Medical image low-power-consumption display method and device, medium and program product

Abstract

The invention discloses a medical image low-power-consumption display method and device, a medium and a program product, and relates to the field of image processing. The method comprises the steps of obtaining an initial medical image; performing identification processing on the initial medical image through a preset key diagnosis identification model to determine a key diagnosis area in the initial medical image; based on the initial medical image, determining an area outside the key diagnosis area as a non-key diagnosis area; performing brightness reduction and contrast reduction processing on the non-key diagnosis area to obtain a non-key diagnosis area weakened image; generating an adjusted medical image according to the weakened images of the key diagnosis area and the non-key diagnosis area; and sending the adjusted medical image to a medical image display module. According to the method, the power consumption of the display module can be effectively reduced while continuous high-definition display of the medical image is ensured, and the purpose of low-power-consumption display of the medical image is achieved.

Description

Technical Field

[0001] The present 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 Art

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

[0003] Based on the above factors, the energy consumption of medical image display modules often remains at a high level. Therefore, it is very important to reduce the power consumption of medical image display modules, which not only helps to reduce energy consumption and costs, but also reduces equipment heating, improves equipment stability and service life. At the same time, for portable medical devices, low power consumption means longer battery life, thereby improving the efficiency and quality of medical services while ensuring the safety and comfort of patients.

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

[0005] In view of the above-mentioned technical problems and defects, the purpose of the present 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 purpose of low-power display of medical images.

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

[0007] The present invention uses a key diagnosis recognition model to identify and process the initial medical image and determine the key diagnosis area, which ensures that the key area that the doctor is most concerned about can be accurately identified. Then, the area outside the key diagnosis area is determined as a non-key diagnosis area, and the non-key diagnosis area is subjected to brightness reduction and contrast reduction processing to obtain a weakened image of the non-key diagnosis area. In this way, the display power consumption of the non-key area is reduced, because after reducing the brightness and contrast, the energy consumed by the display module in these areas is reduced. Then, based on the weakened images of the key diagnosis area and the non-key diagnosis area, an adjusted medical image is generated, and the key diagnosis area maintains a high-definition display to meet the doctor's observation needs for image details, while the processed non-key diagnosis area reduces power consumption without affecting the overall diagnosis. Finally, the adjusted medical image is sent to the medical image display module, which effectively reduces the power consumption of the display module while ensuring the continuous high-definition display of the medical image, and achieves the purpose of low-power display of the medical image.

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

[0009] By adopting the technical solution of the above embodiment, the brightness and contrast of the non-critical diagnosis area are dynamically adjusted by considering the ambient light brightness of the medical image display module, thereby achieving energy saving. This method can ensure that the energy consumption of the display is optimized under different lighting conditions while maintaining the readability of the image. This adaptive adjustment is particularly important in occasions where the ambient light changes greatly, such as mobile medical equipment or outdoor medical applications.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the brightness of the non-critical diagnostic area is reduced according to the current ambient light brightness, including: the brightness of the non-critical diagnostic area is reduced by a brightness adjustment formula, and the brightness adjustment formula includes: ; in, I ( p ) is the pixel in the non-critical diagnosis area p The original brightness, I ′( p ) is the pixel p The adjusted brightness, L env is the current ambient light brightness, L ref is the reference ambient light brightness, Imax is the maximum possible brightness value of the image, a is the experimental coefficient.

[0011] The technical solution of the above embodiment is adopted to reduce the brightness of the non-critical diagnostic area through a specific brightness adjustment formula, which takes into account the ambient light brightness, the original brightness of the pixel and the maximum brightness value of the image. This brightness-based adjustment helps to reduce energy consumption while maintaining the visibility of key information in the image, especially in bright environments, which can reduce the backlight requirements of the display, thereby reducing overall power consumption.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the contrast reduction processing is performed on the non-critical diagnostic area according to the current ambient light brightness, including: the contrast reduction processing is performed on the non-critical diagnostic area by using a contrast adjustment formula, and the contrast adjustment formula includes:

[0013] in, C ( p ) is the pixel in the non-critical diagnosis area p The original contrast ratio, C ′( p ) is the pixel p The adjusted contrast, L env is the current ambient light brightness, L ref is the reference ambient light brightness, C max is the maximum possible contrast value of the image, b is the experimental parameter.

[0014] The technical solution of the above embodiment is adopted to provide a contrast adjustment formula for reducing the contrast of the non-critical diagnosis area, while taking into account the ambient light brightness and the maximum contrast value of the image. This adjustment helps to optimize the visual quality of the image without excessive energy consumption, so that the details and layering of the image are properly displayed under different lighting conditions, thereby improving the visual effect of the image and the accuracy of diagnosis.

[0015] In combination with some embodiments of the first aspect, in some embodiments, after acquiring the initial medical image, it also includes: determining the degree of change of 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 of the image content.

[0016] By adopting the technical solution of the above embodiment, the power consumption is further reduced by monitoring the degree of change of the 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 streaming. By reducing unnecessary screen refreshes, energy consumption can be significantly reduced while ensuring the smoothness and real-time nature of the image.

[0017] In combination 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 of the image content includes: adjusting the screen refresh rate by a refresh rate adjustment formula, and the refresh rate adjustment formula includes:

[0018] in, R ′ is the adjusted screen refresh rate, R base is the basic screen refresh rate, Δ I ( τ ) is at time τ The degree of change in image content between two consecutive frames of images. I threshold is the preset threshold, T is the time window that considers changes in image content, Alpha and Beta is the adjustment parameter.

[0019] The technical solution of the above embodiment is adopted to reasonably adjust the screen refresh rate through the refresh rate adjustment formula, which takes into account the time accumulation effect of image content changes. This method can more accurately capture the dynamic characteristics of image changes, making the adjustment of the refresh rate more precise and reasonable, thereby effectively reducing the energy consumption of the display device while maintaining image quality.

[0020] In combination 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, it also includes: performing brightness enhancement and contrast enhancement processing on the critical diagnostic area according to the current ambient light brightness.

[0021] With the technical solution of the above embodiment, after determining the non-critical diagnosis area, it is also considered to enhance the brightness and contrast of the critical diagnosis area according to the ambient light brightness. This enhancement helps to improve the visibility of the critical area under low light or specific visual conditions, ensuring that the doctor can clearly see important diagnostic information, thereby improving the accuracy of diagnosis and the effectiveness of treatment.

[0022] In a second aspect, an embodiment of the present invention provides an electronic device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation method of the first aspect or the second aspect.

[0023] In a third aspect, the present invention provides a computer-readable storage medium comprising instructions, which, when executed on the electronic device, causes the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation of the first aspect or the second aspect.

[0024] In a fourth aspect, the present invention provides a computer program product comprising instructions, which, when the computer program product is run on the electronic device, enables the electronic device to execute the method described in the first aspect or the second aspect, and any possible implementation of the first aspect or the second aspect.

[0025] It is understandable that 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 in the present invention. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0026] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: 1. Balance between energy saving and display effect: The present invention achieves an optimal balance between energy saving and display effect. By distinguishing between key diagnostic areas and non-key diagnostic areas, and reducing the brightness and contrast of non-key areas in a targeted manner, and dynamically adjusting the screen refresh rate according to the ambient light brightness, the present invention effectively reduces the power consumption of the display module, extends the service life of the equipment, and reduces energy consumption while ensuring that key medical image information is clearly visible.

[0027] 2. Environmental adaptability: By monitoring the ambient light brightness in real time and dynamically adjusting the image brightness, contrast and refresh rate according to this change, the present invention ensures a comfortable visual experience under different lighting conditions. This adaptive adjustment not only improves the readability of the image, but also reduces unnecessary high-brightness display in bright environments, thereby further reducing energy consumption.

[0028] 3. Dynamic optimization of image quality: Through real-time monitoring of the degree of change in image content and adjustment of the refresh rate based on this, as well as brightness and contrast enhancement processing of key diagnostic areas, the present invention can reduce unnecessary processing and data transmission while maintaining image quality, and optimize the image display process. This not only improves the user experience, but also ensures that the key information of medical images can be accurately conveyed under various conditions, thereby improving the accuracy of diagnosis and the effectiveness of treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings herein are incorporated into and constitute a part of the specification, showing embodiments consistent with the present invention, and together with the specification, are used to explain the principles of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 is a flow chart of a low-power display method for medical images according to an embodiment of the present invention; Figure 2 is a flow chart of another low-power display method for medical images according to an embodiment of the present invention; Figure 3 It is a schematic diagram of the architecture of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The terms used in the following embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to be limiting of the present invention. As used in the specification of the present invention, the singular expressions "a", "a", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present invention refers to any or all possible combinations comprising one or more of the listed items.

[0031] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0032] It should also be noted that, unless otherwise clearly specified and limited, in the embodiments of the present invention, the terms such as "setting" and "connection" should be understood in a broad sense. 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 the internal connection of two components; it can be a wired communication connection or a wireless communication connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The embodiments of the present invention are described in detail below.

[0033] The embodiment of the present invention provides a low-power consumption display method for medical images. Figure 1 As shown, the following steps are included: Step 201, obtaining an initial medical image.

[0034] Initial medical images can be obtained through medical imaging equipment, such as computed tomography (CT), magnetic resonance imaging (MRI), X-ray machines, ultrasound equipment, etc. These medical imaging devices capture the internal structure and function information of the human body according to the specified medical needs, generate digital images containing the details required for diagnosis, and then store and transmit these images in digital form through the connected data processing system for doctors and clinical staff to analyze and diagnose.

[0035] Step 202: Perform recognition processing on the initial medical image using a preset key diagnosis recognition model to determine the key diagnosis area in the initial medical image.

[0036] Among them, the critical diagnostic area refers to the specific area in the medical image that has a decisive influence on the diagnosis and treatment decision. These areas usually 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 plan planning and surgical navigation. Therefore, it is necessary to maintain high resolution and high contrast when displaying to ensure that doctors can accurately identify and analyze this key information.

[0037] In this embodiment, the key diagnosis recognition model is trained to accurately identify the key diagnosis area. The key diagnosis recognition model can automatically analyze the initial medical image and determine the key diagnosis area in the image through image processing techniques such as edge detection, feature extraction, segmentation and classification. The model will output a probability map or directly mark the key area.

[0038] The training process of the key diagnosis recognition model is a machine learning process involving a large amount of data and complex calculations, designed to enable the model to accurately identify key diagnostic areas from medical images. The following is a detailed description of the training process: 1) Data collection and preprocessing: Collect a large amount of medical image data as sample data for training. These data may come from different imaging modalities, such as CT, MRI, X-ray, etc.

[0039] Preprocess the images, including denoising, standardization, and resizing, to improve the efficiency and effectiveness of model training.

[0040] 2) Labeling: Professional doctors or technicians annotate key diagnostic areas in the image, which may include marking the boundaries of the lesion, identifying specific anatomical structures, etc.

[0041] The labeling process provides the model with the “correct answers” ​​required for training, that is, the outputs that the model needs to learn.

[0042] 3) Choose the model architecture: Choose appropriate deep learning architectures, such as convolutional neural networks (CNNs), which perform well in image recognition tasks.

[0043] 4) Training: The model is trained using the labeled data. During the training process, the model learns features through forward propagation and adjusts the weights through backpropagation to minimize the difference between the prediction and the actual annotation.

[0044] Apply techniques such as cross-validation to evaluate the performance of the model and avoid overfitting.

[0045] 5) Performance evaluation: An independent test set was used to evaluate the accuracy, sensitivity, specificity and other indicators of the model.

[0046] Adjust model parameters or redesign the network structure based on the evaluation results.

[0047] 6) Tuning: Based on the results of the performance evaluation, the model is tuned, which may include changing the learning rate, adding regularization, adjusting the number or depth of network layers, etc.

[0048] 7) Verification and testing: The model is further validated and tested in actual medical environments to ensure that it can also perform well on real-world data.

[0049] 8) Deployment and monitoring: Deploy trained models into clinical settings and continuously monitor their performance to identify and correct any issues.

[0050] Step 203: Based on the initial medical image, determine the area outside the critical diagnosis area as a non-critical diagnosis area.

[0051] Specifically, all parts of the initial medical image except the critical diagnosis area can be automatically marked as non-critical diagnosis areas by dividing the image area. For example, an attribute label can be assigned to each pixel in the image, and the pixels belonging to the critical diagnosis area are marked as "critical", and the remaining pixels are marked as "non-critical". In this way, the area outside the critical diagnosis area can be clearly identified as the non-critical diagnosis area, providing an accurate basis for subsequent different processing operations on different areas.

[0052] Step 204 , performing brightness reduction and contrast reduction processing on the non-critical diagnosis area to obtain a weakened image of the non-critical diagnosis area.

[0053] Specifically, after the non-critical diagnostic area is determined, a processing mechanism needs to be established to adjust the image attributes of the non-critical diagnostic area in a targeted manner. For brightness reduction processing, a suitable brightness adjustment coefficient can be set. The determination of this coefficient requires comprehensive consideration of many factors, such as the overall brightness distribution of the initial medical image, the brightness difference between the critical diagnostic area and the non-critical diagnostic area, etc. For example, if the overall brightness of the initial medical image is high, a larger brightness reduction coefficient can be selected to ensure that the brightness of the non-critical diagnostic area can be significantly reduced.

[0054] Next, each pixel in the non-critical diagnosis area is traversed. For each pixel, a new brightness value is calculated based on the brightness adjustment coefficient. For example, if the original brightness value of a pixel is 250 and the brightness adjustment coefficient is 0.7, the adjusted brightness value becomes 175.

[0055] A similar method can be used for contrast reduction processing. First determine a contrast adjustment coefficient, and then adjust the grayscale difference between pixels in the non-critical diagnosis area according to the coefficient. For example, the grayscale values ​​of two adjacent pixels are 180 and 200, respectively, and the contrast is high. After contrast adjustment, assuming that the contrast adjustment coefficient is 0.6, their grayscale difference will be reduced, and the new grayscale values ​​may become 185 and 190, thereby reducing the contrast.

[0056] By adjusting the brightness and contrast of all pixels in the non-critical diagnosis area in turn, the image in the non-critical diagnosis area can be made relatively dim and blurred. Without affecting the clear display of the critical diagnosis area, the energy consumption of the display module in the non-critical area is effectively reduced, and finally a weakened image of the non-critical diagnosis area is obtained. This processing method not only meets the doctor's need to observe the details of the image in the critical diagnosis area, but also achieves the goal of reducing power consumption, which is of great significance for improving the performance and efficiency of medical image display modules.

[0057] Step 205 , generating an adjusted medical image by attenuating the images of the critical diagnosis area and the non-critical diagnosis area.

[0058] Specifically, firstly, the determined key diagnosis area and the attenuated image of the non-key diagnosis area obtained after brightness reduction and contrast reduction are clearly identified. The key diagnosis area is kept in its original state without any change to ensure the image details and clarity of the key area.

[0059] Then, the attenuated image of the non-critical diagnostic area is placed in the position corresponding to the critical diagnostic area. In this process, it is necessary to ensure that the boundary between the attenuated image of the critical diagnostic area and the non-critical diagnostic area is seamlessly connected so that the entire image looks natural and smooth. Through precise image fusion technology, the attenuated images of the critical diagnostic area and the non-critical diagnostic area are integrated together to finally generate an adjusted medical image.

[0060] This adjusted medical image not only highlights important information in the key diagnostic area, 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.

[0061] Step 206, sending the adjusted medical image to the medical image display module.

[0062] Specifically, the data integrity and accuracy of the adjusted medical image should be ensured first, and the image data should be verified to confirm that no data loss or damage occurs during the generation and processing of the image.

[0063] Then, the adjusted medical image is 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, optical fiber, etc., or a wireless connection, such as Bluetooth, Wi-Fi, etc. During the transmission process, the stability and speed of data transmission must be ensured to avoid problems such as image freeze and distortion.

[0064] Once the image data is successfully transmitted to the medical image display module, the module will analyze and display the received image data. The display module will present the adjusted medical image in a clear and accurate manner based on the characteristics of the image and its own display parameters for doctors to observe and diagnose.

[0065] This embodiment aims to achieve a balance between high-definition display and low power consumption of medical images. First, the initial medical image is identified and processed using the key diagnosis recognition model to determine the key diagnosis area, which ensures that the key area that the doctor is most concerned about can be accurately identified. Then, the area outside the key diagnosis area is determined as a non-key diagnosis area, and the non-key diagnosis area is subjected to brightness reduction and contrast reduction processing to obtain a weakened image of the non-key diagnosis area. In this way, the display power consumption of the non-key area is reduced, because after reducing the brightness and contrast, the energy consumed by the display module in these areas is reduced. Then, an adjusted medical image is generated based on the weakened images of the key diagnosis area and the non-key diagnosis area. The key diagnosis area maintains a high-definition display to meet the doctor's observation needs for image details, and the processed non-key diagnosis area reduces power consumption without affecting the overall diagnosis. Finally, the adjusted medical image is sent to the medical image display module, which effectively reduces the power consumption of the display module while ensuring the continuous high-definition display of the medical image, and achieves the purpose of low-power display of the medical image.

[0066] Combine the following Figure 2 The method of the embodiment of the present invention is specifically described, comprising the following steps: Step 301, obtaining an initial medical image.

[0067] Then proceed to step 302 and step 309 respectively.

[0068] Step 302: Perform recognition processing on the initial medical image using a preset key diagnosis recognition model to determine the key diagnosis area in the initial medical image.

[0069] This step refers to step 202 and will not be described again here.

[0070] Step 303: Based on the initial medical image, determine the area outside the critical diagnosis area as a non-critical diagnosis area.

[0071] This step refers to step 203 and will not be described again here.

[0072] Step 304, confirming the current ambient light brightness of the environment in which the medical image display module is located.

[0073] Specifically, an ambient light sensor is installed near the medical image display module. The ambient light sensor can sense the light intensity of the surrounding environment and convert it into electrical signals. After processing and analysis, these electrical signals can be used to determine the specific value of the current ambient light brightness. For example, the ambient light sensor can measure the ambient light brightness once every period of time (such as a few seconds) and send the measurement results to the image processing system.

[0074] In addition, other devices or technologies can also be used to indirectly determine the ambient light brightness, such as using a camera to capture the surrounding environment and then using an image analysis algorithm to estimate the ambient light brightness. Regardless of which method is used, the purpose is to accurately obtain the current ambient light brightness of the environment in which the medical image display module is located, so that in subsequent steps, non-critical diagnostic areas can be processed more reasonably based on this information.

[0075] Step 305 , reducing the brightness and contrast of the non-critical diagnosis area according to the current ambient light brightness, to obtain a weakened image of the non-critical diagnosis area.

[0076] After obtaining the current ambient light brightness, the brightness and contrast of the non-critical diagnosis area can be reduced according to this information. If the current ambient light brightness is high, the brightness and contrast reduction of the non-critical diagnosis area can be appropriately increased.

[0077] For example, when the ambient light is very bright, in order to avoid the non-critical diagnostic area being too dazzling and distracting the doctor's attention, the brightness of the non-critical diagnostic area can be reduced to a lower level, and the grayscale difference between pixels can be further reduced to reduce the contrast. On the contrary, if the current ambient light is low, the degree of reduction in brightness and contrast can be relatively reduced to ensure that the non-critical diagnostic area can still provide certain visual information and is not completely unclear. The specific processing process can be achieved by adjusting the brightness value and contrast parameters of each pixel in the non-critical diagnostic area.

[0078] For brightness reduction, the new brightness value of each pixel can be calculated based on the ambient light brightness and the preset brightness adjustment formula. For contrast reduction, the grayscale difference between pixels can be adjusted based on the ambient light brightness and the contrast adjustment algorithm.

[0079] By performing such processing on all pixels in the non-critical diagnosis area, a weakened image of the non-critical diagnosis area is finally obtained, thereby achieving the goal of reducing the power consumption of the display module while adapting to different ambient light brightness.

[0080] In some embodiments, the brightness of the non-critical diagnosis area may be reduced by a brightness adjustment formula, and the brightness adjustment formula includes:

[0081] in, I ( p ) is the pixel in the non-critical diagnosis area p The original brightness, I ′( p ) is the pixel p The adjusted brightness, L env is the current ambient light brightness, L ref is the reference ambient light brightness, I max is the maximum possible brightness value of the image, a is the experimental coefficient.

[0082] I max The maximum range of image brightness can be determined by the hardware specifications of the display device, or obtained through experimental measurement. L ref and a This can be optimized and debugged through a series of experiments and user tests. In actual operation, these parameters may need to be adjusted and calibrated according to specific device performance, usage scenarios, and user feedback to achieve the best visual effect and energy consumption balance.

[0083] 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.

[0084] Logarithmic function The ambient light brightness ratio is mapped to a nonlinear space. The use of the logarithmic function simulates the nonlinear perception of brightness by the human eye, that is, when the ambient light brightness is low, a small change in brightness has a greater impact on the human eye, while when the ambient light brightness is high, the same change in brightness has a smaller impact on the human eye.

[0085] Experimental coefficient a It is used to adjust the intensity of the logarithmic function in the brightness adjustment formula, so as to control the sensitivity of the ambient light brightness change to the brightness adjustment of the non-critical diagnostic area.

[0086] The item represents the current pixel p The difference between the brightness of the I ( p ) near I max When , this difference is close to 0, which means that the brightness adjustment is small; when I ( p ) is smaller, this difference is larger, which means a larger brightness adjustment.

[0087] It is the brightness adjustment factor, which can be dynamically adjusted according to the ambient light brightness and the brightness of the current pixel to ensure that the brightness of non-critical areas is appropriately reduced under different ambient light conditions.

[0088] Multiply the brightness adjustment factor by the original brightness I ( p ), get the adjusted brightness I ′( p ). In this way, the brightness of non-critical areas is reduced when the ambient light level is high to save energy, while maintaining a high brightness when the ambient light level is low to ensure image readability.

[0089] In this embodiment, the contrast of the non-critical diagnosis area may also be reduced by using a contrast adjustment formula, and the contrast adjustment formula includes:

[0090] in, C ( p ) is the pixel in the non-critical diagnosis area p The original contrast ratio, C ′( p ) is the pixel p The adjusted contrast, L env is the current ambient light brightness, L ref is the reference ambient light brightness, C max is the maximum possible contrast value of the image, b is the experimental parameter.

[0091] C max It can be obtained through technical parameters or experimental measurements. It defines the upper limit of contrast adjustment to ensure that the image maintains optimal visual clarity at different brightness levels.

[0092] b It is an experimental parameter used to adjust the degree of influence of ambient light brightness changes on contrast adjustment. This parameter is optimized through a series of experiments and user tests to achieve appropriate contrast of images under different ambient lighting conditions, taking into account 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 lighting in the usage environment, and user preferences.

[0093] The term maps the ambient light brightness ratio to a nonlinear space. This nonlinear term is achieved through experimental parameters bAdjust to control how much contrast is adjusted.

[0094] The term represents the difference between the contrast of the current pixel and the maximum contrast. C ( p ) near C max When , this difference is close to 0, which means that the contrast adjustment is small; when C ( p ) is smaller, this difference is larger, meaning a larger contrast adjustment.

[0095] is the contrast adjustment factor. This factor is dynamically adjusted according to the ambient light brightness and the contrast of the current pixel to ensure that the contrast of the non-critical diagnostic area is appropriately adjusted or reduced under different ambient light conditions. Multiply the contrast adjustment factor by the original contrast C ( p ), and get the adjusted contrast C ′( p ).

[0096] The contrast adjustment formula rationally achieves contrast reduction processing in non-critical diagnostic areas by comprehensively considering ambient light brightness, image contrast and flexible adjustment parameters, which not only reduces display power consumption but also maintains key diagnostic information of medical images, demonstrating its effectiveness and practicality in medical image display.

[0097] Step 306: Perform brightness enhancement and contrast enhancement processing on the key diagnosis area according to the current ambient light brightness.

[0098] Specifically, after first determining the current ambient light brightness, analyze its impact on the display effect of the key diagnostic area. If the ambient light brightness is high, the image of the key diagnostic area may not appear clear and prominent enough, and corresponding brightness enhancement and contrast enhancement processing is required. The appropriate brightness enhancement and contrast enhancement coefficients can be calculated based on the ambient light brightness value and the preset enhancement algorithm. For brightness enhancement, adjust the brightness value of each pixel in the key diagnostic area one by one, and increase its brightness value according to the enhancement coefficient, so that the key diagnostic area can still be clearly visible in a strong light environment.

[0099] For example, if the original brightness value of a pixel 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 in the key diagnostic area. For example, the grayscale values ​​of two adjacent pixels were originally 120 and 130, respectively. After contrast enhancement, their grayscale difference may increase to 110 and 140, making the image of the key diagnostic area more vivid and prominent. If the ambient light is low, brightness enhancement and contrast enhancement can also be performed appropriately according to the situation to ensure that the key diagnostic area can be clearly displayed in a low-light environment, providing accurate image information for the doctor's diagnosis.

[0100] Step 307 , generating an adjusted medical image by attenuating the images according to the key diagnosis area and the non-key diagnosis area.

[0101] The key diagnosis area in this step is processed by brightness enhancement and contrast enhancement.

[0102] Step 308: Send the adjusted medical image to the medical image display module.

[0103] This step refers to step 206, and the steps are repeated here.

[0104] Step 309, determining the degree of change of the image content of the initial medical image.

[0105] Specifically, multiple consecutive frames of initial medical images can be compared and analyzed. First, a reference image, such as the first frame, can be selected as a reference. Then, for each subsequent frame, it is compared with the reference image pixel by pixel. The difference between the corresponding pixels of the two images is calculated, for example, the absolute value of the difference in grayscale value or color value of the pixel 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 means that the image content of the pixel has changed.

[0106] By performing statistical analysis on the difference values ​​of all pixels, we can get the index of the degree of change of the entire image. For example, we can calculate the ratio of the number of changed pixels to the total number of pixels, and this ratio can be used to indicate the degree of change of the image content. Or we can calculate the average value, variance and other statistics of the difference values ​​of all pixels to characterize the degree of change of the image content.

[0107] In addition, image recognition algorithms can be used to identify specific objects or features in the image, and the degree of change in the image content can be determined by comparing changes in the position, shape, size, etc. of these objects or features in different frames.

[0108] Step 310: Adjust the screen refresh rate of the medical image display module according to the degree of change of the image content.

[0109] After determining the degree of change in the 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 the image content is low, it means that the image is relatively stable. At this time, the screen refresh rate can be reduced to reduce power consumption. For example, when the degree of change in the image content is less than a certain threshold, the screen refresh rate can be reduced from 60Hz to 30Hz. This can not only meet the doctor's observation needs for the image, but also reduce the energy consumption of the display module. If the degree of change in the image content is high, it means that the image changes more frequently. At this time, the screen refresh rate needs to be increased to ensure smooth display of the image. For example, when the degree of change in the image content is greater than another higher threshold, the screen refresh rate can be increased from 60Hz to 120Hz to ensure that the doctor can clearly observe the changing details of the image.

[0110] 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.

[0111] In some embodiments, this step may specifically include: adjusting the screen refresh rate by a refresh rate adjustment formula, the refresh rate adjustment formula including:

[0112] in, R ′ is the adjusted screen refresh rate.

[0113] R base Is the basic screen refresh rate, which is the default refresh rate when there is no image content change. It is usually set based on the hardware specifications of the display device and the user's basic needs for image smoothness. For example, for most medical displays, R base It's likely set to 60Hz, a refresh rate that should provide a good visual experience in most situations.

[0114] Δ I ( τ ) is at time τ The degree of change of image content between two consecutive frames of images.

[0115] I threshold It 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 significant changes from minor changes. This value should be small enough to ensure that important image changes can be captured, but large enough to avoid frequent adjustments to the refresh rate due to minor noise or irrelevant changes.

[0116] T is the time window that takes into account changes in image content.

[0117] Alpha and Beta are adjustment parameters that control the nonlinear characteristics and strength of the refresh rate adjustment. Their values ​​can be determined through experiments and user testing to find the best balance between power consumption and visual experience. For example, by having users switch between different α and β The clarity and smoothness of the image are evaluated under different values ​​to determine the optimal values ​​of these parameters.

[0118] In the refresh rate adjustment formula: Item represents the time window T This allows the system to consider image changes over a period of time, rather than just changes at a single moment, thereby more comprehensively reflecting the dynamic characteristics of the image.

[0119] The term normalizes the degree of change in image content to a preset threshold I threshold This ensures that the refresh rate is adjusted to match the relative importance of the change in image content, avoiding unnecessary adjustments due to the magnitude of the absolute change.

[0120] The nonlinear adjustment is introduced in this option, so that when the image content changes greatly, the refresh rate is also adjusted greatly. This nonlinear characteristic is more in line with the human eye's perception of image changes and improves the visual experience.

[0121] The term calculates the dynamic average of image content changes. This makes the refresh rate adjustment smoother and avoids refresh rate fluctuations caused by instantaneous changes.

[0122] α and β Provides additional flexibility, allowing adjustment of the refresh rate to be optimized based on specific applications and user preferences. α Used to set the weight of the base refresh rate, and β Used to control the strength of the nonlinear adjustment.

[0123] R base It is the basic screen refresh rate, which provides a starting point for the adjustment of the refresh rate. This ensures that even when the image content changes slightly, the screen can maintain a certain refresh rate to ensure the smoothness of the image.

[0124] The low-power display method for medical images provided in this embodiment is intended to optimize the display effect and energy consumption of medical images. First, the image processing system (hereinafter referred to as the system) obtains the initial medical image, and then analyzes the image using a preset key diagnosis recognition model to identify and determine the key diagnosis areas in the image. For these key areas, the system will retain their original brightness and contrast to ensure the accuracy of the diagnosis. For non-critical diagnosis areas, the system will dynamically adjust its brightness and contrast according to the current ambient light brightness, using specific brightness and contrast adjustment formulas to achieve this. These formulas take into account the ambient light brightness, the original brightness and contrast of the pixel, the maximum possible brightness and contrast values ​​of the image, and the experimental coefficients to intelligently reduce the brightness and contrast of non-critical areas and reduce energy consumption.

[0125] Furthermore, the system monitors the degree of change in the image content of the initial medical image and adjusts the screen refresh rate based on this change, which is achieved through a specially designed refresh rate adjustment formula that involves the degree of image content change and the time window, as well as adjustment parameters to ensure that power consumption is reduced while maintaining image quality. In addition, the system also performs brightness enhancement and contrast enhancement processing on key diagnostic areas based on the current ambient light brightness to improve image visibility and diagnostic accuracy.

[0126] Combining these steps, this embodiment achieves the goal of reducing display power consumption without sacrificing medical image quality by intelligently identifying key diagnostic areas and non-key diagnostic areas and dynamically adjusting display parameters according to ambient light brightness and image content changes. This method not only improves the energy efficiency of medical equipment, but also may extend the service life of the equipment and provide doctors with a more comfortable and accurate visual experience, thereby improving the quality and efficiency of medical services.

[0127] The method provided in the above embodiment can be executed by an image processing system, which can include an electronic device. The electronic device in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of an electronic device in an embodiment of the present invention.

[0128] It should be noted that Figure 3 The structure of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0129] like Figure 3As shown, the electronic device includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In RAM 403, various programs and data required for system operation are also stored. CPU 401, ROM 402 and RAM 403 are connected to each other through bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0130] The following components are connected to the I / O interface 405: an input section 406 including an audio input device, a button switch, etc.; an output section 407 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0131] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the present invention are performed.

[0132] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0134] Specifically, the electronic device of this embodiment includes a processor and a memory, the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the electronic device to execute the method provided by the above embodiment.

[0135] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the electronic device, the electronic device implements the method provided in the above embodiment.

[0136] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

[0137] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0138] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A low-power display method for medical images, characterized in that: include: Acquiring initial medical images; Performing recognition processing on the initial medical image by using a preset key diagnosis recognition model to determine a key diagnosis area in the initial medical image; Based on the initial medical image, determining the area outside the critical diagnosis area as a non-critical diagnosis area; Performing brightness reduction and contrast reduction processing on the non-critical diagnosis area to obtain a weakened image of the non-critical diagnosis area; Generate an adjusted medical image based on the attenuated images of the critical diagnosis area and the non-critical diagnosis area; The adjusted medical image is sent to a medical image display module.

2. The method according to claim 1, characterized in that The step of reducing the brightness and contrast of the non-critical diagnosis area to obtain a weakened image of the non-critical diagnosis area includes: Confirming the current ambient light brightness of the environment in which the medical image display module is located; The non-critical diagnosis area is subjected to brightness reduction and contrast reduction processing according to the current ambient light brightness to obtain a weakened image of the non-critical diagnosis area.

3. The method according to claim 2, characterized in that The step of reducing the brightness of the non-critical diagnosis area according to the current ambient light brightness includes: The brightness of the non-critical diagnosis area is reduced by a brightness adjustment formula, and the brightness adjustment formula includes: ； in, I ( p ) is the pixel point in the non-critical diagnosis area p The original brightness, I ′( p ) is the pixel point p The adjusted brightness, L env is the current ambient light brightness, L ref is the reference ambient light brightness, I max is the maximum possible brightness value of the image, a is the experimental coefficient.

4. The method according to claim 2, characterized in that: Performing contrast reduction processing on the non-critical diagnosis area according to the current ambient light brightness includes: The contrast of the non-critical diagnosis area is reduced by a contrast adjustment formula, wherein the contrast adjustment formula includes: ； in, C ( p ) is the pixel point in the non-critical diagnosis area p The original contrast ratio, C ′( p ) is the pixel point p The adjusted contrast, L env is the current ambient light brightness, L ref is the reference ambient light brightness, C max is the maximum possible contrast value of the image, b is the experimental parameter.

5. The method according to any one of claims 1 to 4, characterized in that: After acquiring the initial medical image, the method further includes: determining a degree of change in image content of the initial medical image; The screen refresh rate of the medical image display module is adjusted according to the degree of change of the image content.

6. The method according to claim 5, characterized in that The step of adjusting the screen refresh rate of the medical image display module according to the degree of change of the image content includes: The screen refresh rate is adjusted by a refresh rate adjustment formula, wherein the refresh rate adjustment formula includes: ； in, R ′ is the adjusted screen refresh rate, R base is the basic screen refresh rate, Δ I ( τ ) is at time τ The degree of change in image content between two consecutive frames of images. I threshold is the preset threshold, T is the time window that considers changes in image content, Alpha and Beta is the adjustment parameter.

7. The method according to claim 1, characterized in that After determining the area outside the critical diagnosis area as a non-critical diagnosis area based on the initial medical image, the method further includes: According to the current ambient light brightness, brightness enhancement and contrast enhancement processing are performed on the key diagnosis area.

8. An electronic device, characterized in that: including one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium storing computer instructions, characterized in that: When the computer instructions are executed on an electronic device, the electronic device is caused to execute the method as claimed in any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is executed on an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 7.

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