WO2022001358A1 - 图像处理方法、装置、计算机设备、存储介质及标测系统 - Google Patents

图像处理方法、装置、计算机设备、存储介质及标测系统 Download PDF

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WO2022001358A1
WO2022001358A1 PCT/CN2021/091872 CN2021091872W WO2022001358A1 WO 2022001358 A1 WO2022001358 A1 WO 2022001358A1 CN 2021091872 W CN2021091872 W CN 2021091872W WO 2022001358 A1 WO2022001358 A1 WO 2022001358A1
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dimensional
image
model
myocardial fibrosis
region
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PCT/CN2021/091872
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French (fr)
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宫晶晶
沈刘娉
孙毅勇
曹先锋
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上海微创电生理医疗科技股份有限公司
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Priority to US18/001,203 priority Critical patent/US20230230230A1/en
Priority to EP21832037.2A priority patent/EP4148670A4/en
Publication of WO2022001358A1 publication Critical patent/WO2022001358A1/zh

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Definitions

  • the present application relates to the technical field of medical equipment, and in particular, to an image processing method, apparatus, computer equipment, storage medium and mapping system.
  • Catheter ablation is a widely used method for the treatment of arrhythmia at present, mainly under the monitoring of X-ray angiography machine, the catheter is inserted into the heart by puncturing the blood vessel, and the location of the lesion causing the arrhythmia is first checked to determine the location of the arrhythmia, and then release it at the location of the lesion.
  • Energy such as radio frequency, cryotherapy, ultrasound, laser, etc., causes tissue necrosis to block abnormal signal conduction paths, so as to achieve the purpose of treatment.
  • the three-dimensional mapping system has been widely used in the field of electrophysiology, and the ablation operation under the guidance of the three-dimensional mapping system is also a recognized method for the treatment of arrhythmia.
  • the electroanatomical map in the three-dimensional mapping system cannot fully reflect the myocardial activity, resulting in inaccurate location of the lesion.
  • An image processing method comprising:
  • the imaging image including a plurality of tomographic images
  • Three-dimensional reconstruction is performed according to the plurality of tomographic images to obtain the three-dimensional image model; wherein, the three-dimensional image model includes a three-dimensional myocardial fibrosis region image;
  • the three-dimensional electroanatomical model comprising a three-dimensional abnormal myocardial tissue image
  • the three-dimensional image model and the three-dimensional electroanatomical model are registered, and the overlapping part of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image is determined as the lesion position.
  • the calculation is performed according to the three-dimensional model of the myocardial fibrosis region to obtain the height, width, thickness, volume and surface area of the myocardial fibrosis region. Then, according to the relationship between the height, width, thickness, volume, surface area of the myocardial fibrosis region and the ablation indication parameter, an ablation strategy for reference is generated to guide the doctor to perform the ablation operation.
  • An image processing device comprising:
  • a first acquisition module configured to acquire an imaging image, wherein the imaging image includes a plurality of tomographic images
  • a three-dimensional reconstruction module configured to perform three-dimensional reconstruction according to the plurality of tomographic images to obtain the three-dimensional image model; wherein, the three-dimensional image model includes a three-dimensional myocardial fibrosis region image;
  • a second acquisition module configured to acquire a three-dimensional electroanatomical model, where the three-dimensional electroanatomical model includes a three-dimensional abnormal myocardial tissue image;
  • the image registration module is used for registering the three-dimensional image model and the three-dimensional electroanatomical model, and determining the overlapping part of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image as the lesion location.
  • mapping system comprising:
  • the mapping module is used to obtain a three-dimensional positioning signal from the catheter and construct a three-dimensional cardiac cavity model according to the three-dimensional positioning signal, and superimpose the collected electrophysiological information of the mapping points on the three-dimensional cardiac cavity model to generate a three-dimensional electroanatomy Model;
  • an image processing module which implements the steps of the image processing method in any of the above-mentioned embodiments
  • a display module configured to display the three-dimensional electroanatomical model, the three-dimensional myocardial fibrosis region image, and the registration process of the three-dimensional electroanatomical model and the three-dimensional image model.
  • a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the method steps in any of the foregoing embodiments when the processor executes the computer program.
  • the imaging image includes a plurality of tomographic images; three-dimensional reconstruction is performed according to the plurality of tomographic images to obtain the three-dimensional image.
  • One or more of the height, width, thickness, volume and surface area of the myocardial fibrosis area are obtained by calculation, and displayed on the three-dimensional mapping system, so that the operator has a better understanding of the lesion area and ablation of the lesion area. It is more thorough and greatly reduces the recurrence rate. And according to the relationship between one or more of the height, width, thickness, volume and surface area of the myocardial fibrosis area and the ablation indication parameter, an ablation strategy for reference is generated, which shortens the learning period for the operator to apply the system. , thereby greatly shortening the operation time and making the operation simpler.
  • FIG. 1 is a schematic flowchart of an image processing method in one embodiment
  • FIG. 2 is a schematic flowchart of an image processing method in one embodiment
  • 3a is a schematic flowchart of an image processing method in one embodiment
  • Figure 3b is a schematic diagram of a myocardial fibrosis region in one embodiment
  • FIG. 4 is a schematic flowchart of an image processing method in one embodiment
  • FIG. 5 is a schematic flowchart of an image processing method in one embodiment
  • 6a is a schematic flowchart of an image processing method in one embodiment
  • 6b is a schematic flowchart of an image processing method in one embodiment
  • 6c is a structural block diagram of an image processing apparatus in one embodiment
  • FIG. 7 is a block diagram of a module of a three-dimensional mapping system in one embodiment
  • FIG. 8 is a schematic structural diagram of a three-dimensional mapping system in one embodiment
  • Figure 9 is a diagram of the internal structure of a computer device in one embodiment.
  • Arrhythmia refers to the abnormality of the normal rhythm of the heart, and arrhythmias that are faster than the normal heart rate (60-100 beats/min) are tachyarrhythmias. In severe cases, chest pain, difficulty breathing, loss of consciousness, and even stroke may occur.
  • Catheter ablation is a widely used method for the treatment of cardiac arrhythmia, mainly under the monitoring of X-ray angiography machine, the catheter is inserted into the heart by puncturing the blood vessel, and the abnormal location that causes the tachycardia is first checked to determine the abnormal location of the tachycardia. Release energy such as radio frequency, cryotherapy, ultrasound, laser, etc., to make tissue necrotic to block abnormal signal conduction paths, so as to achieve the purpose of treatment.
  • Circumferential pulmonary vein isolation under the guidance of three-dimensional mapping system is a recognized method for the treatment of non-sustained atrial fibrillation.
  • new ablation techniques have been developed in recent years, such as pressure catheter-based radiofrequency ablation, balloon catheter-based cryoablation, etc., due to the unknown mechanism of arrhythmia, the location of the lesion is not easy to determine, and the success rate of ablation is still low. And the recurrence rate after surgery is also high. Studies have shown that more than 80% of the recurrence of atrial fibrillation is due to incomplete isolation of the pulmonary veins, resulting in electrical signal conduction between the pulmonary veins and the left atrium; some studies suggest that it may be related to myocardial fibrosis.
  • Myocardial fibrosis is the result of persistent or repeated aggravation of myocardial ischemia and hypoxia in myocardial fibers caused by moderate or severe coronary atherosclerotic stenosis, accompanied by increased cardiac volume, increased weight, dilation of all cardiac chambers, Wall thickness may be normal, but there are multifocal white fibrous cords or masses, even transmural scarring, or the endocardium is thickened and loses its normal luster, sometimes a mural thrombus is seen, and clinically manifests as arrhythmias or cardiac failure exhaustion.
  • clinical myocardial biopsy can identify myocardial fibrosis, it has problems such as invasiveness and limitations in the diagnostic area.
  • Imaging detection such as MRI (Magnetic Resonance Imaging), CT (Computed Tomography) and PET (Positron Emission Tomography) has the characteristics of non-invasiveness, while MRI has the advantages of accurate localization, Wide range, high precision and non-invasive advantages.
  • LGE-MRI late gadolinium-enhanced magnetic resonance imaging
  • imaging diagnosis is mostly used for the formulation of ablation strategies before ablation and the evaluation of postoperative effects; Due to the influence of factors, the recorded map cannot fully reflect the myocardial activity. Therefore, the present application creatively combines imaging images and mapping maps to achieve precise location of the lesion to guide the ablation operation.
  • an image processing method is provided, and the method includes the following steps:
  • the imaging image may be any one of CT image, PET image, MRI image or LGE-MRI image.
  • the imaging images include multiple slice images.
  • Tomographic images can more accurately show the fibrosis of myocardial tissue, such as the degree of fibrosis, the extent and shape of fibrotic tissue.
  • the imaging image can be stored locally on the computer in advance, and the imaging image is loaded and imported through the image import module, so as to obtain the imaging image.
  • three-dimensional reconstruction can be used in the process of establishing a mathematical model suitable for computer representation and processing of myocardial tissue.
  • the mathematical model obtained by 3D reconstruction is the basis for processing, operating and analyzing the properties of myocardial tissue in a computer environment, and is also a key technology for expressing myocardial tissue or cardiac chamber parts in a computer environment. Areas of myocardial fibrosis are the result of persistent or repeated aggravation of myocardial ischemia and hypoxia in myocardial fibers caused by moderate or severe coronary atherosclerotic stenosis.
  • the imaging image is imported into the 3D mapping system, and the imaging image is 3D reconstructed by the 3D mapping system.
  • the 3D reconstructed 3D model can be used to map the myocardial fibrosis area. Displayed, a three-dimensional image model is obtained, and the three-dimensional image model includes a three-dimensional myocardial fibrosis region image. Further, different colors can be used to identify normal areas and fibrotic areas, and the number, location and extent of myocardial fibrosis areas can be displayed in an intuitive manner.
  • three-dimensional mapping is a mapping technology that uses catheter movement and records electrocardiographic information, and its principle is similar to the global positioning system (GPS).
  • the three-dimensional electroanatomical model is a three-dimensional image produced by mapping the myocardium or cardiac chamber.
  • the location sensor (such as magnetic positioning sensor or electrical positioning sensor) on the catheter is used to collect mapping points to construct a cardiac cavity geometric model (or a three-dimensional cardiac cavity anatomical model), and to collect multiple mapping points evenly distributed in the cardiac cavity in a point-by-point manner .
  • the ECG signal is collected by the signal sensor in the cardiac chamber, the activation time or voltage of each mapping point is calculated, and the markers are marked with different colors and superimposed on the cardiac chamber geometric model to generate a three-dimensional electroanatomical model.
  • the three-dimensional electroanatomical model includes three-dimensional images of abnormal myocardial tissue.
  • the three-dimensional abnormal myocardial tissue image may be a low-voltage area and/or a scar area.
  • the catheter is closely attached to the inner wall of the chamber to perform mapping at different positions, using the catheter position information and the collected ECG signals to construct a three-dimensional cardiac chamber geometric model and superimpose the electrophysiological information to form a three-dimensional electroanatomical model.
  • different colors can be used to distinguish normal and abnormal myocardial regions, and further use, for example, color to divide abnormal myocardial regions into low-voltage areas and scar areas, typically less than 0.05-0.1 mv for atrial tissue and less than 0.05-0.1 mv for ventricular tissue. 0.5mv was defined as the scar area.
  • the low voltage zone can be set by the user according to the actual situation.
  • the activity of local myocardial tissue can be understood, for example, the distribution of the scar area can be marked, which can help to analyze the mechanism of arrhythmia formation and maintenance.
  • S140 register the three-dimensional image model with the three-dimensional electroanatomical model, and determine the overlapping portion of the image of the myocardial fibrosis area and the image of the abnormal myocardial tissue as the lesion location.
  • imaging images are usually used as preoperative diagnosis, which can preliminarily determine the location and extent of myocardial fibrosis.
  • the abnormal myocardial tissue area in the three-dimensional electroanatomical model is related to myocardial fibrosis to a certain extent, not all fibrotic areas are All are abnormal and require ablation. Therefore, the 3D image model and the 3D electroanatomical model can be fused to more accurately locate the lesion location for effective ablation.
  • the three-dimensional image model is displayed, and it can be translated, rotated, zoomed or displayed from other conventional perspectives, and the three-dimensional image model is registered with the three-dimensional electroanatomical model, and the three-dimensional myocardial fibrosis region image on the three-dimensional image model and If the three-dimensional abnormal myocardial tissue images in the three-dimensional electroanatomical model have overlapping parts, the overlapping parts can be determined as the location of the lesions.
  • the imaging images include multiple tomographic images; performing three-dimensional reconstruction according to the multiple tomographic images to obtain a three-dimensional image model, wherein the three-dimensional image model includes three-dimensional myocardial fibrosis region images; Electroanatomical model, the three-dimensional electroanatomical model includes three-dimensional abnormal myocardial tissue images; since there is a certain corresponding relationship between the abnormal myocardial tissue area and myocardial fibrosis in the three-dimensional electroanatomical model, the three-dimensional image model is matched with the three-dimensional electroanatomical model.
  • the tomographic image includes a two-dimensional image of a region of myocardial fibrosis. As shown in FIG. 2 , before the three-dimensional reconstruction is performed according to the multiple tomographic images to obtain the three-dimensional image model, the method further includes the following steps:
  • denoising processing refers to the process of reducing noise in tomographic images.
  • the tomographic image in addition to the cardiac cavity region, the tomographic image also includes images of other regions such as the trunk and ribs, and the images of other regions in the tomographic image are regarded as noise removal; on the other hand, the tomographic image still has some low pixels Or the unclear area is mixed, and the tomographic image is denoised based on some filtering principles.
  • the basic idea of mathematical morphology is to use structural elements with a certain shape to measure and extract the corresponding shape in the image to achieve the purpose of image analysis and recognition, which can simplify the image data, maintain their basic shape characteristics, and remove undesired shapes. coherent structure.
  • Mathematical morphology consists of a set of morphological algebraic operators, and the basic operations include dilation (or dilation), erosion (or erosion), opening and closing, etc.
  • the grayscale image of the cardiac chamber contains the grayscale information of the myocardial tissue region, and the other regions except the heart in the grayscale image of the cardiac chamber are set to the same grayscale value or the same color, that is, the other regions are set as the background.
  • the position coordinates of the cardiac cavity region in the imaging image are obtained, and based on the relevant operations of mathematical morphology, the grayscale distribution characteristics of the imaging image are extracted according to the cardiac cavity region coordinates, and the grayscale information of the cardiac cavity region image is obtained. .
  • other region images in each tomographic image are set as the background, so as to obtain the cardiac chamber grayscale images.
  • the feature extraction of the heart region is performed on the imaging image to obtain the grayscale image of the cardiac cavity, and it is necessary to further distinguish the fibrotic region and the non-fibrotic region from the grayscale image of the cardiac cavity.
  • the gray distribution information of the image is counted, wherein the area with high gray value represents the myocardial fibrosis area in the image, and the area with low gray value represents the non-fibrotic myocardial area in the image, and then filter based on different Principle of denoising to identify myocardial fibrosis areas in grayscale images of cardiac chambers.
  • the myocardial fibrosis region in the grayscale image of the cardiac cavity is identified, which is used for the subsequent image segmentation and three-dimensional image model. It lays the foundation for the reconstruction of myocardial fibrosis, and accurately identifies the area of myocardial fibrosis, which is conducive to the establishment of a 3D model that is more in line with the actual situation, and further improves the accuracy of the location of the lesion.
  • the step of performing 3D reconstruction according to a plurality of tomographic images to obtain a 3D image model includes: S310. Perform image segmentation on each cardiac cavity grayscale image according to the identified myocardial fibrosis region. , to obtain multiple corresponding two-dimensional images of myocardial fibrosis regions.
  • the step of registering the three-dimensional image model with the three-dimensional electroanatomical model includes: S330 , registering the first three-dimensional model with the three-dimensional electroanatomical model.
  • image segmentation is to perform feature extraction on the preprocessed image.
  • a segmentation algorithm that measures the complexity of tissue spatial distribution characterized by fibrotic tissue, such as density and clustering, can be designed to determine within a predetermined range. Whether there is a certain degree of fibrosis, distinguish between fibrotic and non-fibrotic areas, producing an image based on the characteristics of the fibrotic tissue, and the color can represent the degree of fibrosis.
  • Image segmentation algorithms can be LevelSet segmentation, Graph Cuts segmentation, watershed segmentation based on morphological transformation, region growth segmentation, etc.
  • each cardiac cavity grayscale image is segmented by an image segmentation module to obtain a corresponding two-dimensional myocardial fibrosis region image.
  • the 2D myocardial fibrosis region image obtained after image segmentation is reconstructed in 3D, and multiple 2D myocardial fibrosis region images are reconstructed into a 3D model of the myocardial fibrosis region, which can visually display the 3D structure of myocardial fiber tissue.
  • the 3D model is registered with the 3D electroanatomical model. If the 3D myocardial fibrosis region image on the 3D model overlaps with the 3D abnormal myocardial tissue image in the 3D electroanatomical model, the overlapped part can be determined as the location of the lesion. .
  • the mottled area shown in the figure is a fibrotic tissue
  • the area with uniform grayscale shown in the figure is a normal tissue. It can be understood that different colors can be used to identify normal tissue and fibrotic tissue, so as to visually display the number, location and extent of myocardial fibrosis areas.
  • the step of performing 3D reconstruction according to a plurality of tomographic images to obtain a 3D image model includes: S410 , performing 3D reconstruction using each cardiac cavity grayscale image to obtain a second 3D model, and The second three-dimensional model is marked with a three-dimensional myocardial fibrosis region image.
  • the step of registering the three-dimensional image model with the three-dimensional electroanatomical model includes: S420, registering the second three-dimensional model with the three-dimensional electroanatomical model.
  • the second three-dimensional model is a three-dimensional model of the entire cardiac cavity.
  • the chest cavity of the human body is scanned to obtain an imaging image, and the imaging image includes a plurality of tomographic images.
  • the tomographic image is subjected to operations such as denoising, morphological processing, and image grayscale distribution feature extraction to obtain a cardiac cavity grayscale image.
  • the constructed second three-dimensional model is registered with the three-dimensional electroanatomical model.
  • the overlapping part can be Determine the location of the lesion.
  • the average registration error, the maximum registration error and the minimum registration error between the 3D image model and the 3D electroanatomical model can also be calculated, A measure of how well each region matches.
  • the method further includes the following steps:
  • the three-dimensional structure of the myocardial fiber tissue can be segmented from the second three-dimensional model. Specifically, it is displayed layer by layer in the order from the endocardium to the epicardium, so as to clearly understand the degree of fibrosis of each layer of myocardial tissue.
  • the fibrosis regions in each layer of the image can be individually segmented and extracted; on the other hand, a specific fibrosis range can also be selected for separate extraction, such as setting seed points and using the region growth algorithm to separate all layers.
  • the fibrotic regions of the myocardial tissue are extracted separately, and then three-dimensional reconstruction is performed on them to obtain a three-dimensional model of the myocardial fibrosis region, which can visually display the three-dimensional structure of myocardial fiber tissue.
  • the 3D model of the myocardial fibrosis area is registered with the 3D electroanatomical model, and if there is an overlap between the 3D myocardial fibrosis area image and the 3D abnormal myocardial tissue image in the 3D electroanatomical model, the overlapped part can be determined as lesion location.
  • the method further includes the following steps: calculating according to the three-dimensional model of the myocardial fibrosis region to obtain one or more of the height, width, thickness, volume, and surface area of the myocardial fibrosis region. Further, an ablation strategy for reference is generated according to one or more of the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • the fibrosis region in each layer of the image is extracted separately, and the three-dimensional reconstruction of the fibrosis region image of each layer is used to obtain a three-dimensional model of the myocardial fibrosis region.
  • calculate the three-dimensional model of the myocardial fibrosis area and obtain parameters such as height, width, thickness, volume, and surface area of the myocardial fibrosis area.
  • the ablation indication parameters are determined according to the height, width, thickness, volume, and surface area of the myocardial fibrosis area, and an ablation strategy is generated for the operation. refer to.
  • the ablation strategy includes the settings of parameters such as ablation integral value, ablation diameter, ablation depth, pressure value, power, temperature, impedance, and time. In this embodiment, a more reasonable reference is provided for the operator through the ablation strategy.
  • the three-dimensional electroanatomical model includes a three-dimensional activation conduction map and/or a three-dimensional voltage map; registering the three-dimensional image model with the three-dimensional electroanatomical model includes: registering the three-dimensional image model with the three-dimensional activation conduction map; And/or, registering the three-dimensional image model with the three-dimensional voltage map.
  • the three-dimensional excitation conduction map and the three-dimensional voltage map are two different presentation methods selected when performing 3D cardiac electrophysiological mapping.
  • the three-dimensional excitation conduction map shows the path of ECG signal conduction
  • the three-dimensional voltage map shows the voltage difference of the ECG signal.
  • the three-dimensional image model can be a three-dimensional model of a myocardial fibrosis area, and the three-dimensional model is registered with the three-dimensional electroanatomical model, and the three-dimensional myocardial fibrosis area image on the three-dimensional model and the three-dimensional abnormal myocardial tissue image in the three-dimensional electroanatomical model are registered. If there is an overlapping portion, the overlapping portion can be determined as the location of the lesion.
  • the three-dimensional image model may also be a three-dimensional model of a cardiac chamber marked with images of myocardial fibrosis regions (ie, a three-dimensional model of the entire cardiac chamber).
  • the constructed 3D model of the cardiac chamber is registered with the 3D electroanatomical model. If there is an overlap between the 3D myocardial fibrosis region image on the 3D model of the cardiac chamber and the 3D abnormal myocardial tissue image in the 3D electroanatomical model, the overlapping part can be adjusted. Determine the location of the lesion.
  • the scar area, the low voltage area, and the myocardial fibrosis area are different representations of the abnormal myocardial area, and the three represent the abnormal myocardial area from different angles, it may be more effective to combine the three. And accurately identify the specific lesion site.
  • the present application provides an image processing method, as shown in Figure 6a, the method includes the following steps:
  • the imaging image includes a plurality of tomographic images, and the tomographic images include two-dimensional myocardial fibrosis region images.
  • the imaging images can be stored in the image file management module, and the image file management module is mainly responsible for managing files, loading files, acquiring file information, and storing intermediate files that require preprocessing or other operations. Select the imaging image in the image file management module through the image import module, load and import it to perform a series of processing operations on the imaging image.
  • S606a Based on mathematical morphology, obtain the coordinates of the cardiac cavity region in each of the tomographic images, extract the grayscale information of the cardiac cavity region images in the corresponding tomographic images according to the cardiac cavity region coordinates, and convert the Images of other regions were set as the background to obtain grayscale images of cardiac chambers.
  • S608a Perform statistics on the grayscale information of each cardiac chamber grayscale image to identify the myocardial fibrosis region in the cardiac chamber grayscale image.
  • S610a Perform image segmentation on each cardiac chamber grayscale image according to the identified myocardial fibrosis region, to obtain a plurality of corresponding two-dimensional myocardial fibrosis region images.
  • the three-dimensional model of the myocardial fibrosis region includes a three-dimensional myocardial fibrosis region image.
  • the three-dimensional electroanatomical model includes three-dimensional images of abnormal myocardial tissue.
  • S616a register the three-dimensional model of the myocardial fibrosis region with the three-dimensional electroanatomical model, and determine the overlapping portion of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image as the lesion location.
  • the present application provides an image processing method, as shown in Figure 6b, the method includes the following steps:
  • the imaging image includes a plurality of tomographic images, and the tomographic images include two-dimensional myocardial fibrosis region images.
  • S606b based on mathematical morphology, extract the grayscale information of the cardiac cavity region image in the corresponding tomographic image according to the cardiac cavity region coordinates, and set other region images in each tomographic image as the background to obtain the cardiac cavity grayscale image.
  • S608b Count the grayscale information of each cardiac chamber grayscale image to identify the myocardial fibrosis region in the cardiac chamber grayscale image.
  • the three-dimensional electroanatomical model includes three-dimensional images of abnormal myocardial tissue.
  • the three-dimensional electroanatomical model includes a three-dimensional activation conduction map and/or a three-dimensional voltage map.
  • S618b register the three-dimensional model of the myocardial fibrosis region with the three-dimensional electroanatomical model, and determine the overlapping portion of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image as the lesion location.
  • S624b Calculate and display the average registration error, the maximum registration error, and the minimum registration error between the three-dimensional image model and the three-dimensional electroanatomical model.
  • steps in the flowcharts of the above embodiments are sequentially displayed in accordance with the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in the above embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times. These sub-steps or stages are not necessarily completed at the same time. The order of execution of the steps is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of sub-steps or stages of other steps.
  • an image processing apparatus 600 including: a first acquisition module 610, a three-dimensional reconstruction module 620, a second acquisition module 630, and an image registration module 640, wherein:
  • the first acquisition module 610 is configured to acquire imaging images, where the imaging images include a plurality of tomographic images;
  • the three-dimensional reconstruction module 620 is configured to perform three-dimensional reconstruction according to the plurality of tomographic images to obtain the three-dimensional image model; wherein, the three-dimensional image model includes a three-dimensional myocardial fibrosis region image;
  • the second acquisition module 630 is configured to acquire a three-dimensional electroanatomical model, where the three-dimensional electroanatomical model includes a three-dimensional abnormal myocardial tissue image;
  • the image registration module 640 is configured to register the three-dimensional image model with the three-dimensional electroanatomical model, and determine the overlapping portion of the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue image as a lesion location.
  • the tomographic image includes regions of myocardial fibrosis.
  • the device also includes:
  • a denoising processing module for performing denoising processing on each of the tomographic images
  • the first extraction module is used to obtain the coordinates of the cardiac cavity region in each of the tomographic images based on mathematical morphology, extract the grayscale information of the cardiac cavity region images of the corresponding tomographic images according to the cardiac cavity region coordinates, and convert each tomographic image.
  • the images of other regions of the tomographic image are set as the background to obtain a grayscale image of the cardiac cavity;
  • the fibrosis identification module is configured to perform statistics on the grayscale information of each cardiac cavity image, and identify the myocardial fibrosis region in the cardiac cavity grayscale image.
  • the three-dimensional reconstruction module 620 is further configured to perform image segmentation on each of the cardiac chamber grayscale images according to the identified myocardial fibrosis region, to obtain multiple corresponding two-dimensional myocardial fibrosis region images;
  • the two-dimensional image of the myocardial fibrosis region is taken for three-dimensional reconstruction to obtain a first three-dimensional model, and the first three-dimensional model is used as the three-dimensional model of the myocardial fibrosis region;
  • the image registration module 640 is further configured to register the first three-dimensional model with the three-dimensional electroanatomical model.
  • the three-dimensional reconstruction module 620 is further configured to perform three-dimensional reconstruction using each grayscale image of the cardiac chamber to obtain a second three-dimensional model; the second three-dimensional model is a three-dimensional model of the entire cardiac chamber and the third The three-dimensional myocardial fibrosis region is marked on the two-dimensional model;
  • the image registration module 640 is further configured to register the second three-dimensional model with the three-dimensional electroanatomical model.
  • the device further includes: a second acquisition module configured to extract, layer by layer, the two-dimensional myocardial fibrosis region in each layer of the image of the second three-dimensional model in the order from the endocardium to the epicardium and, the three-dimensional model reconstruction module is used for reconstructing the extracted two-dimensional myocardial fibrosis region images of each layer to obtain a three-dimensional model of the myocardial fibrosis region;
  • a second acquisition module configured to extract, layer by layer, the two-dimensional myocardial fibrosis region in each layer of the image of the second three-dimensional model in the order from the endocardium to the epicardium and, the three-dimensional model reconstruction module is used for reconstructing the extracted two-dimensional myocardial fibrosis region images of each layer to obtain a three-dimensional model of the myocardial fibrosis region;
  • the image registration module 640 is further configured to register the three-dimensional model of the myocardial fibrosis region with the three-dimensional electroanatomical model.
  • the device further includes: a first calculation module, configured to perform calculation according to the three-dimensional model of the myocardial fibrosis region to obtain the height, width, thickness, volume and surface area of the myocardial fibrosis region.
  • a first calculation module configured to perform calculation according to the three-dimensional model of the myocardial fibrosis region to obtain the height, width, thickness, volume and surface area of the myocardial fibrosis region.
  • the device further comprises: an ablation strategy generation module, configured to generate an ablation strategy for reference according to the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • an ablation strategy generation module configured to generate an ablation strategy for reference according to the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • the three-dimensional electroanatomical model includes a three-dimensional activation conduction map and/or a three-dimensional voltage map; the image registration module 640 is further configured to register the three-dimensional image model with the three-dimensional activation conduction map; and/or, registering the three-dimensional image model with the three-dimensional voltage map.
  • the apparatus further includes: a second calculation module configured to calculate an average registration error, a maximum registration error and a minimum registration error between the three-dimensional image model and the three-dimensional electroanatomical model.
  • the three-dimensional activation conduction map reflects the conduction path of the ECG signal; the three-dimensional voltage map shows the voltage difference of the ECG signal; wherein, the three-dimensional voltage map identifies normal myocardial tissue regions and low-voltage regions and scar area; the three-dimensional abnormal myocardial tissue image includes the image of the low voltage area and/or the image of the scar area.
  • Each module in the above-mentioned image processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof.
  • the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
  • the present application provides a three-dimensional mapping system, as shown in FIG. 7 , the mapping system includes:
  • the mapping module 710 is used to obtain a three-dimensional positioning signal from the catheter and construct a three-dimensional cardiac cavity model according to the three-dimensional positioning signal, and superimpose the collected electrophysiological information of the mapping points on the three-dimensional cardiac cavity model to generate a three-dimensional electrophysiological model.
  • anatomical model
  • An image processing module 720 configured to implement the steps of the image processing method described in any one of the foregoing embodiments;
  • the display module 730 is configured to display the three-dimensional electroanatomical model, the three-dimensional myocardial fibrosis region image, and the registration process of the three-dimensional electroanatomical model and the three-dimensional image model.
  • the three-dimensional mapping system includes hardware equipment and software applications, wherein: the hardware equipment includes an interventional catheter with a positioning sensor, a positioning processing unit, a patient interface unit, a radio frequency instrument, a workstation, a display, and the like.
  • the hardware equipment includes an interventional catheter with a positioning sensor, a positioning processing unit, a patient interface unit, a radio frequency instrument, a workstation, a display, and the like.
  • the positioning sensor (magnetic field positioning or electric field positioning) is used to transmit and receive positioning signals; as shown in Figure 8, when the positioning sensor is a magnetic positioning sensor, the three-dimensional mapping system also includes a magnetic field generator; the positioning processing unit is used to control the magnetic field or The electric field generator works and processes and analyzes the positioning information; the patient interface unit is used to analyze and process the ECG signal, etc.; the computer workstation configures the software application for summarizing all the positioning information and ECG information, and reflects it on the display through the software to help the surgeon perform ablation better.
  • software applications include system status, patient information logging, case data management, image processing, and cardiac mapping.
  • the system status can monitor the connection and working conditions of hardware equipment in real time; patient information login is to record patient-related information such as name, gender, ID number and preliminary medical diagnosis information; case data management is to manage all case data, which can be used for cases Review; the image processing module includes image file management module, image segmentation module, 3D reconstruction module, image editing module and image registration module, etc.
  • the cardiac mapping module is used for catheter real-time display, cardiac cavity model construction, ECG signal real-time display and Recording of related events, display of images after registration, display of ablation parameters and ablation status, etc.
  • the mapping module may be a data processor, such as a computer CPU and GPU; the image processing module may be an image signal processor, such as another computer CPU and GPU; the display module may be a display; the data processor and The image signal processors may be two independent processors as described above. In other embodiments, the mapping module and the image processing module may also be the same processor, for example, the same CPU.
  • a computer device is provided, and the computer device may be a terminal, and its internal structure diagram may be as shown in FIG. 9 .
  • the computer equipment includes a processor, internal memory, a communication interface, a display screen, and an input device connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium, an internal memory.
  • the nonvolatile storage medium stores an operating system and a computer program.
  • the internal memory provides an environment for the execution of the operating system and computer programs in the non-volatile storage medium.
  • the communication interface of the computer device is used for wired or wireless communication with an external terminal, and the wireless communication can be realized by WIFI, operator network, NFC (Near Field Communication) or other technologies.
  • the computer program implements an image processing method when executed by a processor.
  • the display screen of the computer equipment may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment may be a touch layer covered on the display screen, or a button, a trackball or a touchpad set on the shell of the computer equipment , or an external keyboard, trackpad, or mouse.
  • FIG. 9 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.
  • a computer device including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program:
  • imaging images which include multiple tomographic images; performing three-dimensional reconstruction according to the multiple tomographic images to obtain the three-dimensional image model, where the three-dimensional image model includes three-dimensional myocardial fibrosis region images; acquiring a three-dimensional electroanatomical model , the three-dimensional electroanatomical model includes a three-dimensional abnormal myocardial tissue image; the three-dimensional image model and the three-dimensional electroanatomical model are registered, and the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue are determined.
  • the overlapping part of the images is the location of the lesion.
  • the processor further implements the following steps when executing the computer program: performing denoising processing on each of the tomographic images;
  • the regional coordinates extract the grayscale information of the cardiac cavity region image of the corresponding tomographic image, and set other regions of each of the tomographic images as the background to obtain the cardiac cavity grayscale image;
  • the information is counted, and the myocardial fibrosis area in the grayscale image of the cardiac chamber is identified.
  • the processor further implements the following steps when executing the computer program: image segmentation is performed on each of the cardiac chamber grayscale images according to the identified myocardial fibrosis regions to obtain a plurality of corresponding two-dimensional myocardial fibrosis regions image; perform three-dimensional reconstruction using a plurality of the two-dimensional images of the myocardial fibrosis area to obtain a first three-dimensional model, and use the first three-dimensional model as the three-dimensional model of the myocardial fibrosis area; combine the first three-dimensional model with the 3D electroanatomical model for registration.
  • the processor further implements the following steps when executing the computer program: performing three-dimensional reconstruction using each of the cardiac chamber grayscale images to obtain a second three-dimensional model, where the second three-dimensional model is a three-dimensional model of the entire cardiac chamber, and The second three-dimensional model is marked with the myocardial fibrosis region image; the second three-dimensional model is registered with the three-dimensional electroanatomical model.
  • the processor further implements the following steps when executing the computer program: extracting, layer by layer, the two-dimensional myocardial fibrosis region in each layer image of the second three-dimensional model in an order from the endocardium to the epicardium image; reconstructing the extracted two-dimensional myocardial fibrosis region images of each layer to obtain a three-dimensional model of the myocardial fibrosis region; registering the three-dimensional model of the myocardial fibrosis region with the three-dimensional electroanatomical model.
  • the processor further implements the following steps when executing the computer program: calculating according to the three-dimensional model of the myocardial fibrosis region to obtain the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • the processor executes the computer program, the following steps are further implemented: generating an ablation strategy for reference according to the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • the three-dimensional electroanatomical model includes a three-dimensional activation conduction map and/or a three-dimensional voltage map; when the processor executes the computer program, the following step is further implemented: matching the three-dimensional image model with the three-dimensional activation conduction map and/or registering the three-dimensional image model with the three-dimensional voltage map.
  • the processor further implements the following steps when executing the computer program: calculating an average registration error, a maximum registration error and a minimum registration error between the three-dimensional image model and the three-dimensional electroanatomical model.
  • a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
  • imaging images which include multiple tomographic images; performing three-dimensional reconstruction according to the multiple tomographic images to obtain the three-dimensional image model, where the three-dimensional image model includes three-dimensional myocardial fibrosis region images; acquiring a three-dimensional electroanatomical model , the three-dimensional electroanatomical model includes a three-dimensional abnormal myocardial tissue image; the three-dimensional image model and the three-dimensional electroanatomical model are registered, and the three-dimensional myocardial fibrosis region image and the three-dimensional abnormal myocardial tissue are determined.
  • the overlapping part of the images is the location of the lesion.
  • the computer program further implements the following steps when executed by the processor: performing denoising processing on each of the tomographic images;
  • the cavity region coordinates extract the grayscale information of the cardiac cavity region image of the corresponding tomographic image, and set the other region images of each tomographic image as the background to obtain the cardiac cavity grayscale image;
  • the grayscale information is counted to identify the myocardial fibrosis area in the grayscale image of the cardiac cavity.
  • image segmentation is performed on each gray-scale image of the cardiac chamber according to the identified myocardial fibrosis region to obtain a plurality of corresponding two-dimensional myocardial fibrosis images. area image; perform three-dimensional reconstruction using a plurality of the two-dimensional myocardial fibrosis area images to obtain a first three-dimensional model, and use the first three-dimensional model as the three-dimensional model of the myocardial fibrosis area;
  • the three-dimensional electroanatomical model was used for registration.
  • the following steps are further implemented: performing three-dimensional reconstruction using each grayscale image of the cardiac chamber to obtain a second three-dimensional model, where the second three-dimensional model is a three-dimensional model of the entire cardiac chamber, And the second three-dimensional model is marked with the image of the myocardial fibrosis region; the second three-dimensional model is registered with the three-dimensional electroanatomical model.
  • the computer program further implements the following steps when executed by the processor: extracting two-dimensional myocardial fibrosis in each layer image of the second three-dimensional model layer by layer in an order from the cardiac endocardium to the epicardium region image; reconstruct the extracted two-dimensional myocardial fibrosis region images of each layer to obtain a three-dimensional model of the myocardial fibrosis region; register the three-dimensional model of the myocardial fibrosis region with the three-dimensional electroanatomical model .
  • the computer program further implements the following steps when executed by the processor: calculating according to the three-dimensional model of the myocardial fibrosis region to obtain the height, width, thickness, volume and surface area of the myocardial fibrosis region.
  • the computer program further implements the following steps when executed by the processor: generating an ablation strategy for reference according to the height, width, thickness, volume, and surface area of the myocardial fibrosis region.
  • the three-dimensional electroanatomical model includes a three-dimensional activation conduction map and/or a three-dimensional voltage map; when the computer program is executed by the processor, the following step is further implemented: performing the three-dimensional image model with the three-dimensional activation conduction map. registering; and/or registering the three-dimensional image model with the three-dimensional voltage map.
  • the computer program when executed by the processor, further implements the steps of: calculating an average registration error, a maximum registration error, and a minimum registration error between the three-dimensional image model and the three-dimensional electroanatomical model.
  • Non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, or optical memory, and the like.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • the RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

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Abstract

一种图像处理方法、装置、计算机设备、存储介质及标测系统，该方法包括：获取影像学图像（S110），所述影像学图像包括多张断层图像；根据所述多张断层图像进行三维重建，得到所述三维影像模型（S120）；所述三维影像模型包括三维心肌纤维化区域图像；获取三维电解剖模型（S130），所述三维电解剖模型包括三维非正常心肌组织图像；由于三维电解剖模型中的非正常心肌组织区域与心肌纤维化存在一定的对应关系，则将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置（S140）。该方法实现了病灶位置的精确定位，从而有效地提高手术成功率。

Description

图像处理方法、装置、计算机设备、存储介质及标测系统
本申请要求于2020年6月30日提交中国专利局，申请号为2020106132423，申请名称为“图像处理方法、装置、计算机设备、存储介质及标测系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及医疗设备技术领域，特别是涉及一种图像处理方法、装置、计算机设备、存储介质及标测系统。
背景技术
在现有医学理论基础上，心律失常往往是由心脏内某一个或多个区域发生异常所引起。导管消融术是目前广泛应用的治疗心律失常的方法，主要是在X光血管造影机的监测下，通过穿刺血管把导管插入心脏，首先检查确定引起心律失常的病灶位置，然后在该病灶位置释放能量如射频、冷冻、超声、激光等，使组织坏死以阻断异常信号传导路径，从而达到治疗目的。
传统技术中，三维标测系统在电生理领域已经有着广泛的应用，且在三维标测系统指导下的消融手术也是公认的治疗心律失常的手段。但是，三维标测系统中的电解剖图并不能完全反映心肌活动的情况，从而导致病灶位置的定位并不准确。
发明内容
基于此，有必要针对上述技术问题，提供一种能够准确定位病灶位置的图像处理方法、装置、计算机设备、存储介质及标测系统。
一种图像处理方法，所述方法包括：
获取影像学图像，所述影像学图像包括多张断层图像；
根据所述多张断层图像进行三维重建，得到所述三维影像模型；其中，所述三维影像模型包括三维心肌纤维化区域图像；
获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；
将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
其中根据所述心肌纤维化区域的三维模型进行计算，得到所述心肌纤维化区域的高度、宽度、厚度、体积、表面积。再根据所述心肌纤维化区域的高度、宽度、厚度、体积、表面积与消融指示参数之间的关系，生成供参考的消融策略，以指导医生进行消融手术。
一种图像处理装置，所述装置包括：
第一获取模块，用于获取影像学图像，所述影像学图像包括多张断层图像；
三维重建模块，用于根据所述多张断层图像进行三维重建，得到所述三维影像模型；其中，所述三维影像模型包括三维心肌纤维化区域图像；
第二获取模块，用于获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；
图像配准模块，用于将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
一种三维标测系统，所述标测系统包括：
标测模块，用于自导管获取三维定位信号并根据所述三维定位信号构建三维心腔模型，并将采集得到的标测点电生理信息叠加在所述三维心腔模型上，生成三维电解剖模型；
图像处理模块，实现上述任一实施例中图像处理方法的步骤；
显示模块，用于显示所述三维电解剖模型、所述三维心肌纤维化区域图像以及所述三维电解剖模型与所述三维影像模型的配准过程。
一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现上述任一实施例中的方法步骤。
一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现上述任一实施例中的方法步骤。
上述图像处理方法、装置、计算机设备、存储介质及标测系统，通过获取影像学图像，所述影像学图像包括含有多张断层图像；根据所述多张断层图像进行三维重建，得到所述三维影像模型；所述三维影像模型包括三维心肌纤维化区域图像；获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；由于三维电解剖模型中的非正常心肌组织区域与心肌纤维化存在一定的对应关系，则将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。实现了病灶位置的精确定位，从而有效地提高手术成功率。通过计算得到了所述心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个，并显示在三维标测系统上，使得术者对病灶区域更加了解，对病灶区域的消融更加彻底，大大降低了复发率。并且根据所述心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个与消融指示参数之间的关系，生成供参考的消融策略，缩短了术者对系统应用的学习周期，从而大大缩短了手术时间，也使得手术更加简单。
附图说明
图1为一个实施例中图像处理方法的流程示意图；
图2为一个实施例中图像处理方法的流程示意图；
图3a为一个实施例中图像处理方法的流程示意图；
图3b为一个实施例中心肌纤维化区域的示意图；
图4为一个实施例中图像处理方法的流程示意图；
图5为一个实施例中图像处理方法的流程示意图；
图6a为一个实施例中图像处理方法的流程示意图；
图6b为一个实施例中图像处理方法的流程示意图；
图6c为一个实施例中图像处理装置的结构框图；
图7为一个实施例中三维标测系统的模块框图；
图8为一个实施例中三维标测系统的结构示意图；
图9为一个实施例中计算机设备的内部结构图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
心律失常是指心脏的正常节律发生异常，而快于正常心率(60-100次/分)的心律失常则是快速心律失常，临床上以心悸、心慌、胸闷、乏力、头晕、目眩等为主要表现，严重者可出现胸痛、呼吸困难、意识丧失，甚至引发脑卒中。导管消融手术是目前广泛应用的治疗心律失常的方法，主要是在X光血管造影机的监测下，通过穿刺血管把导管插入心脏，先检查确定引起心动过速的异常位置，然后在该病灶部位释放能量如射频、冷冻、超声、激光等，使组织坏死以阻断异常信号传导路径，从而达到治疗的目的。
三维标测系统指导下的环肺静脉隔离术是公认的治疗非持续性房颤的手段。虽然近些年消融新技术不断发展，如基于压力导管的射频消融、基于球囊型导管的冷冻消融等，但是由于心律失常发生机制不明，病灶位置不易确定，消融手术的成功率仍然较低，而且术后复发率也较高。研究表明，80％以上的房颤复发是因为肺静脉隔离不彻底，导致肺静脉与左房之间仍存在电信号传导；也有研究认为可能与心肌组织的纤维化有关。
心肌纤维化是由中或重度的冠状动脉粥样硬化性狭窄引起心肌纤维持续性或反复加重的心肌缺血缺氧所产生的结果，伴随心脏体积增大，重量增加，所有心腔扩张，心壁厚度可能正常，但有多灶性白色纤维条索或条块，甚至透壁性瘢痕，或者心内膜增厚并失去正常光泽，有时可见附壁性血栓，临床上表现为心律失常或心力衰竭。临床心肌活检虽然可以鉴别心肌纤维化，但存在有创性和诊断区域的局限性等问题。MRI(Magnetic Resonance Imaging，磁共振成像)、CT(Computed Tomography，电子计算机断层扫描)和PET(正电子发射断层扫描)等影像学检测具有无创的特点，而MRI在心肌纤维化检测中具有定位准确、范围广、精度高及无创性等优势。近年来研究发现，LGE-MRI(晚钆增强磁共振成像)可以用来检查心肌组织的纤维化程度、发生纤维化组织的范围和形状，是判断心肌纤维化相对直接的方法。
传统技术中，一方面，影像学诊断多用于消融手术前消融策略的制定和消融术后效果的评价；另一方面，三维标测系统由于导管贴靠、个体差异如解剖结构变异、脂肪覆盖等 因素的影响，记录的标测图不能完全反映心肌活动情况。因此，本申请创造性地将影像学图像与标测图相结合，实现病灶位置的精确定位以指导消融手术。
在一个实施例中，如图1所示，提供了一种图像处理方法，该方法包括以下步骤：
S110、获取影像学图像。
其中，影像学图像可以是CT图像、PET图像、MRI图像或者LGE-MRI图像中的任一种。影像学图像包括多张断层图像。断层影像可以比较确切地显示心肌组织的纤维化情况，比如纤维化的程度、纤维化组织的范围和形状。具体地，影像学图像可以事先存储在计算机本地，通过图像导入模块将影像学图像加载导入，从而获取影像学图像。
S120、根据多张断层图像进行三维重建，得到三维影像模型。
其中，三维重建可以用于对心肌组织建立适合计算机表示和处理的数学模型的过程。三维重建得到的数学模型是在计算机环境下进行处理、操作和分析心肌组织性质的基础，也是在计算机环境中表达心肌组织或者心腔部分的关键技术。心肌纤维化区域是由中或者重度的冠状动脉粥样硬化性狭窄引起心肌纤维持续性或者反复加重的心肌缺血缺氧所产生的结果。具体地，将影像学图像导入三维标测系统，通过三维标测系统对影像学图像进行三维重建，由于影像学图像中含有心肌纤维化区域，则通过三维重建的三维模型可以将心肌纤维化区域显示出来，得到三维影像模型，且三维影像模型包括三维心肌纤维化区域图像。进一步地，可以使用不同的颜色标识正常区域和纤维化区域，以直观的方式显示心肌纤维化区域的数量、位置和范围。
S130、获取三维电解剖模型。
其中，三维标测是利用导管移动并记录心电信息的标测技术，其原理类似于全球定位系统(GPS)。三维电解剖模型是对心肌或者心腔进行标测后产生的三维图像。通过导管上的位置传感器(比如磁定位传感器或电定位传感器)采集标测点构建心腔几何模型(或者三维心腔解剖模型)，以逐点方式采集多个均匀分布于心腔的标测点。通过心腔内的信号传感器采集心电信号，计算各标测点的激动时间或电压，并用不同的颜色进行标记叠加于心腔几何模型上，生成三维电解剖模型。三维电解剖模型包括三维非正常心肌组织图像。三维非正常心肌组织图像可以是低电压区及/或瘢痕区。具体地，导管紧贴心腔内壁在不同位置进行标测，利用导管位置信息和采集到的心电信号，构建三维心腔几何模型并叠加电生理信息形成三维电解剖模型。
示例性地，可用不同的颜色来区分正常心肌区域和非正常心肌区域，并进一步用例如颜色将非正常心肌区域分为低电压区和瘢痕区，通常心房组织小于0.05-0.1mv和心室组织小于0.5mv定义为瘢痕区。低电压区可以由使用者根据实际情况自行设定。通过三维电解剖模型可了解局部心肌组织的活性，比如，标出瘢痕区的分布，可以协助分析心律失常形成和维持机制。
S140、将三维影像模型与三维电解剖模型进行配准，并确定心肌纤维化区域图像与非正常心肌组织图像的重叠部分为病灶位置。
其中，影像学图像通常作为术前诊断，可以初步确定心肌纤维化位置和范围，虽然三维电解剖模型中的非正常心肌组织区域与心肌纤维化有一定程度的联系，但并不是所有纤维化区域都是异常的且需要消融的。因此可以将三维影像模型与三维电解剖模型进行融合，更准确地定位病灶位置以实施有效消融。具体地，将三维影像模型进行显示，可对其进行平移、旋转、缩放或者其他常规视角显示，将三维影像模型与三维电解剖模型进行配准，三维影像模型上的三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。
上述图像处理方法中，通过获取影像学图像，影像学图像包括多张断层图像；根据多张断层图像进行三维重建，得到三维影像模型，所述三维影像模型包括三维心肌纤维化区域图像；获取三维电解剖模型，三维电解剖模型包括三维非正常心肌组织图像；由于三维电解剖模型中的非正常心肌组织区域与心肌纤维化存在一定的对应关系，则将三维影像模型与三维电解剖模型进行配准，并确定三维心肌纤维化区域图像与三维非正常心肌组织图像的重叠部分为病灶位置。实现了病灶位置的精确定位，可有效地提高手术成功率，降低复发率，缩短手术时间，也使得手术更加简单，缩短学习周期。
在一个实施例中，断层图像包括二维心肌纤维化区域图像。如图2所示，在根据多张断层图像进行三维重建，得到三维影像模型之前，该方法还包括以下步骤：
S210、对每张断层图像进行去噪处理。
其中，去噪处理是指减少断层图像中噪声的过程。具体地，一方面除心腔区域之外，断层图像还包括躯干、肋骨等其他区域的图像，将断层图像中的其他区域图像视为噪声去除；另一方面，断层图像还存在一些像素不高或者混杂不清晰的区域，则基于一些滤波原理对断层图像进行去噪处理。
S220、基于数学形态学，在每张断层图像中获取心腔区域坐标，根据心腔区域坐标提取对应的断层图像中的心腔区域图像的灰度信息，并将每张断层图像中的其他区域图像设置为背景，得到对应的心腔灰度图像。
其中，数学形态学的基本思想是用具有一定形态的结构元素去量度和提取图像中的对应形状以达到对图像分析和识别的目的，可简化图像数据，保持它们基本的形状特性，并除去不相干的结构。数学形态学由一组形态学的代数运算子组成，基本运算有膨胀(或扩张)、腐蚀(或侵蚀)、开启和闭合等。心腔灰度图像包含心肌组织区域的灰度信息，而心腔灰度图像中除心脏外的其他区域设置为同一灰度值或者同一颜色，即将其他区域设为背景。
具体地，获取心腔区域在影像学图像中的位置坐标，基于数学形态学的相关操作，根据心腔区域坐标对影像学图像的灰度分布特征进行提取，得到心腔区域图像的灰度信息。为了仅仅保留心腔区域图像，将每张断层图像中的其他区域图像设置为背景，从而得到心腔灰度图像。
S230、对每张心腔灰度图像的灰度信息进行统计，识别心腔灰度图像中的心肌纤维化 区域。
其中，对影像学图像进行心脏区域的特征提取，得到心腔灰度图像，需要进一步地从心腔灰度图像中区分出纤维化区域和非纤维化区域。具体地，对图像的灰度分布信息进行统计，其中灰度值高的区域代表图像中的心肌纤维化区域，灰度值低的区域代表图像中的心肌非纤维化区域，然后进行基于不同滤波原理的去噪处理，识别出心腔灰度图像中的心肌纤维化区域。
本实施例中，通过对每张断层图像进行去噪处理、形态学处理和图像灰度信息统计等操作，识别心腔灰度图像中的心肌纤维化区域，为后面的图像分割以及三维影像模型的重建打下基础，而且准确地识别心肌纤维化区域，有利于建立与实际情况更加贴合的三维模型，进一步地提升病灶位置定位的准确性。
在一个实施例中，如图3a所示，根据多张断层图像进行三维重建，得到三维影像模型的步骤包括：S310、根据识别的心肌纤维化区域对每张心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像。
以及S320、利用多张二维心肌纤维化区域图像进行三维重建，得到第一三维模型，将所述第一三维模型作为心肌纤维化区域的三维模型。
将三维影像模型与三维电解剖模型进行配准的步骤包括：S330、将第一三维模型与三维电解剖模型进行配准。
其中，图像分割是将预处理后的图像进行特征提取，具体地，可以设计以纤维化组织为特征的组织空间分布复杂性的度量如密度、聚类等的分割算法，确定在预定的范围内是否有一定程度的纤维化，区分纤维化区域和非纤维化区域，产生基于纤维化组织特征的图像，颜色可代表纤维化程度。图像分割算法可以是LevelSet分割、Graph Cuts分割、基于形态学变换的分水岭分割、区域增长分割等。具体地，通过图像分割模块对每张心腔灰度图像进行分割，得到对应的二维心肌纤维化区域图像。将图像分割后得到的二维心肌纤维化区域图像进行三维重构，将多张二维心肌纤维化区域图像重建为心肌纤维化区域的三维模型，该三维模型可以直观显示心肌纤维组织的三维结构。将该三维模型与三维电解剖模型进行配准，该三维模型上的三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。进一步地，如图3b所示，图中所示的斑驳区域为纤维化组织，图中所示的灰度均匀区域为正常组织。可以理解的是，可以利用不同的颜色标识正常组织和纤维化组织，直观显示心肌纤维化区域的数量、位置和范围。
在一个实施例中，如图4所示，根据多张断层图像进行三维重建，得到三维影像模型的步骤包括：S410、利用每张心腔灰度图像进行三维重建，得到第二三维模型，且第二三维模型上标示有三维心肌纤维化区域图像。
将三维影像模型与三维电解剖模型进行配准的步骤包括：S420、将第二三维模型与三维电解剖模型进行配准。
其中，第二三维模型为整个心腔的三维模型。具体地，对人体胸腔部分进行扫描得到影像学图像，影像学图像包括多张断层图像，对断层图像进行去噪处理、形态学处理和图像灰度分布特征提取等操作得到心腔灰度图像。首先，利用处理后得到的心腔灰度图像进行三维重建，得到第二三维模型，由于已经从心腔灰度图像中识别出心肌纤维化区域，则可以在第二三维模型上标示出心肌纤维化区域图像。将构建的第二三维模型与三维电解剖模型进行配准，第二三维模型上的三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。
进一步地，为了判断三维影像模型与三维电解剖模型之间的匹配度是否合适，还可以计算三维影像模型与三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差，以对每个区域的匹配程度进行度量。
在一个实施例中，如图5所示，该方法还包括以下步骤：
S510、按照心脏内膜至外膜的顺序，逐层提取第二三维模型的每层图像中的二维心肌纤维化区域图像。
S520、将提取到的各层二维心肌纤维化区域图像重建得到心肌纤维化区域的三维模型。
S530、将所述心肌纤维化区域的三维模型与所述三维电解剖模型进行配准。
具体地，在构建第二三维模型后，可以从第二三维模型中分割出心肌纤维组织的三维结构。具体地，按照心脏内膜至外膜的顺序逐层显示，从而清楚地了解各层心肌组织的纤维化程度。在此基础上，一方面可以对每层图像中的纤维化区域进行单独地分割提取；另一方面也可以选取特定的纤维化范围进行单独提取，比如设置种子点利用区域增长算法，将所有层的纤维化区域分别提取出来，然后对其进行三维重建得到心肌纤维化区域的三维模型，可以直观显示心肌纤维组织的三维结构。最后，将心肌纤维化区域的三维模型与三维电解剖模型进行配准，则三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。
在一个实施例中，该方法还包括以下步骤：根据心肌纤维化区域的三维模型进行计算，得到心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个。进一步地，根据心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个，生成供参考的消融策略。
具体地，在已知各层心肌组织的纤维化程度基础上，对每层图像中的纤维化区域进行单独提取，利用各层的纤维化区域图像进行三维重建，得到心肌纤维化区域的三维模型，对心肌纤维化区域的三维模型进行计算，得到心肌纤维化区域的高度、宽度、厚度、体积、表面积等参数，这些参数可以更加直观的向术者展示纤维化程度。在知道心肌纤维化区域的三维模型的这些参数后，为了进一步指导手术并提升手术效果，根据心肌纤维化区域的高度、宽度、厚度、体积、表面积确定消融指示参数，并生成消融策略以供术者参考。消融策略包括消融积分值、消融直径、消融深度、压力值、功率、温度、阻抗、时间等参数 的设置。本实施例中，通过消融策略为术者提供更合理的参考。
在一个实施例中，三维电解剖模型包括三维激动传导图和/或三维电压图；将三维影像模型与三维电解剖模型进行配准，包括：将三维影像模型与三维激动传导图进行配准；和/或，将三维影像模型与三维电压图进行配准。
其中，三维激动传导图和三维电压图是进行三维心脏电生理标测时选择的两种不同的呈现方式，三维激动传导图表明心电信号传导的路径，三维电压图表明心电信号的电压差。三维影像模型可以是心肌纤维化区域的三维模型，将该三维模型与三维电解剖模型进行配准，该三维模型上的三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。三维影像模型也可以是标示有心肌纤维化区域图像的心腔三维模型(即整个心腔的三维模型)。将构建的心腔三维模型与三维电解剖模型进行配准，心腔三维模型上的三维心肌纤维化区域图像与三维电解剖模型中的三维非正常心肌组织图像存在重叠部分，则可以将重叠部分确定为病灶位置。
本实施例中，由于瘢痕区、低电压区、心肌纤维化区域分别是心肌异常区域的不同表征方式，且三者是从不同的角度展示心肌异常部位，将三者进行结合可能会更有效地且精确地确认具体的病灶部位。
在一个实施例中，本申请提供一种图像处理方法，如图6a所示，该方法包括以下步骤：
S602a、获取影像学图像。
其中，影像学图像包括多张断层图像，断层图像包括二维心肌纤维化区域图像。具体地，影像学图像可以存储于图像文件管理模块，且图像文件管理模块主要负责管理文件、加载文件以及获取文件信息，并存储需要预处理或其他操作的中间文件。通过图像导入模块选取图像文件管理模块中的影像学图像，将其加载导入以对影像学图像进行一系列的处理操作。
S604a、对每张断层图像进行去噪处理。
S606a、基于数学形态学，在每张所述断层图像中获取心腔区域坐标，根据心腔区域坐标提取对应的断层图像中的心腔区域图像的灰度信息，并将每张断层图像中的其他区域图像设置为背景，得到心腔灰度图像。
S608a、对每张心腔灰度图像的灰度信息进行统计，识别心腔灰度图像中的心肌纤维化区域。
S610a、根据识别的心肌纤维化区域对每张心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像。
S612a、利用多张二维心肌纤维化区域图像进行三维重建，得到心肌纤维化区域的三维模型。
其中，心肌纤维化区域的三维模型包括三维心肌纤维化区域图像。
S614a、获取三维电解剖模型。
其中，三维电解剖模型包括三维非正常心肌组织图像。
S616a、将心肌纤维化区域的三维模型与三维电解剖模型进行配准，并确定三维心肌纤维化区域图像与三维非正常心肌组织图像的重叠部分为病灶位置。
在一个实施例中，本申请提供一种图像处理方法，如图6b所示，该方法包括以下步骤：
S602b、获取影像学图像。
其中，影像学图像包括多张断层图像，断层图像包括二维心肌纤维化区域图像。
S604b、对每张断层图像进行去噪处理。
S606b、基于数学形态学，根据心腔区域坐标提取对应的断层图像中的心腔区域图像的灰度信息，并将每张断层图像中的其他区域图像设置为背景，得到心腔灰度图像。
S608b、对每张心腔灰度图像的灰度信息进行统计，识别心腔灰度图像中的心肌纤维化区域。
S610b、利用每张心腔灰度图像进行三维重建，得到第二三维模型，且第二三维模型上标示有三维心肌纤维化区域图像。
S612b、按照心脏内膜至外膜的顺序，逐层提取第二三维模型的每层图像中的二维心肌纤维化区域图像。
S614b、将提取到的各层二维心肌纤维化区域图像重建得到心肌纤维化区域的三维模型。
S616b、获取三维电解剖模型。
其中，三维电解剖模型包括三维非正常心肌组织图像。三维电解剖模型包括三维激动传导图和/或三维电压图。
S618b、将心肌纤维化区域的三维模型与三维电解剖模型进行配准，并确定三维心肌纤维化区域图像与三维非正常心肌组织图像的重叠部分为病灶位置。
S620b、根据心肌纤维化区域的三维模型进行计算，得到心肌纤维化区域的高度、宽度、厚度、体积、表面积。
S622b、根据心肌纤维化区域的高度、宽度、厚度、体积、表面积，生成供参考的消融策略。
S624b、计算三维影像模型与三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差并显示。
应该理解的是，虽然上述各实施例的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，上述各实施例中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮 流或者交替地执行。
在一个实施例中，如图6c所示，提供了一种图像处理装置600，包括：第一获取模块610、三维重建模块620、第二获取模块630和图像配准模块640，其中：
第一获取模块610用于获取影像学图像，所述影像学图像包括多张断层图像；
三维重建模块620用于根据所述多张断层图像进行三维重建，得到所述三维影像模型；其中，所述三维影像模型包括三维心肌纤维化区域图像；
第二获取模块630用于获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；
图像配准模块640用于将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
在一个实施例中，断层图像包括心肌纤维化区域。该装置还包括：
去噪处理模块，用于对每张所述断层图像进行去噪处理；
第一提取模块，用于基于数学形态学，在每张所述断层图像获取心腔区域坐标，根据心腔区域坐标提取对应的所述断层图像的心腔区域图像的灰度信息，并将每张所述断层图像的其他区域图像设置为背景，得到心腔灰度图像；
纤维化识别模块，用于对每张所述心腔图像的灰度信息进行统计，识别所述心腔灰度图像中的心肌纤维化区域。
在一个实施例中，三维重建模块620还用于根据识别的心肌纤维化区域对每张所述心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像；利用多张所述二维心肌纤维化区域图像进行三维重建，得到第一三维模型，将所述第一三维模型作为心肌纤维化区域的三维模型；
图像配准模块640还用于将所述第一三维模型与所述三维电解剖模型进行配准。
在一个实施例中，三维重建模块620还用于利用每张所述心腔灰度图像进行三维重建，得到第二三维模型；所述第二三维模型为整个心腔的三维模型且所述第二三维模型上标示有所述三维心肌纤维化区域；
图像配准模块640还用于将所述第二三维模型与所述三维电解剖模型进行配准。
在一个实施例中，该装置还包括：第二获取模块用于按照所述心脏内膜至外膜的顺序，逐层提取所述第二三维模型的每层图像中的二维心肌纤维化区域图像；以及，三维模型重建模块用于将提取到的各层所述二维心肌纤维化区域图像重建得到所述心肌纤维化区域的三维模型；
图像配准模块640还用于将所述心肌纤维化区域的三维模型与所述三维电解剖模型进行配准。
在一个实施例中，该装置还包括：第一计算模块，用于根据所述心肌纤维化区域的三维模型进行计算，得到所述心肌纤维化区域的高度、宽度、厚度、体积、表面积。
在一个实施例中，该装置还包括：消融策略生成模块，用于根据所述心肌纤维化区域 的高度、宽度、厚度、体积、表面积，生成供参考的消融策略。
在一个实施例中，所述三维电解剖模型包括三维激动传导图和/或三维电压图；图像配准模块640，还用于将所述三维影像模型与所述三维激动传导图进行配准；和/或，将所述三维影像模型与所述三维电压图进行配准。
在一个实施例中，该装置还包括：第二计算模块，用于计算所述三维影像模型与所述三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差。
在一个实施例中，所述三维激动传导图反映心电信号传导路径；所述三维电压图表明心电信号的电压差；其中，所述三维电压图标识出有正常心肌组织区、低电压区和瘢痕区；所述三维非正常心肌组织图像包括所述低电压区的图像及/或所述瘢痕区的图像。
关于图像处理装置的具体限定可以参见上文中对于图像处理方法的限定，在此不再赘述。上述图像处理装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，本申请提供一种三维标测系统，如图7所示，该标测系统包括：
标测模块710，用于自导管获取三维定位信号并根据所述三维定位信号构建三维心腔模型，并将采集得到的标测点电生理信息叠加在所述三维心腔模型上，生成三维电解剖模型；
图像处理模块720，用于实现上述实施例中任一项所述的图像处理方法的步骤；
显示模块730，用于显示所述三维电解剖模型、所述三维心肌纤维化区域图像以及所述三维电解剖模型与所述三维影像模型的配准过程。
示例性地，三维标测系统包括硬件设备和软件应用程序，其中：硬件设备包括带有定位传感器的介入导管、定位处理单元、患者接口单元、射频仪、工作站及显示器等。定位传感器(磁场定位或电场定位)用于发射和接收定位信号；如图8所示，当定位传感器为磁定位传感器时，三维标测系统还包括磁场发生器；定位处理单元用于控制磁场或电场发生器工作并对定位信息进行处理分析；患者接口单元用于分析处理心电信号等；计算机工作站配置软件应用程序，用于汇总所有的定位信息和心电信息，通过软件将其反映在显示器上以帮助术者更好地进行消融手术。
进一步地，软件应用程序包括系统状态、患者信息登录、病例数据管理、图像处理和心脏标测。其中，系统状态可实时监测硬件设备的连接和工作情况；患者信息登录是记录患者相关信息如姓名、性别、ID号以及初步医学诊断信息等；病例数据管理是管理所有的病例数据，可用于病例回顾；图像处理模块包括图像文件管理模块、图像分割模块、三维重建模块、图像编辑模块和图像配准模块等，心脏标测模块用于导管实时显示、心腔模型构建、心电信号实时显示和相关事件记录、配准后图像的显示、消融参数和消融状态显示等。在一实施例中，标测模块可以是数据处理器，例如计算机CPU和GPU；图像处理模块可以是图像信号处理器，例如是另一个计算机CPU和GPU；显示模块可以是显示器；数据 处理器和图像信号处理器可以是如上所述的两个独立的处理器，在其他实施例中，标测模块和图像处理模块也可以是同一个处理器，例如是同一个CPU。
在一个实施例中，提供了一种计算机设备，该计算机设备可以是终端，其内部结构图可以如图9所示。该计算机设备包括通过系统总线连接的处理器、内存储器、通信接口、显示屏和输入装置。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统和计算机程序。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的通信接口用于与外部的终端进行有线或无线方式的通信，无线方式可通过WIFI、运营商网络、NFC(近场通信)或其他技术实现。该计算机程序被处理器执行时以实现一种图像处理方法。该计算机设备的显示屏可以是液晶显示屏或者电子墨水显示屏，该计算机设备的输入装置可以是显示屏上覆盖的触摸层，也可以是计算机设备外壳上设置的按键、轨迹球或触控板，还可以是外接的键盘、触控板或鼠标等。
本领域技术人员可以理解，图9中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一个实施例中，提供了一种计算机设备，包括存储器和处理器，存储器中存储有计算机程序，该处理器执行计算机程序时实现以下步骤：
获取影像学图像，所述影像学图像包括多张断层图像；根据所述多张断层图像进行三维重建，得到所述三维影像模型，三维影像模型包括三维心肌纤维化区域图像；获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：对每张所述断层图像进行去噪处理；基于数学形态学，在每张所述断层图像获取心腔区域坐标，根据心腔区域坐标提取对应的断层图像的心腔区域图像的灰度信息，并将每张所述断层图像的其他区域设置为背景，得到心腔灰度图像；对每张所述心腔图像的灰度信息进行统计，识别所述心腔灰度图像中的心肌纤维化区域。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：根据识别的心肌纤维化区域对每张所述心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像；利用多张所述二维心肌纤维化区域图像进行三维重建，得到第一三维模型，将所述第一三维模型作为心肌纤维化区域的三维模型；将所述第一三维模型与所述三维电解剖模型进行配准。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：利用每张所述心腔灰度图像进行三维重建，得到第二三维模型，第二三维模型为整个心腔的三维模型，且所述第二三维模型上标示有所述心肌纤维化区域图像；将所述第二三维模型与所述三维电解剖模 型进行配准。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：按照所述心脏内膜至外膜的顺序，逐层提取所述第二三维模型的每层图像中的二维心肌纤维化区域图像；将提取到的各层所述二维心肌纤维化区域图像重建得到所述心肌纤维化区域的三维模型；将所述心肌纤维化区域的三维模型与所述三维电解剖模型进行配准。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：根据所述心肌纤维化区域的三维模型进行计算，得到所述心肌纤维化区域的高度、宽度、厚度、体积、表面积。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：根据所述心肌纤维化区域的高度、宽度、厚度、体积、表面积，生成供参考的消融策略。
在一个实施例中，所述三维电解剖模型包括三维激动传导图和/或三维电压图；处理器执行计算机程序时还实现以下步骤：将所述三维影像模型与所述三维激动传导图进行配准；和/或将所述三维影像模型与所述三维电压图进行配准。
在一个实施例中，处理器执行计算机程序时还实现以下步骤：计算所述三维影像模型与所述三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差。
在一个实施例中，提供了一种计算机可读存储介质，其上存储有计算机程序，计算机程序被处理器执行时实现以下步骤：
获取影像学图像，所述影像学图像包括多张断层图像；根据所述多张断层图像进行三维重建，得到所述三维影像模型，三维影像模型包括三维心肌纤维化区域图像；获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：对每张所述断层图像进行去噪处理；基于数学形态学，在每张所述断层图像获取心腔区域坐标，根据心腔区域坐标提取对应的断层图像的心腔区域图像的灰度信息，并将每张所述断层图像的其他区域图像设置为背景，得到心腔灰度图像；对所述每张心腔图像的灰度信息进行统计，识别所述心腔灰度图像中的心肌纤维化区域。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：根据识别的心肌纤维化区域对每张所述心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像；利用多张所述二维心肌纤维化区域图像进行三维重建，得到第一三维模型，将所述第一三维模型作为心肌纤维化区域的三维模型；将所述第一三维模型与所述三维电解剖模型进行配准。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：利用每张所述心腔灰度图像进行三维重建，得到第二三维模型，第二三维模型为整个心腔的三维模型，且所述第二三维模型上标示有所述心肌纤维化区域图像；将所述第二三维模型与所述三维电解剖模型进行配准。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：按照所述心脏内膜至外膜的顺序，逐层提取所述第二三维模型的每层图像中的二维心肌纤维化区域图像；将提取到的各层所述二维心肌纤维化区域图像重建得到所述心肌纤维化区域的三维模型；将所述心肌纤维化区域的三维模型与所述三维电解剖模型进行配准。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：根据所述心肌纤维化区域的三维模型进行计算，得到所述心肌纤维化区域的高度、宽度、厚度、体积、表面积。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：根据所述心肌纤维化区域的高度、宽度、厚度、体积、表面积，生成供参考的消融策略。
在一个实施例中，所述三维电解剖模型包括三维激动传导图和/或三维电压图；计算机程序被处理器执行时还实现以下步骤：将所述三维影像模型与所述三维激动传导图进行配准；和/或将所述三维影像模型与所述三维电压图进行配准。
在一个实施例中，计算机程序被处理器执行时还实现以下步骤：计算所述三维影像模型与所述三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一种。非易失性存储器可包括只读存储器(Read-Only Memory，ROM)、磁带、软盘、闪存或光存储器等。易失性存储器可包括随机存取存储器(Random Access Memory，RAM)或外部高速缓冲存储器。作为说明而非局限，RAM可以是多种形式，比如静态随机存取存储器(Static Random Access Memory，SRAM)或动态随机存取存储器(Dynamic Random Access Memory，DRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (17)

  1. 一种图像处理方法，包括：
    获取影像学图像，所述影像学图像包括多张断层图像；
    根据所述多张断层图像进行三维重建，得到三维影像模型；其中，所述三维影像模型包括三维心肌纤维化区域图像；
    获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；
    将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
  2. 根据权利要求1所述的方法，其中，所述断层图像包括心肌纤维化区域；
    在所述根据所述多张断层图像进行三维重建，得到三维影像模型之前，所述方法还包括：
    对每张所述断层图像进行去噪处理；
    基于数学形态学，在每张所述断层图像中获取心腔区域坐标，根据所述心腔区域坐标提取对应的所述断层图像中的心腔区域图像的灰度信息，并将每张所述断层图像中的其他区域图像设置为背景，得到对应的心腔灰度图像；
    对每张所述心腔灰度图像的灰度信息进行统计，识别所述心腔灰度图像中的心肌纤维化区域。
  3. 根据权利要求2所述的方法，其中，
    所述根据所述多张断层图像进行三维重建，得到三维影像模型的步骤，包括：根据识别的所述心肌纤维化区域对每张所述心腔灰度图像分别进行图像分割，得到多张对应的二维心肌纤维化区域图像；利用多张所述二维心肌纤维化区域图像进行三维重建，得到第一三维模型，所述第一三维模型为心肌纤维化区域的三维模型。
  4. 根据权利要求3所述的方法，其中，所述将所述三维影像模型与所述三维电解剖模型进行配准的步骤，包括将所述第一三维模型与所述三维电解剖模型进行配准。
  5. 根据权利要求2所述的方法，其中，所述根据所述多张断层图像进行三维重建，得到所述三维影像模型的步骤，包括：
    利用每张所述心腔灰度图像进行三维重建，得到第二三维模型；所述第二三维模型为整个心腔的三维模型，且所述第二三维模型上标示有所述三维心肌纤维化区域图像。
  6. 根据权利要求5所述的方法，其中，所述将所述三维影像模型与所述三维电解剖模型进行配准的步骤，包括：
    将所述第二三维模型与所述三维电解剖模型进行配准。
  7. 根据权利要求5或6所述的方法，还包括：
    按照所述心脏内膜至外膜的顺序，逐层提取所述第二三维模型的每层图像中的二维心肌纤维化区域图像；
    将提取到的各层所述二维心肌纤维化区域图像重建得到所述心肌纤维化区域的三维 模型；
    将所述心肌纤维化区域的三维模型与所述三维电解剖模型进行配准。
  8. 根据权利要求3或5所述的方法，还包括：
    根据所述心肌纤维化区域的三维模型进行计算，得到所述心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个；
    根据所述心肌纤维化区域的高度、宽度、厚度、体积、表面积中的一个或多个，生成供参考的消融策略。
  9. 根据权利要求1至6中任意一项所述的方法，其中，所述三维电解剖模型包括三维激动传导图和/或三维电压图；所述将所述三维影像模型与所述三维电解剖模型进行配准的步骤，包括：
    将所述三维影像模型与所述三维激动传导图进行配准；和/或
    将所述三维影像模型与所述三维电压图进行配准。
  10. 根据权利要求9所述的方法，其中，所述三维激动传导图反映心电信号传导路径；所述三维电压图表明心电信号的电压差；
    其中，所述三维电压图标识有正常心肌组织区、低电压区和瘢痕区；所述三维非正常心肌组织图像包括所述低电压区的图像及/或所述瘢痕区的图像。
  11. 根据权利要求10所述的方法，还包括：
    计算所述三维影像模型与所述三维电解剖模型之间的平均配准误差、最大配准误差以及最小配准误差。
  12. 根据权利要求1所述的方法，其中，根据所述多张断层图像进行三维重建，得到三维影像模型包括：使用不同的颜色标识正常区域和纤维化区域。
  13. 根据权利要求8所述的方法，其中，所述消融策略包括消融积分值、消融直径、消融深度、压力值、功率、温度、阻抗和/或时间的设置。
  14. 一种图像处理装置，包括：
    第一获取模块，用于获取影像学图像，所述影像学图像包括多张断层图像；
    三维重建模块，用于根据所述多张断层图像进行三维重建，得到所述三维影像模型；其中，所述三维影像模型包括三维心肌纤维化区域图像；
    第二获取模块，用于获取三维电解剖模型，所述三维电解剖模型包括三维非正常心肌组织图像；
    图像配准模块，用于将所述三维影像模型与所述三维电解剖模型进行配准，并确定所述三维心肌纤维化区域图像与所述三维非正常心肌组织图像的重叠部分为病灶位置。
  15. 一种三维标测系统，包括：
    标测模块，用于自导管获取三维定位信号并根据所述三维定位信号构建三维心腔模型，并将采集得到的标测点电生理信息叠加在所述三维心腔模型上，生成三维电解剖模型；
    图像处理模块，用于实现权利要求1至13中任一项所述的图像处理方法的步骤；
    显示模块，用于显示所述三维电解剖模型、所述三维心肌纤维化区域图像以及所述三维电解剖模型与所述三维影像模型的配准过程。
  16. 一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，其中，所述处理器执行所述计算机程序时实现权利要求1至13中任一项所述的方法的步骤。
  17. 一种计算机可读存储介质，其上存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1至13中任一项所述的方法的步骤。
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