Dual-energy cone beam CT (Computed Tomography) imaging method, device and equipment based on prior guidance and medium

Abstract

The invention relates to the field of image processing, and discloses a dual-energy cone-beam CT imaging method based on prior guidance, which comprises the following steps: acquiring high-energy projection data and low-energy projection data of dual-energy cone-beam CT, preprocessing the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image, and outputting the high-energy projection image and the low-energy projection image; performing contrast compensation on the high-energy projection image to obtain a contrast compensation prior image, performing calculation according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image, performing threshold segmentation on the high-energy projection image, and performing forward projection on the image subjected to threshold segmentation to obtain a high-density mask projection image. And performing weighted fusion on the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image, and performing three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image. The quality of a hybrid reconstructed image obtained by combining two kinds of energy of the dual-energy cone beam CT can be improved.

Description

Technical Field

[0001] The present application relates to the field of image processing, and in particular to a dual-energy cone-beam CT imaging method, device, equipment and medium based on prior guidance. Background Art

[0002] Cone-beam computed tomography (CBCT) has the advantages of high resolution and low radiation dose, and is widely used in oral and maxillofacial imaging examinations. In oral and maxillofacial imaging examinations, the tooth density is usually very high, and even accompanied by metal objects such as crowns, so the cone-beam CT image has serious beam hardening artifacts, which interferes with the doctor's reading and examination. Compared with cone-beam CT, dual-energy cone-beam CT can provide two energies, and the images obtained with different energies have their own characteristics, thus providing rich feature prior information. At present, the mixed reconstructed image is mainly obtained by a simple linear combination of the two energies, and it is still impossible to fully utilize the complementary information of the two to obtain better image quality. Therefore, how to effectively combine the two energy information becomes the key, and a dual-energy cone-beam CT imaging method based on prior guidance is urgently needed to improve the quality of the reconstructed image.

[0003] The existing technology currently has the problem of low quality of hybrid reconstructed images obtained by combining two energies of dual-energy cone-beam CT. Summary of the invention

[0004] The present application provides a dual-energy cone-beam CT imaging method, device, equipment and medium based on prior guidance, the main purpose of which is to solve the problem of low quality of hybrid reconstructed images obtained by combining two energies of dual-energy cone-beam CT.

[0005] To achieve the above purpose, the present application provides a dual-energy cone-beam CT imaging method based on prior guidance, comprising:

[0006] Acquire high-energy projection data and low-energy projection data of dual-energy cone-beam CT, and pre-process the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image;

[0007] Performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image;

[0008] Calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression priori image;

[0009] Performing threshold segmentation on the high-energy projection image, and forward projecting the image after the threshold segmentation to obtain a high-density mask projection image;

[0010] According to the high-density mask projection image, weighted fusion is performed on the contrast compensation prior image and the artifact suppression prior image to obtain a mixed projection image;

[0011] The mixed projection image is three-dimensionally reconstructed to obtain a mixed reconstructed image.

[0012] In some embodiments, the preprocessing of the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image includes:

[0013] Get the preset angle compensation parameters;

[0014] Aligning the high-energy projection data and the low-energy projection data using the angle compensation parameter to obtain high-energy alignment data and low-energy alignment data;

[0015] Acquire background signal and transmission signal from a preset detector;

[0016] Counting the number of the background signals as the number of incident photons;

[0017] Counting the number of the transmission signals as the number of outgoing photons;

[0018] A high-energy attenuation projection of the high-energy alignment data and a low-energy attenuation projection of the low-energy alignment data are calculated according to the number of incident photons and the number of outgoing photons;

[0019] A high-energy projection image and a low-energy projection image are generated according to the high-energy attenuation projection and the low-energy attenuation projection.

[0020] In some embodiments, performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image includes:

[0021] Normalizing the grayscale of the low-energy projection image to obtain a weight coefficient;

[0022] Compensating each pixel in the high-energy projection image according to the weight coefficient to obtain an updated pixel value of each pixel;

[0023] The updated pixel value of each pixel is synthesized into a contrast compensated prior image.

[0024] In some embodiments, the calculating effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image includes:

[0025] Acquire a modulation coefficient between the high-energy projection image and the low-energy projection image;

[0026] Calculating the high-energy projection image and the low-energy projection image according to the modulation coefficient to obtain a synthetic energy projection image;

[0027] The synthetic energy projection image and the high energy projection image are weightedly fused to obtain an artifact suppression prior image.

[0028] In some embodiments, performing threshold segmentation on the high-energy projection image and forward projecting the image after threshold segmentation to obtain a high-density mask projection image includes:

[0029] Performing three-dimensional reconstruction on the high-energy projection image to obtain a high-energy attenuation image;

[0030] Setting a pixel value in the high-energy attenuation image that is greater than a preset pixel threshold as a first pixel value;

[0031] Setting the pixel value in the high-energy attenuation image that is less than or equal to the pixel threshold as a second pixel value;

[0032] Combining a plurality of the first pixel values ​​and a plurality of the second pixel values ​​into a high-density mask image;

[0033] Get the ray-driven forward projection operator;

[0034] The high-density mask image is projected according to the ray-driven forward projection operator to obtain a high-density mask projection image.

[0035] In some embodiments, weighted fusion of the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image includes:

[0036] Normalizing pixels in the high-density mask projection image to obtain a normalized image;

[0037] The normalized image is used to calculate pixels in the contrast compensation prior image and pixels in the artifact suppression prior image to obtain a mixed projection image.

[0038] In some embodiments, the three-dimensional reconstruction of the mixed projection image to obtain a mixed reconstructed image includes:

[0039] Obtaining the reconstruction volume and projection angle in the three-dimensional reconstruction parameters;

[0040] Performing filtering on the mixed projection image to obtain a plurality of filtered projection data;

[0041] superimposing each of the projection data into the reconstructed volume according to the projection angle;

[0042] The reconstructed volume is normalized to obtain a mixed reconstructed image.

[0043] In order to solve the above problems, the present invention also provides a dual-energy cone-beam CT imaging device based on a priori guidance, the device comprising:

[0044] An image acquisition module, used for acquiring high-energy projection data and low-energy projection data of dual-energy cone-beam CT, and preprocessing the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image;

[0045] A contrast compensation module, used for performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image;

[0046] An artifact suppression module is used to calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image, and obtain an artifact suppression prior image;

[0047] An image segmentation module, used for performing threshold segmentation on the high-energy projection image, and forward projecting the image after threshold segmentation to obtain a high-density mask projection image;

[0048] An image fusion module, configured to perform weighted fusion of the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image;

[0049] The image reconstruction module is used to perform three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

[0050] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0051] at least one processor; and,

[0052] a memory communicatively connected to the at least one processor; wherein,

[0053] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the above-mentioned dual-energy cone-beam CT imaging method based on a priori guidance.

[0054] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned dual-energy cone-beam CT imaging method based on prior guidance. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a process flow of a dual-energy cone-beam CT imaging method based on a priori guidance provided in one embodiment of the present application;

[0056] Figure 2 A functional module diagram of a dual-energy cone-beam CT imaging device based on a priori guidance provided in one embodiment of the present application;

[0057] Figure 3 A schematic diagram of the structure of an electronic device for implementing the dual-energy cone-beam CT imaging method based on prior guidance provided in one embodiment of the present application.

[0058] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0059] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0060] The embodiment of the present application provides a dual-energy cone-beam CT imaging method based on prior guidance. The execution subject of the dual-energy cone-beam CT imaging method based on prior guidance includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the dual-energy cone-beam CT imaging method based on prior guidance can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0061] Reference Figure 1 FIG. 1 is a flow chart of a dual-energy cone-beam CT imaging method based on a priori guidance provided in an embodiment of the present application. In this embodiment, a dual-energy cone-beam CT imaging method based on a priori guidance includes:

[0062] S1. Acquire high-energy projection data and low-energy projection data of dual-energy cone-beam CT, and pre-process the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image.

[0063] In the embodiment of the present invention, dual-energy cone-beam CT is a technology that uses X-rays of different energies to obtain images, which can provide richer tissue and material information. A dual-energy cone-beam CT system is used to scan the scanned object through two X-ray sources of different energies to obtain high-energy projection data and low-energy projection data.

[0064] In detail, the preprocessing of the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image includes:

[0065] Get the preset angle compensation parameters;

[0066] Aligning the high-energy projection data and the low-energy projection data using the angle compensation parameter to obtain high-energy alignment data and low-energy alignment data;

[0067] Acquire background signal and transmission signal from a preset detector;

[0068] Counting the number of the background signals as the number of incident photons;

[0069] Counting the number of the transmission signals as the number of outgoing photons;

[0070] A high-energy attenuation projection of the high-energy alignment data and a low-energy attenuation projection of the low-energy alignment data are calculated according to the number of incident photons and the number of outgoing photons;

[0071] A high-energy projection image and a low-energy projection image are generated according to the high-energy attenuation projection and the low-energy attenuation projection.

[0072] In detail, aligning the high-energy projection data and the low-energy projection data using the angle compensation parameter to obtain high-energy alignment data and low-energy alignment data includes:

[0073] Obtaining the rotation angle and translation parameters in the angle compensation parameters;

[0074] Rotate the high-energy projection data and the low-energy projection data according to the rotation angle to obtain high-energy rotation data and low-energy rotation data;

[0075] The high-energy rotation data and the low-energy rotation data are moved using the translation parameters to obtain high-energy alignment data and low-energy alignment data.

[0076] In detail, the photon number information in the high-energy projection data and the low-energy projection data is converted into projection values ​​corresponding to the attenuation coefficient, and a high-energy projection image and a low-energy projection image are generated according to the projection values. The calculation formula is as follows:

[0077]

[0078] Among them, s0 represents the number of incident photons on the scanned object, s represents the number of outgoing photons after passing through the scanned object, and p h represents the high energy projection image, p l Indicates a low-energy projected image.

[0079] This process can effectively improve the alignment accuracy of projection data, thereby ensuring the accuracy of high-energy and low-energy projection images, and by accurately counting the number of incident photons and the number of outgoing photons, calculating the attenuation coefficient, ensuring that the generated image more truly reflects the characteristics of the internal structure of the object. This not only improves the imaging quality, but also provides a reliable data basis for subsequent image analysis.

[0080] S2. Perform contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image.

[0081] In an embodiment of the present invention, performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image includes:

[0082] Normalizing the grayscale of the low-energy projection image to obtain a weight coefficient;

[0083] Compensating each pixel in the high-energy projection image according to the weight coefficient to obtain an updated pixel value of each pixel;

[0084] The updated pixel value of each pixel is synthesized into a contrast compensated prior image.

[0085] Specifically, the low-energy projection image is grayscale normalized to obtain a weight coefficient, and the calculation formula is as follows:

[0086]

[0087] Among them, p l (i) represents the i-th pixel value in the low-energy projection image, p l_min Represents the low energy projection image p l The minimum pixel value in (i), p l_max Represents the low energy projection image p l The maximum pixel value in (i), w p (i) represents the weight coefficient.

[0088] The high-energy projection image is contrast-compensated according to the weight coefficient to obtain a contrast-compensated prior image. The calculation formula is as follows:

[0089] p prior_comtrast =w p *p h

[0090] Among them, w prepresents the weight coefficient, p h represents the high energy projection image, p prior_comtrast represents the contrast compensated prior image.

[0091] By performing contrast compensation on the high-energy projection image based on the low-energy projection image, the image detail and visual quality can be significantly improved. By normalizing the grayscale of the low-energy projection image, the generated weight coefficient can effectively reflect the importance of different regions. The local contrast of each pixel is calculated, and these local contrasts are combined with the weight coefficient to obtain an updated contrast, and a contrast-compensated prior image is synthesized, which not only enhances the image quality, but also provides a clearer basis for subsequent analysis and improves the overall effect of image processing.

[0092] S3. Calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression priori image.

[0093] In the embodiment of the present invention, the calculating effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image includes:

[0094] Acquire a modulation coefficient between the high-energy projection image and the low-energy projection image;

[0095] Calculating the high-energy projection image and the low-energy projection image according to the modulation coefficient to obtain a synthetic energy projection image;

[0096] The synthetic energy projection image and the high energy projection image are weightedly fused to obtain an artifact suppression prior image.

[0097] In detail, the high-energy projection image and the low-energy projection image are calculated according to the modulation coefficient to obtain a synthetic energy projection image that is beneficial to artifact suppression. The calculation formula is as follows:

[0098] P composition (i) = P h (i)+α*[p h (i)―p l (i)]

[0099] Among them, P h (i) represents the i-th pixel value in the high-energy projection image, α represents the adjustable modulation coefficient, and p l (i) represents the i-th pixel value in the low-energy projection image, P composition (i) represents the i-th pixel value in the synthetic energy projection image.

[0100] The synthetic energy projection image and the high energy projection image are weightedly fused to obtain an artifact suppression prior image. The calculation formula is as follows:

[0101] P prior_artfect (i) = w*P compostion (i)+(1―w)*P h (i)

[0102] Among them, w represents the adjustable weight coefficient, P compostion (i) represents the i-th pixel value in the synthetic energy projection image, P h (i) represents the i-th pixel value in the high-energy projection image, P prior_artfect (i) represents the i-th pixel value in the artifact suppression prior image.

[0103] By obtaining the modulation coefficient between the high-energy projection image and the low-energy projection image, the contrast relationship between the two images in different energy states can be effectively quantified. After calculating the high-energy projection image and the low-energy projection image using the modulation coefficient, the generated synthetic energy projection image can more comprehensively display the structural features of the target. The synthetic energy projection image is then weightedly fused with the high-energy projection image, which helps to significantly suppress artifacts and improve image clarity.

[0104] S4, performing threshold segmentation on the high-energy projection image, and forward projecting the image after threshold segmentation to obtain a high-density mask projection image.

[0105] In the embodiment of the present invention, the step of performing threshold segmentation on the high-energy projection image and forward projecting the image after threshold segmentation to obtain a high-density mask projection image includes:

[0106] Performing three-dimensional reconstruction on the high-energy projection image to obtain a high-energy attenuation image;

[0107] Setting a pixel value in the high-energy attenuation image that is greater than a preset pixel threshold as a first pixel value;

[0108] Setting the pixel value in the high-energy attenuation image that is less than or equal to the pixel threshold as a second pixel value;

[0109] Combining a plurality of the first pixel values ​​and a plurality of the second pixel values ​​into a high-density mask image;

[0110] Get the ray-driven forward projection operator;

[0111] The high-density mask image is projected according to the ray-driven forward projection operator to obtain a high-density mask projection image.

[0112] In detail, the 3D reconstruction adopts the FDK reconstruction method, which mainly uses the ramp filter operator and the weighted back-projection operator to reconstruct the 2D projection data into a 3D spatial image to obtain a high-energy attenuation image.

[0113] Specifically, the pixel value in the high-energy attenuation image is compared with the pixel threshold, and the high-energy attenuation image is segmented by threshold to obtain a high-density mask image. The high-density mask image I obtained by threshold segmentation is m (i) is a binary image, where the area with a value of 1 represents a high-density area and the area with a value of 0 represents the background. The calculation formula is as follows:

[0114]

[0115] Among them, I m (i) is the i-th pixel value in the high-density mask image, I h (i) is the i-th pixel in the high energy attenuation image, and t is the preset pixel threshold.

[0116] In detail, forward projection converts the image data in three-dimensional space into a two-dimensional projection image. The ray-driven forward projection operator projects the high-density mask image at different angles to generate a high-density mask projection image. The calculation formula is as follows:

[0117] p m (t,θ)=∫I m (x,y)δ(t―xcosθ―ysinθ)dydx

[0118] Among them, p m (t,θ) represents the projection value at angle θ and position t, δ represents the Dirac function, I m is the high-density mask image, and (x, y) represents the pixel coordinates in the high-density mask image.

[0119] By reconstructing the high-energy projection image in three dimensions, a high-energy attenuation image is obtained, which can effectively identify and separate high-density areas. Classifying pixel values ​​according to preset thresholds helps to clarify the characteristics of different materials or structures. The generated high-density mask image is convenient for subsequent analysis to ensure that key areas are accurately represented. Using the ray-driven forward projection operator to project the mask image not only improves the clarity and accuracy of the projected image, but also provides a reliable basis for further image processing and analysis.

[0120] S5. Perform weighted fusion on the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image.

[0121] In an embodiment of the present invention, weighted fusion of the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image includes:

[0122] Normalizing pixels in the high-density mask projection image to obtain a normalized image;

[0123] The normalized image is used to calculate pixels in the contrast compensation prior image and pixels in the artifact suppression prior image to obtain a mixed projection image.

[0124] In detail, the pixels in the high-density mask projection image are normalized to between 0 and 1.

[0125] In detail, the contrast compensation prior image and the artifact suppression prior image are weightedly fused according to the high-density mask projection image to obtain a mixed projection image. The calculation formula is as follows:

[0126] p hybird (i) = p m (i)*P prior_artfect (i)+[1―p m (i)]·P prior_artfect (i)

[0127] Among them, p hybird (i) represents the i-th pixel value in the mixed projection image, p m (i) represents the i-th pixel value in the high-density mask projection image, P prior_artfect (i) represents the i-th pixel value in the artifact suppression prior image.

[0128] By normalizing the high-density mask projection image, the contrast and consistency of the image can be effectively improved, thereby enhancing the accuracy of subsequent processing. Using the normalized image to perform weighted fusion of the contrast compensation prior image and the artifact suppression prior image can integrate the information of different images while retaining details and suppressing artifacts. This method improves the quality of the mixed projection image, making the final result clearer and more usable.

[0129] S6. Perform three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

[0130] In an embodiment of the present invention, the three-dimensional reconstruction of the mixed projection image to obtain a mixed reconstructed image includes:

[0131] Obtaining the reconstruction volume and projection angle in the three-dimensional reconstruction parameters;

[0132] Performing filtering on the mixed projection image to obtain a plurality of filtered projection data;

[0133] superimposing each of the projection data into the reconstructed volume according to the projection angle;

[0134] The reconstructed volume is normalized to obtain a mixed reconstructed image.

[0135] In detail, the Ram-Lak filter is suitable for CT images and can effectively enhance the edges of the images. The mixed projection image is converted into the frequency domain using the fast Fourier transform, and the Ram-Lak filter is applied to the frequency domain data to enhance the frequency components of interest and suppress noise and low-frequency interference. The filtered frequency domain data is inversely transformed and returned to the spatial domain to obtain a filtered projection data set.

[0136] By obtaining the 3D reconstruction parameters and projection angles, an accurate 3D reconstruction volume can be effectively constructed. Filtering the mixed projection image can eliminate noise and artifacts and improve data quality. Superimposing the filtered projection data into the reconstructed volume according to the projection angle can fully reflect the structural details of the object, while the normalization process ensures the consistency and comparability of data at different angles, thereby ultimately obtaining a clear and accurate mixed reconstructed image.

[0137] like Figure 2 , which is a functional module diagram of a dual-energy cone-beam CT imaging device based on a priori guidance provided in one embodiment of the present application.

[0138] The dual-energy cone-beam CT imaging device 100 based on prior guidance of the present invention can be installed in an electronic device. According to the functions implemented, the dual-energy cone-beam CT imaging device 100 based on prior guidance can include an image acquisition module 101, a contrast compensation module 102, an artifact suppression module 103, an image segmentation module 104, an image fusion module 105 and an image reconstruction module 106. The module described in this application can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0139] In this embodiment, the functions of each module / unit are as follows:

[0140] An image acquisition module 101 is used to acquire high-energy projection data and low-energy projection data of a dual-energy cone-beam CT, and pre-process the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image;

[0141] A contrast compensation module 102, configured to perform contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image;

[0142] An artifact suppression module 103 is used to calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image, and obtain an artifact suppression prior image;

[0143] An image segmentation module 104 is used to perform threshold segmentation on the high-energy projection image, and forward project the image after threshold segmentation to obtain a high-density mask projection image;

[0144] An image fusion module 105 is used to perform weighted fusion of the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image;

[0145] The image reconstruction module 106 is used to perform three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

[0146] In detail, each module described in the dual-energy cone-beam CT imaging device 100 based on prior guidance in the embodiment of the present invention is used in the same manner as described above. Figure 1 The dual-energy cone-beam CT imaging method based on prior guidance described in the present invention has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0147] like Figure 3 , which is a schematic diagram of the structure of an electronic device for implementing a dual-energy cone-beam CT imaging method based on a priori guidance provided by an embodiment of the present invention.

[0148] The electronic device may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a dual-energy cone-beam CT imaging program based on a priori guidance.

[0149] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (ControlUnit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (for example, executing a dual-energy cone-beam CT imaging program based on prior guidance, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device and process data.

[0150] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 can also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the dual-energy cone-beam CT imaging program based on prior guidance, but also can be used to temporarily store data that has been output or is to be output.

[0151] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0152] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0153] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0154] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0155] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0156] The dual-energy cone-beam CT imaging program based on prior guidance stored in the memory 11 in the electronic device is a combination of multiple instructions. When running in the processor 10, it can achieve: acquiring high-energy projection data and low-energy projection data of dual-energy cone-beam CT, preprocessing the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image; performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image; calculating effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image; performing threshold segmentation on the high-energy projection image, and forward projecting the image after threshold segmentation to obtain a high-density mask projection image; performing weighted fusion on the contrast-compensated prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image; and performing three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

[0157] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0158] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0159] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can achieve the following: acquiring high-energy projection data and low-energy projection data of a dual-energy cone-beam CT, preprocessing the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image; performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast compensation prior image; calculating effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image; performing threshold segmentation on the high-energy projection image, and forward projecting the image after threshold segmentation to obtain a high-density mask projection image; performing weighted fusion on the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image; and performing three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

[0160] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0161] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0162] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0163] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0164] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0165] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0166] The embodiments of the present application can acquire and process relevant data based on image processing. Among them, image processing refers to the technology of operating and analyzing image data to extract information or improve image quality. It involves the application of various mathematical, computer algorithms and techniques to images to change, analyze or extract useful information from images. Image processing is an important part of the field of computer vision and artificial intelligence, and can be widely used in many fields such as medical treatment, industrial detection, security monitoring, automatic driving, entertainment, remote sensing, etc.

[0167] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0168] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A dual-energy cone-beam CT imaging method based on prior guidance, characterized in that: The method comprises: Acquire high-energy projection data and low-energy projection data of dual-energy cone-beam CT, and pre-process the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image; Performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image; Calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression priori image; Performing threshold segmentation on the high-energy projection image, and forward projecting the image after the threshold segmentation to obtain a high-density mask projection image; According to the high-density mask projection image, weighted fusion is performed on the contrast compensation prior image and the artifact suppression prior image to obtain a mixed projection image; The mixed projection image is three-dimensionally reconstructed to obtain a mixed reconstructed image.

2. The dual-energy cone-beam CT imaging method based on prior guidance according to claim 1, characterized in that: The preprocessing of the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image includes: Get the preset angle compensation parameters; Aligning the high-energy projection data and the low-energy projection data using the angle compensation parameter to obtain high-energy alignment data and low-energy alignment data; Acquire background signal and transmission signal from a preset detector; Counting the number of the background signals as the number of incident photons; Counting the number of the transmission signals as the number of outgoing photons; A high-energy attenuation projection of the high-energy alignment data and a low-energy attenuation projection of the low-energy alignment data are calculated according to the number of incident photons and the number of outgoing photons; A high-energy projection image and a low-energy projection image are generated according to the high-energy attenuation projection and the low-energy attenuation projection.

3. The dual-energy cone-beam CT imaging method based on prior guidance according to claim 1, characterized in that: The step of performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image includes: Normalizing the grayscale of the low-energy projection image to obtain a weight coefficient; Compensating each pixel in the high-energy projection image according to the weight coefficient to obtain an updated pixel value of each pixel; The updated pixel value of each pixel is synthesized into a contrast compensated prior image.

4. The dual-energy cone-beam CT imaging method based on prior guidance according to claim 1, characterized in that: The calculating effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image to obtain an artifact suppression prior image includes: Acquire a modulation coefficient between the high-energy projection image and the low-energy projection image; Calculating the high-energy projection image and the low-energy projection image according to the modulation coefficient to obtain a synthetic energy projection image; The synthetic energy projection image and the high energy projection image are weightedly fused to obtain an artifact suppression prior image.

5. The dual-energy cone-beam CT imaging method based on prior guidance according to claim 1, characterized in that: The step of performing threshold segmentation on the high-energy projection image and forward projecting the image after threshold segmentation to obtain a high-density mask projection image includes: Performing three-dimensional reconstruction on the high-energy projection image to obtain a high-energy attenuation image; Setting a pixel value in the high-energy attenuation image that is greater than a preset pixel threshold as a first pixel value; Setting the pixel value in the high-energy attenuation image that is less than or equal to the pixel threshold as a second pixel value; Combining a plurality of the first pixel values ​​and a plurality of the second pixel values ​​into a high-density mask image; Get the ray-driven forward projection operator; The high-density mask image is projected according to the ray-driven forward projection operator to obtain a high-density mask projection image.

6. The dual-energy cone-beam CT imaging method based on prior guidance according to claim 1, characterized in that: The step of weightedly fusing the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image includes: Normalizing pixels in the high-density mask projection image to obtain a normalized image; The normalized image is used to calculate pixels in the contrast compensation prior image and pixels in the artifact suppression prior image to obtain a mixed projection image.

7. The dual-energy cone-beam CT imaging method based on a priori guidance according to claim 1, characterized in that: The three-dimensional reconstruction of the mixed projection image to obtain a mixed reconstructed image includes: Obtaining the reconstruction volume and projection angle in the three-dimensional reconstruction parameters; Performing filtering on the mixed projection image to obtain a plurality of filtered projection data; superimposing each of the projection data into the reconstructed volume according to the projection angle; The reconstructed volume is normalized to obtain a mixed reconstructed image.

8. A dual-energy cone-beam CT imaging device based on prior guidance, characterized in that: The device comprises: An image acquisition module, used for acquiring high-energy projection data and low-energy projection data of dual-energy cone-beam CT, and preprocessing the high-energy projection data and the low-energy projection data to obtain a high-energy projection image and a low-energy projection image; A contrast compensation module, used for performing contrast compensation on the high-energy projection image according to the low-energy projection image to obtain a contrast-compensated prior image; An artifact suppression module is used to calculate effective energy projection information for effectively suppressing artifacts according to the high-energy projection image and the low-energy projection image, and obtain an artifact suppression prior image; An image segmentation module, used for performing threshold segmentation on the high-energy projection image, and forward projecting the image after threshold segmentation to obtain a high-density mask projection image; An image fusion module, configured to perform weighted fusion of the contrast compensation prior image and the artifact suppression prior image according to the high-density mask projection image to obtain a mixed projection image; The image reconstruction module is used to perform three-dimensional reconstruction on the mixed projection image to obtain a mixed reconstructed image.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the dual-energy cone-beam CT imaging method based on a priori guidance as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the dual-energy cone-beam CT imaging method based on a priori guidance as claimed in any one of claims 1 to 7 is implemented.

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