reduce brightness, a new brightness value for each pixel can be calculated based on ambient light intensity and a preset brightness adjustment formula. To reduce contrast, the grayscale difference between pixels can be adjusted based on ambient light intensity and a contrast adjustment algorithm.

[0098] By processing all pixels in the non-critical diagnostic area in this way, a weakened image of the non-critical diagnostic area is finally obtained, which can reduce the power consumption of the display module while adapting to different ambient light levels.

[0099] In some embodiments, the brightness of non-critical diagnostic areas can be reduced using a brightness adjustment formula, which includes:

[0100]

[0101] in, I ( p () represents pixels in the non-critical diagnostic area. p The original brightness, I ′( p () is a pixel. p The adjusted brightness L env This refers to the current ambient light level. L ref It is based on ambient light brightness. I max It is the maximum possible brightness value of the image. a It is the experimental coefficient.

[0102] I max The maximum range of image brightness can be determined by the hardware specifications of the display device or by experimental measurement. L ref and a These parameters can be optimized and determined through a series of experiments and user tests. In actual operation, these parameters may need to be adjusted and calibrated based on specific device performance, usage scenarios, and user feedback to achieve a better balance between visual effects and energy consumption.

[0103] In the brightness adjustment formula, when the ambient light brightness increases, the ratio of the current ambient light brightness to the reference ambient light brightness increases, indicating that the environment becomes brighter.

[0104] logarithmic function The ratio of ambient light intensity is mapped to a nonlinear space. The use of a logarithmic function simulates the nonlinear perception of brightness by the human eye; that is, when the ambient light intensity is low, small changes in brightness have a large impact on the human eye, while when the ambient light intensity is high, the same change in brightness has a small impact on the human eye.

[0105] Experimental coefficient a In the brightness adjustment formula, the intensity of the logarithmic function's influence is adjusted to control the sensitivity of ambient light brightness changes to brightness adjustments in non-critical diagnostic areas.

[0106] The term represents the current pixel. p The difference between the brightness and the maximum brightness. When I ( p ) near I max When the difference is close to 0, it means the brightness adjustment is small; when I ( pWhen the value is small, this difference is large, which means that the brightness adjustment is large.

[0107] It is a brightness adjustment factor that can be dynamically adjusted according to the ambient light brightness and the current pixel brightness to ensure that the brightness of non-critical areas is appropriately reduced under different ambient light conditions.

[0108] Multiply the brightness adjustment factor by the original brightness I ( p ), to obtain the adjusted brightness I ′( p In this way, the brightness of non-critical areas is reduced when the ambient light is high to save energy, while maintaining a high brightness when the ambient light is low to ensure image readability.

[0109] In this embodiment, the contrast of non-critical diagnostic areas can also be reduced using a contrast adjustment formula, which includes:

[0110]

[0111] in, C ( p () represents pixels in the non-critical diagnostic area. p The original contrast, C ′( p () is a pixel. p Adjusted contrast L env This refers to the current ambient light level. L ref It is based on ambient light brightness. C max It is the maximum possible contrast value of the image. b These are experimental parameters.

[0112] C max It can be obtained through technical parameters or experimental measurements. It defines the upper limit of contrast adjustment, ensuring that the image maintains optimal visual clarity at different brightness levels.

[0113] b This is an experimental parameter used to adjust the impact of changes in ambient light intensity on contrast adjustment. This parameter is optimized through a series of experiments and user tests to achieve suitable image contrast under different ambient lighting conditions, while also considering visual comfort and energy efficiency. In practical applications, b The value may need to be adjusted and calibrated based on the specific performance of the device, changes in ambient lighting, and user preferences.

[0114] This term maps the ambient light intensity ratio to a nonlinear space. This nonlinear term is obtained through experimental parameters. b Adjustments are made to control the magnitude of the contrast adjustment.

[0115] This term represents the difference between the contrast of the current pixel and the maximum contrast. When C ( p ) near C max When this difference is close to 0, it means the contrast adjustment is small; when C ( p When the difference is small, the difference is large, which means that the contrast adjustment is large.

[0116] This is the contrast adjustment factor. This factor is dynamically adjusted based on ambient light intensity and the current pixel's contrast to ensure that the contrast of non-critical diagnostic areas is appropriately adjusted or reduced under different ambient light conditions. Multiply the contrast adjustment factor by the original contrast. C ( p ), to obtain the adjusted contrast C ′( p ).

[0117] This contrast adjustment formula, by comprehensively considering ambient light brightness, image contrast, and flexible adjustment parameters, reasonably achieves contrast reduction processing for non-critical diagnostic areas. This reduces display power consumption while maintaining key diagnostic information in medical images, demonstrating its effectiveness and practicality in medical image display.

[0118] Step 306: Based on the current ambient light level, perform brightness enhancement and contrast enhancement processing on the key diagnostic area.

[0119] Specifically, after determining the current ambient light intensity, its impact on the display effect of the critical diagnostic area is analyzed. If the ambient light intensity is high, the image in the critical diagnostic area may appear unclear and less prominent. In this case, appropriate brightness enhancement and contrast enhancement processing is required. Appropriate brightness enhancement and contrast enhancement coefficients can be calculated based on the ambient light intensity value and a preset enhancement algorithm. For brightness enhancement, the brightness value of each pixel within the critical diagnostic area is adjusted individually, increasing its brightness value according to the enhancement coefficient, so that the critical diagnostic area remains clearly visible even in strong light conditions.

[0120] For example, if a pixel's original brightness value is 150 and the enhancement factor is 1.2, the adjusted brightness value becomes 180. Contrast enhancement is achieved by adjusting the grayscale difference between pixels within the critical diagnostic area. For instance, if two adjacent pixels originally have grayscale values ​​of 120 and 130, after contrast enhancement, their grayscale difference might increase to 110 and 140, making the critical diagnostic area more vivid and prominent. If the ambient light is low, brightness and contrast enhancement can also be appropriately applied to ensure the critical diagnostic area is clearly displayed in low-light conditions, providing accurate image information for doctors' diagnoses.

[0121] Step 307: Generate adjusted medical images based on the attenuated images of critical and non-critical diagnostic areas.

[0122] In this step, the key diagnostic area has undergone brightness and contrast enhancement processing.

[0123] Step 308: Send the adjusted medical image to the medical image display module.

[0124] This step refers to step 206, and the steps are repeated here.

[0125] Step 309: Determine the degree of change in the image content of the initial medical image.

[0126] Specifically, a comparative analysis can be performed on multiple consecutive initial medical images. First, a baseline image, such as the first frame, can be selected as a reference. Then, for each subsequent frame, it is compared pixel-by-pixel with the baseline image. The difference between corresponding pixels in the two images is calculated; for example, the absolute value of the difference in grayscale or color values ​​can be calculated. If the difference is small, it can be considered that the pixel has not changed significantly between the two frames; if the difference is large, it indicates that the image content of the pixel has changed.

[0127] By statistically analyzing the differences between all pixels, we can obtain an indicator of the overall degree of change in the image. For example, we can calculate the proportion of changed pixels to the total number of pixels; this proportion can be used to represent the degree of change in the image content. Alternatively, we can calculate statistical measures such as the mean and variance of the differences between all pixels to characterize the degree of change in the image content.

[0128] In addition, image recognition algorithms can be used to identify specific objects or features in an image, and the degree of change in the image content can be determined by comparing the changes in the position, shape, size, etc. of these objects or features in different frames.

[0129] Step 310: Adjust the screen refresh rate of the medical image display module according to the degree of change in image content.

[0130] After determining the degree of change in image content, the screen refresh rate of the medical image display module can be adjusted based on this indicator. If the degree of change in image content is low, it indicates that the image is relatively stable, and the screen refresh rate can be reduced to lower power consumption. For example, when the degree of change in image content is less than a certain threshold, the screen refresh rate can be reduced from 60Hz to 30Hz. This satisfies the doctor's observation needs while reducing the power consumption of the display module. If the degree of change in image content is high, it means that the image changes frequently, and the screen refresh rate needs to be increased to ensure smooth image display. For example, when the degree of change in image content is greater than another high threshold, the screen refresh rate can be increased from 60Hz to 120Hz to ensure that the doctor can clearly observe the details of the image changes.

[0131] By dynamically adjusting the screen refresh rate, the power consumption of the display module can be effectively reduced while ensuring the display quality of medical images.

[0132] In some embodiments, this step may specifically include: adjusting the screen refresh rate using a refresh rate adjustment formula, wherein the refresh rate adjustment formula includes:

[0133]

[0134] in, R ′ represents the adjusted screen refresh rate.

[0135] R base This is the base screen refresh rate, the default refresh rate when there are no changes in image content. It is typically set based on the display device's hardware specifications and the user's basic requirements for image smoothness. For example, for most medical monitors... R base It may be set to 60Hz, which is a refresh rate that provides a good visual experience in most cases.

[0136] Δ I ( τ ) is in time τ The degree of change in image content between two consecutive frames.

[0137] I threshold This is a preset threshold used to determine when to adjust the refresh rate based on changes in image content. It can be determined by analyzing a large amount of medical image data to find a value that can distinguish between significant and minor changes. This value should be small enough to ensure that important image changes are captured, but large enough to avoid frequent refresh rate adjustments due to minor noise or irrelevant changes.

[0138] T It is a time window that takes into account changes in image content.

[0139] α and β These are adjustment parameters used to control the non-linear characteristics and intensity of refresh rate adjustment. Their values ​​can be determined through experimentation and user testing to find the optimal balance between power consumption and visual experience. For example, this can be achieved by having users experience different refresh rates. α and β The image sharpness and smoothness are evaluated at certain values ​​to determine the optimal values ​​for these parameters.

[0140] In the refresh rate adjustment formula:

[0141] The item indicates the time window. T The integral of the degree of change in image content. This allows the system to consider image changes over a period of time, rather than just changes at a single moment, thus reflecting the dynamic characteristics of the image more comprehensively.

[0142] The term normalizes the degree of change in image content to a preset threshold. I threshold This ensures that refresh rate adjustments are matched to the relative importance of changes in image content, avoiding unnecessary adjustments based on the magnitude of absolute changes.

[0143] This feature introduces a non-linear adjustment, meaning that when the image content changes significantly, the refresh rate adjustment also increases. This non-linear characteristic better aligns with the human eye's perception of image changes, thus improving the visual experience.

[0144] This calculation measures the dynamic average of changes in image content. This makes refresh rate adjustments smoother, avoiding refresh rate fluctuations caused by instantaneous changes.

[0145] α and β It provides additional flexibility, allowing refresh rate adjustments to be optimized based on specific applications and user preferences. α The weight used to set the base refresh rate, and β Used to control the intensity of nonlinear adjustment.

[0146] R base This is the base screen refresh rate, which provides a starting point for adjusting the refresh rate. This ensures that the screen maintains a certain refresh rate even when the image content changes only slightly, thus guaranteeing smooth image display.

[0147] The low-power display method for medical images provided in this embodiment aims to optimize the display effect and energy consumption of medical images. First, the image processing system (hereinafter referred to as the system) acquires an initial medical image. Then, it analyzes the image using a preset key diagnostic recognition model to identify and determine key diagnostic regions in the image. For these key regions, the system retains their original brightness and contrast to ensure diagnostic accuracy. For non-key diagnostic regions, the system dynamically adjusts their brightness and contrast based on the current ambient light intensity using specific brightness and contrast adjustment formulas. These formulas consider ambient light intensity, the original brightness and contrast of pixels, the maximum possible brightness and contrast values ​​of the image, and experimental coefficients to intelligently reduce the brightness and contrast of non-key regions, thereby reducing energy consumption.

[0148] Furthermore, the system monitors the degree of change in the initial medical image content and adjusts the screen refresh rate accordingly. This adjustment is achieved through a specially designed formula that considers the degree of image content change, the time window, and adjustment parameters to ensure reduced power consumption while maintaining image quality. In addition, the system enhances the brightness and contrast of key diagnostic areas based on the current ambient light level to improve image visibility and diagnostic accuracy.

[0149] By combining these steps, this embodiment achieves the goal of reducing display power consumption without sacrificing medical image quality by intelligently identifying critical and non-critical diagnostic areas and dynamically adjusting display parameters based on changes in ambient light and image content. This method not only improves the energy efficiency of medical equipment but may also extend its lifespan and provide doctors with a more comfortable and accurate visual experience, thereby improving the quality and efficiency of medical services.

[0150] The methods provided in the above embodiments can be executed by an image processing system, which may include an electronic device. The electronic device in the embodiments of the present invention is described below from a hardware processing perspective; please refer to [link to relevant documentation]. Figure 3 This is a schematic diagram of the physical device structure of an electronic device in an embodiment of the present invention.

[0151] It should be noted that, Figure 3 The structure of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0152] like Figure 3As shown, the electronic device includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 402 or a program loaded from storage portion 408 into Random Access Memory (RAM) 403, such as performing the methods described in the above embodiments. The RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An Input / Output (I / O) interface 405 is also connected to the bus 404.

[0153] The following components are connected to I / O interface 405: input section 406 including audio input devices, push-button switches, etc.; output section 407 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 408 including a hard disk, etc.; and communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 409 performs communication processing via a network such as the Internet. Drive 410 is also connected to I / O interface 405 as needed. Removable media 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 410 as needed so that computer programs read from them can be installed into storage section 408 as needed.

[0154] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit (CPU) 401, it performs the various functions defined in the present invention.

[0155] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0156] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0157] Specifically, the electronic device of this embodiment includes a processor and a memory. The memory is coupled to one or more processors and is used to store computer program code. The computer program code includes computer instructions. One or more processors call the computer instructions to cause the electronic device to perform the method provided in the above embodiment.

[0158] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The storage medium carries one or more computer programs that, when executed by a processor of the electronic device, cause the electronic device to implement the methods provided in the above embodiments.

[0159] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

[0160] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0161] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A low-power display method for medical images, characterized in that, include: Acquire initial medical images; Determine the degree of change in the image content of the initial medical image; Adjusting the screen refresh rate of the medical image display module according to the degree of change in the image content specifically includes: adjusting the screen refresh rate using a refresh rate adjustment formula, wherein the refresh rate adjustment formula includes: Where R′ is the adjusted screen refresh rate; R base It is the base screen refresh rate; ΔI(τ) is the degree of change in image content between two consecutive frames at time τ; I threshold α is a preset threshold used to determine when to adjust the refresh rate based on changes in image content; T is the time window that considers changes in image content; α and β are adjustment parameters used to control the non-linearity and intensity of the refresh rate adjustment. The initial medical image is processed by a preset key diagnostic recognition model to identify key diagnostic areas in the initial medical image; the key diagnostic recognition model adopts a deep learning architecture and uses image processing technology to determine key diagnostic areas in the image. Based on the initial medical image, the area outside the critical diagnostic area is identified as the non-critical diagnostic area; Confirm the current ambient light level of the environment in which the medical image display module is located; Based on the current ambient light intensity, the non-critical diagnostic area is subjected to brightness and contrast reduction processing to obtain a weakened image of the non-critical diagnostic area; specifically, this includes: reducing the brightness of the non-critical diagnostic area using a brightness adjustment formula, wherein the brightness adjustment formula includes: Where I(p) is the original brightness of pixel p in the non-critical diagnostic area, I′(p) is the adjusted brightness of pixel p, and L env It is the current ambient light level, L ref It is based on ambient light intensity, I max is the maximum possible brightness value of the image, and 'a' is the experimental coefficient; The contrast of the non-critical diagnostic area is reduced using a contrast adjustment formula, which includes: Where C(p) is the original contrast of pixel p in the non-critical diagnostic area, C′(p) is the adjusted contrast of pixel p, and L env It is the current ambient light level, L ref It refers to the ambient light level, C max is the maximum possible contrast value of the image, and b is the experimental parameter; An adjusted medical image is generated based on the attenuated images of the critical diagnostic area and the non-critical diagnostic area. The adjusted medical image is sent to the medical image display module.

2. The method according to claim 1, characterized in that, After determining the area outside the critical diagnostic area as a non-critical diagnostic area based on the initial medical image, the method further includes: Based on the current ambient light level, the key diagnostic area is subjected to brightness enhancement and contrast enhancement processing.

3. An electronic device, characterized in that, Includes one or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the electronic device to perform the method as described in any one of claims 1-2.

4. A computer-readable storage medium storing computer instructions, characterized in that, When the computer instructions are executed on the electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-2.

5. A computer program product, characterized in that, When the computer program product is run on an electronic device, it causes the electronic device to perform the method as described in any one of claims 1-2.

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