Standard uptake value normalization method and system

Abstract

The embodiment of the invention provides a standard uptake value normalization method and system, and the method is executed by a processor, and comprises the steps: determining a normalization factor based on a motif image and a reference standard; and performing normalization processing on the to-be-processed image by using the normalization factor, and determining a normalized standard uptake value.

Description

Technical Field

[0001] The present invention relates to the field of nuclear medicine imaging technology, and in particular to a method and system for normalizing a standard uptake value. Background Art

[0002] The standardized uptake value (SUV) is a semi-quantitative indicator commonly used in tumor image analysis by positron emission tomography. It specifically refers to the ratio of the radioactivity concentration of the imaging agent taken up by local tissues to the average concentration of the systemic injected activity. It can be used to differentiate benign and malignant tumors, evaluate the therapeutic effect, and predict prognosis. Although SUV is currently widely used in clinical practice as a quantitative indicator for image analysis, the patient's physiological factors, examination procedures, equipment quality control, image acquisition and reconstruction methods, etc. will affect the accuracy and repeatability of SUV, so SUV needs to be normalized. However, when SUV is normalized using different EARL (EANM Research Ltd) standards (including EARL V1.0 standard and EARL V2.0 standard) developed by the European Association of Nuclear Medicine (EANM), the recovery coefficient (RC) ranges in EARL V1.0 and EARL V2.0 are missing to varying degrees, so it is impossible to normalize SUV at the same time. mean , SUV max , SUV peak The normalization processing of SUV leads to the reduction of its application value in efficacy evaluation and inter-group comparison.

[0003] Therefore, it is necessary to provide a method and system for normalizing the standard uptake value for SUV in the absence of the RC range of the EARL standard. mean , SUV max , SUV peak Normalization processing is performed to make SUV comparable across devices, patients, and time. Summary of the invention

[0004] One or more embodiments of the present specification provide a method for normalizing a standard uptake value, which is executed by a processor and includes: determining a normalization factor based on a phantom image and a reference standard; and performing normalization processing on the image to be processed using the normalization factor to determine a normalized standard uptake value.

[0005] In some embodiments, the reference standard includes EARL V1.0; the determining of the normalization factor based on the phantom image and the reference standard includes: based on the standard parameters in EARL V1.0, iteratively performing the normalization process on the phantom image to determine a first factor and a second factor; the standard parameters include a maximum recovery coefficient and an average recovery coefficient; based on the first factor and the second factor, determining a third factor by a first preset method.

[0006] In some embodiments, the first preset method includes determining the third factor based on a maximum value of the first factor and the second factor.

[0007] In some embodiments, the reference standard includes EARL V2.0; the determining of the normalization factor based on the model image and the reference standard includes: based on the upper and lower bounds of the standard parameters in the EARL V2.0, calculating the expected value of the standard parameter by a second preset method; the standard parameter includes at least one of the highest restoration coefficient, the average restoration coefficient and the average value of the highest restoration coefficient region; based on the upper and lower bounds of the standard parameters and the expected value, iteratively performing the normalization processing on the model image to determine at least one of the first factor, the second factor and the third factor.

[0008] In some embodiments, the second preset method includes determining the expected value based on an average of the upper bound and the lower bound of the standard parameter.

[0009] One or more embodiments of the present specification provide a standard uptake value normalization system, the system comprising: a first determination module for determining a normalization factor based on a model image and a reference standard; a second determination module for normalizing a processed image using the normalization factor to determine a normalized standard uptake value.

[0010] In some embodiments, the reference standard includes EARL V1.0; the first determination module is further used to: based on the standard parameters in the EARL V1.0, iteratively perform the normalization process on the model image to determine the first factor and the second factor; the standard parameters include the highest recovery coefficient and the average recovery coefficient; based on the first factor and the second factor, determine the third factor by a first preset method.

[0011] In some embodiments, the first preset method includes determining the third factor based on a maximum value of the first factor and the second factor.

[0012] In some embodiments, the reference standard includes EARL V2.0; the first determination module is further used to: calculate the expected value of the standard parameter based on the upper and lower bounds of the standard parameter in the EARL V2.0 by a second preset method; the standard parameter includes at least one of the highest restoration coefficient, the average restoration coefficient and the average value of the highest restoration coefficient area; based on the upper and lower bounds of the standard parameter and the expected value, iteratively perform the normalization processing on the model image to determine at least one of the first factor, the second factor and the third factor.

[0013] In some embodiments, the second preset method includes determining the expected value based on an average of the upper bound and the lower bound of the standard parameter. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0015] Figure 1 is an exemplary module diagram of a standard uptake value normalization system according to some embodiments of the present specification;

[0016] Figure 2 is an exemplary flow chart of a method for normalizing a standard uptake value according to some embodiments of the present specification;

[0017] Figure 3A According to the EARL V1.0 in some embodiments of this specification, mean Schematic diagram of the standard;

[0018] Figure 3B According to the EARL V1.0 in some embodiments of this specification, max Schematic diagram of the standard;

[0019] Figure 4 According to some embodiments of this specification, EARL V2.0 is described in relation to RC mean ,RC max and RC peak Schematic diagram of the standard;

[0020] Figure 5 is an exemplary flow chart of determining a normalization factor based on EARL V1.0 according to some embodiments of this specification;

[0021] Figure 6 is an exemplary flow chart of determining a normalization factor based on EARL V2.0 according to some embodiments of this specification. DETAILED DESCRIPTION

[0022] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0023] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0024] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0025] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0026] When using the EARL standard to normalize SUVs, it is impossible to normalize SUVs at the same time because both EARL V1.0 and EARL V2.0 have different degrees of missing RC ranges. mean , SUV max , SUV peak The normalization processing of SUV leads to the reduction of its application value in efficacy evaluation and inter-group comparison.

[0027] Some embodiments of the present specification provide a method and system for normalizing a standard uptake value. The method can determine a normalization factor based on a phantom image and a reference standard; use the normalization factor to normalize the image to be processed to determine a normalized standard uptake value, thereby achieving SUV normalization of the image to be processed obtained by different scanning devices for different patients at different times when the RC range in the EARL standard is partially missing. mean , SUVmax , SUV peak The normalization processing makes SUV comparable across devices, patients, and time, thus enabling the differentiation of benign and malignant tumors and the evaluation of therapeutic efficacy.

[0028] In some embodiments, the aforementioned standard uptake value normalization method can be performed by a processor. The processor can be set in a medical device or in a separate server. The processor can be used to process data and / or information obtained from a medical device (such as a scanning device). The processor can execute program instructions based on these data, information and / or processing results to perform one or more functions described in this specification. For example, the processor can determine a normalization factor based on a phantom image and a reference standard; use the normalization factor to normalize the image to be processed, and determine a normalized standard uptake value.

[0029] Figure 1 1 is an exemplary module diagram of a standard uptake value normalization system according to some embodiments of the present specification. In some embodiments, the standard uptake value normalization system 100 may include a first determination module 110 and a second determination module 120.

[0030] The first determination module 110 may be configured to determine a normalization factor based on a phantom image and a reference standard.

[0031] In some embodiments, the first determination module 110 can be further used to iteratively normalize the model image based on the standard parameters in EARL V1.0 to determine the first factor and the second factor; the standard parameters include the maximum recovery coefficient and the average recovery coefficient; based on the first factor and the second factor, determine the third factor by a first preset method.

[0032] In some embodiments, the first determination module 110 can be further used to calculate the expected value of the standard parameter based on the upper and lower bounds of the standard parameter in EARL V2.0 through a second preset method; the standard parameter includes at least one of the highest restoration coefficient, the average restoration coefficient and the average value of the highest restoration coefficient area; based on the upper and lower bounds and expected values ​​of the standard parameter, the model image is iteratively normalized to determine at least one of the first factor, the second factor and the third factor.

[0033] The second determination module 120 may be configured to perform normalization processing on the image to be processed using the normalization factor to determine a normalized standard uptake value.

[0034] For more information on determining normalization factors based on phantom images and reference standards and determining normalized standard uptake values, see Figure 2For more information on determining the first, second, and third factors based on the standard parameters in EARL V1.0, see Figure 5 For more information on determining the first, second, and third factors based on the standard parameters in EARL V2.0, see Figure 6 and its related description.

[0035] It should be noted that the above description of the standard uptake value normalization system 100 and its modules is only for convenience of description and does not limit the present specification to the scope of the embodiments. It is understandable that, after understanding the principle of the system, those skilled in the art may arbitrarily combine the modules or form a subsystem to connect with other modules without deviating from the principle. In some embodiments, Figure 1 The first determination module 110 and the second determination module 120 disclosed in the specification may be different modules in a system, or one module may realize the functions of the above two or more modules. For example, each module may share a storage module, or each module may have its own storage module. Such variations are within the protection scope of this specification.

[0036] Figure 2 is an exemplary flow chart of a method for normalizing a standard uptake value according to some embodiments of this specification. In some embodiments, process 200 may be executed by a processor. Figure 2 As shown, process 200 may include the following steps.

[0037] Step 210 , determining a normalization factor based on the phantom image and the reference standard. In some embodiments, step 210 may be performed by the first determination module 110 .

[0038] The phantom image refers to an image related to the radioactivity of the phantom, and can be an image representing the radioactivity of the phantom pellet and the phantom background.

[0039] In some embodiments, the processor can perform different concentrations of developer infusion on multiple phantom balls and a phantom background of a NEMA IQ phantom. The multiple phantom balls can be balls of multiple different diameters. For example, the diameters of the multiple phantom balls can include 37 mm, 28 mm, 22 mm, 17 mm, 13 mm, and 10 mm. Then, the processor can collect the radioactivity of the phantom background and the multiple phantom balls to obtain a phantom image. The NEMA IQ phantom refers to a physical model designed and produced based on the standards of the National Electrical Manufacturers Association (NEMA).

[0040] It is understandable that, in addition to the spherical diameter, the specification may also provide corresponding descriptions based on other parameters of each phantom sphere, for example, the spherical volume, spherical radius, etc. of each phantom sphere.

[0041] Reference standards refer to standards related to semi-quantitative analysis of SUV. For example, reference standards may include EARL V1.0 and EARL V2.0. Reference standards may include one or more determined standard parameters. Among them, standard parameters refer to one or more parameter types used to evaluate the characteristics of RC values. Standard parameters may include but are not limited to the maximum recovery coefficient (also known as RC max ), average recovery coefficient (also known as RC mean ) and the average value of the highest restitution coefficient area (also known as RC peak ), which can be used as the standard that the RC curve corresponding to the normalized phantom image needs to meet.

[0042] RC max For SUV max Normalized reference standard; RC mean For SUV mean Normalized reference standard; RC peak For SUV peak Normalized reference standard. SUV max It refers to the maximum value of SUV of all pixels in the region of interest (ROI); SUV mean It refers to the average value of SUV of all pixels in ROI; SUV peak Refers to the small area inside the ROI (such as 1cm 3 The maximum value among the average SUV values ​​of the pixels in the image.

[0043] The standard parameters in EARL V1.0 include RC max and RC mean .like Figure 3A , Figure 3B As shown in the figure, EARL V1.0 can include the sphere diameters of the six phantom spheres, the RC corresponding to each phantom sphere, and the mean The upper bound (i.e., “RC mean Maximum value”), lower bound (i.e. “RC mean minimum value") and expected value (i.e. "RC mean Expected value”), RC corresponding to each phantom ball max The upper bound (i.e., “RC max Maximum value”), lower bound (i.e. “RC max minimum value") and expected value (i.e. "RC max expected value”).

[0044] The standard parameters in EARL V2.0 include RC max ,RC mean and RC peak .like Figure 4 As shown in the figure, EARL V2.0 contains the spherical diameters of the six model balls and the RC corresponding to each model ball. mean ,RC max and RC peak The upper and lower bounds of .

[0045] In some embodiments, the processor may obtain the reference standard by accessing the NEMA IQ phantom database.

[0046] The normalization factor refers to a parameter used to normalize the image to be processed. The normalization factor may be a size parameter of a Gaussian filter used to normalize the image to be processed.

[0047] The normalization factor may include at least one of a first factor, a second factor, and a third factor. The first factor is used to normalize the image to be processed and determine the normalized SUV mean Parameters, such as Filter mean , which is used to perform Gaussian filtering on the processed image and determine the normalized SUV mean The second factor is used to normalize the image to be processed and determine the normalized SUV max Parameters, such as Filter max , which is used to perform Gaussian filtering on the processed image and determine the normalized SUV max The third factor is used to normalize the image to be processed and determine the normalized SUV peak Parameters, such as Filter peak , which is used to perform Gaussian filtering on the processed image and determine the normalized SUV peak The size parameter of the Gaussian filter.

[0048] In some embodiments, the processor may process the phantom image through a Gaussian filter of a preset size to obtain a processed phantom image, and then calculate the RC curve corresponding to the processed phantom image. The preset size may be a default value, an empirical value, etc.

[0049] In some embodiments, the processor can determine the actual radioactivity ratio of the phantom sphere and the phantom background based on the phantom image; determine the ideal radioactivity ratio of the phantom sphere and the phantom background based on the concentration ratio of the imaging agent perfused into the phantom sphere and the phantom background; then calculate the recovery coefficient of each phantom sphere based on the actual radioactivity ratio and the ideal radioactivity ratio, and draw the RC curve corresponding to the phantom image based on the recovery coefficient of each phantom sphere. The horizontal coordinate of each point in the RC curve is the sphere diameter of each phantom sphere, and the vertical coordinate is the recovery coefficient corresponding to the phantom sphere.

[0050] For example only, when the concentration ratio of each phantom sphere to the phantom background perfusion imaging agent is 10:1, the processor can set the ideal radioactivity of the phantom sphere to 10 and the ideal radioactivity of the phantom background to 1, then the ideal radioactivity ratio of each phantom sphere is 10 / 1=10. When the processor can determine that the actual radioactivity of a phantom sphere is 9 and the actual radioactivity of the phantom background is 0.95 based on the actual acquired phantom image, then the actual radioactivity ratio of the phantom sphere is 9 / 0.95=9.47, and the corresponding RC value of the phantom sphere is calculated to be 9.47 / 10=0.947. The above method can be used to determine the corresponding RC value of each phantom sphere, thereby determining the RC curve corresponding to the phantom image.

[0051] The processor can determine whether the RC curve corresponding to the processed model image meets the corresponding preset restoration condition. In response to no, the size of the Gaussian filter is modified, and the Gaussian filter is iterated until the RC curve corresponding to the processed model image meets the preset restoration condition. The processor can determine the size corresponding to the Gaussian filter at this time as the normalization factor. Among them, the preset restoration condition refers to the condition that the RC curve corresponding to the processed model image needs to meet. For example, the preset restoration condition may include that the absolute percentage error between the RC value of each point in the RC curve corresponding to the processed model image and the expected value of the RC value of the corresponding point in the reference standard is less than an error threshold. Among them, the error threshold can be a preset value (such as 10%). For more information about expected values, please refer to Figure 6 and its related description.

[0052] As an example only, the processor may process the phantom image through a Gaussian filter of a preset size to obtain a processed phantom image, and then calculate the RC corresponding to the processed phantom image. mean Curve, to determine the RC corresponding to the processed phantom image mean Does the curve satisfy the corresponding RC mean Restore the preset conditions, respond to no, modify the size of the Gaussian filter, iterate the Gaussian filter until the RC corresponding to the processed model image is mean The curve meets RCmean Restore the preset conditions, and the processor can use the Filter corresponding to the Gaussian filter at this time mean Determined as the first factor. Among them, RC mean Restoring the preset condition refers to the RC corresponding to the processed phantom image mean The conditions that the curve needs to meet. For example, RC mean The restoration preset condition may include the RC corresponding to the processed phantom image mean The RC of each point on the curve mean The value of the corresponding point in the standard parameter RC mean The absolute percentage error between the expected values ​​of the values ​​is less than RC mean Error threshold. Among them, RC mean The error threshold may be a preset value (eg, 10%). The processor determines the second factor and the third factor in a similar manner to the processor determines the first factor. For details about the processor determining the second factor and the third factor, refer to the aforementioned processor determining the first factor.

[0053] In some embodiments, the processor may iteratively normalize the phantom image based on the standard parameters in EARL V1.0 to determine the first factor and the second factor; based on the first factor and the second factor, determine the third factor by a first preset method. For more information about the above embodiments, please refer to Figure 5 and its related description.

[0054] In some embodiments, the processor may also calculate the expected value of the standard parameter based on the upper and lower bounds of the standard parameter in EARL V2.0 by a second preset method; based on the upper and lower bounds of the standard parameter and the expected value, iteratively perform the normalization process on the model image to determine at least one of the first factor, the second factor, and the third factor. For more information about the above embodiments, please refer to Figure 6 and its related description.

[0055] Step 220 , normalizing the image to be processed using the normalization factor to determine a normalized standard uptake value. In some embodiments, step 220 may be performed by the second determination module 120 .

[0056] The image to be processed refers to a human body image that needs to be semi-quantitatively analyzed for SUV. The processor can obtain the image to be processed by scanning the patient through a scanning device (such as computed tomography (CT), positron emission computed tomography (PET), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), PET-CT imaging equipment, PET-MR imaging equipment, etc.).

[0057] It should be understood that since SUV will be affected by acquisition conditions and reconstruction conditions, when a certain image to be processed needs to be analyzed and processed, its acquisition conditions and reconstruction conditions should be the same as the acquisition conditions and reconstruction conditions of the corresponding model image when the normalization factor is obtained, so that the normalization factor corresponding to the model image can be used to normalize the image to be processed, thereby obtaining the normalized SUV.

[0058] The acquisition conditions refer to conditions related to image acquisition. For example, the acquisition conditions may include, but are not limited to, one or more of image acquisition duration, scanning speed, scanning parameters, scanning device type, acquisition mode, and the like.

[0059] The reconstruction condition refers to a condition related to image reconstruction, for example, the reconstruction condition may include an image reconstruction algorithm, etc.

[0060] The normalized standard uptake value refers to the normalized SUV. For example, the normalized standard uptake value may include u.SUV mean 、u.SUV max 、u.SUV peak wait.

[0061] In some embodiments, the processor may perform Gaussian filtering on the image to be processed based on the normalization factor to obtain a normalized standard uptake value.

[0062] It is worth noting that the standard uptake value before normalization will be affected by the inspection process, image acquisition and reconstruction methods, etc., which will reduce its accuracy and repeatability. However, some embodiments of this specification determine the normalization factor through the phantom image and the reference standard, and perform normalization processing on the image to be processed based on the normalization factor to obtain the normalized standard uptake value. By using the same acquisition conditions and reconstruction conditions to acquire the phantom image and the image to be processed, the control variables are helpful to reduce the amount of calculation, and finally obtain a comparable SUV across devices, patients, and time, which improves the application value of SUV in efficacy evaluation, inter-group comparison, etc.

[0063] In some embodiments, the processor can generate a normalized metabolic tumor volume (MTV) and a normalized total lesion glycolysis (TLG) based on the normalized standard uptake value, thereby reflecting the tumor metabolic activity and tumor metabolic volume. For example, the normalized MTV can be calculated by using a percentage threshold to calculate the normalized SUV. For example, when the threshold is 40% u.SUV max When MTV = 40% * u.SUV max The normalized MTV is calculated. The normalized TLG can be obtained by the formula TLG = MTV × u.SUV mean Calculated.

[0064] Figure 5 FIG. 5 is an exemplary flow chart of determining a normalization factor based on EARL V1.0 according to some embodiments of this specification. In some embodiments, process 500 may be executed by a processor. Figure 5 As shown, process 500 may include the following steps.

[0065] Step 510: Based on the standard parameters in EARL V1.0, the phantom image is iteratively normalized to determine the first factor and the second factor.

[0066] For more information about standard parameters, first factors, and second factors in EARL V1.0, see Figure 2 and its related description.

[0067] Understandably, due to the lack of EARL V1.0 about RC peak Therefore, the processor can only iteratively normalize the model image based on the standard parameters in EARL V1.0 to determine the first factor and the second factor, and cannot directly obtain the third factor.

[0068] The processor iteratively normalizes the phantom image based on the standard parameters in EARL V1.0 to determine the first factor and the second factor in a manner similar to the manner in which the processor determines the normalization factor based on the phantom image and the reference standard. For details about the processor iteratively normalizes the phantom image based on the standard parameters in EARL V1.0 to determine the first factor and the second factor, see Figure 2 The processor determines the normalization factor based on the phantom image and the reference standard.

[0069] Step 520: Determine a third factor by a first preset method based on the first factor and the second factor.

[0070] The first preset method refers to a method for determining the third factor. For example, the first preset method may include determining the third factor based on device parameters, the first factor, and the second factor through operating experience.

[0071] In some embodiments, the first preset method may include determining the third factor based on the maximum value of the first factor and the second factor. For example, the processor may sort the first factor and the second factor according to size and directly determine the maximum value thereof as the third factor.

[0072] It is worth noting that through the phantom test based on EARL V2.0, it was found that after the phantom image was normalized, it met the RC peak When the Gaussian filter size is about Filter max and Filter mean Therefore, some embodiments of the present specification quickly and conveniently determine the third factor in EARL V1.0 through the maximum value of the first factor and the second factor, which is helpful to reduce the amount of calculation.

[0073] In some embodiments of this specification, based on the standard parameters in EARL V1.0, the phantom image is iteratively normalized to determine the first factor and the second factor; and the third factor is determined based on the first factor and the second factor, so as to achieve the missing RC in EARL V1.0. peak The third factor is obtained by taking the upper bound, lower bound and expected value of the image into consideration, so that the processed image can be normalized to obtain the normalized SUV.

[0074] Figure 6 600 is an exemplary flow chart of determining a normalization factor based on EARL V2.0 according to some embodiments of this specification. In some embodiments, process 600 may be executed by a processor. Figure 6 As shown, process 600 may include the following steps.

[0075] Step 610: Based on the upper bound and lower bound of the standard parameter in EARL V2.0, the expected value of the standard parameter is calculated by a second preset method.

[0076] For more information about standard parameters in EARL V2.0, see Figure 2 and its related description.

[0077] Understandably, due to the lack of RC in EARL V2.0 mean ,RC max and RC peak The processor cannot directly normalize the phantom image iteration based on the standard parameters in EARL V2.0 to determine the first factor, the second factor, and the third factor. Therefore, the processor can first obtain RC based on the standard parameters in EARL V2.0. mean ,RC max and RC peak The expected value of , and then further determine the first factor, the second factor and the third factor.

[0078] The expected values ​​of the standard parameters refer to the preferred values ​​of RC.

[0079] The second preset method refers to a method for determining the expected value of the standard parameter. For example, the second preset method may include determining the expected value through operation experience based on the device parameter, the upper bound and the lower bound of the standard parameter in EARL V2.0.

[0080] In some embodiments, the second preset method may include determining the expected value based on the average of the upper and lower bounds of the standard parameter. For example, the processor may calculate RC mean The average of the upper and lower bounds is directly used as RC mean expected value.

[0081] It is worth noting that, through Figure 3A as well as Figure 3B The calculation of EARL V1.0 shown in the figure shows that the expected value of a standard parameter in EARLV1.0 is approximately the average of the upper and lower bounds of the standard parameter. Figure 3A As shown, the RC of the phantom ball with a spherical diameter of 37 mm mean The upper bound is 0.83, the lower bound is 0.71, and the average of the upper and lower bounds is (0.83+0.71) / 2=0.77. Figure 3A The RC of the ball in the model meanThe expected value of is also 0.77. Therefore, the processor can average the upper and lower bounds of each standard parameter in EARL V2.0 and directly determine the expected value corresponding to each standard parameter, which not only enriches the numerical content of the standard parameters in EARL V2.0, but also helps to reduce the amount of calculation.

[0082] Step 620 , based on the expected value of the standard parameter, iteratively normalize the phantom image to determine at least one of the first factor, the second factor, and the third factor.

[0083] The processor iteratively normalizes the phantom image based on the expected values ​​of the standard parameters in EARL V2.0 to determine at least one of the first factor, the second factor, and the third factor, similar to the way the processor determines the normalization factor based on the phantom image and the reference standard. For information about the processor iteratively normalizing the phantom image based on the expected values ​​of the standard parameters in EARL V2.0 to determine at least one of the first factor, the second factor, and the third factor, see Figure 2 The processor determines the normalization factor based on the phantom image and the reference standard.

[0084] Some embodiments of this specification can quickly and conveniently find missing RC in EARL V2.0 through the upper and lower bounds of standard parameters in EARL V2.0. mean ,RC max and RC peak The expected value of is supplemented, thus enriching the numerical content of the standard parameters in EARL V2.0. In addition, the expected value of its standard parameters is used to determine the first factor, the second factor, and the third factor, so as to realize the normalization of the processed image and obtain the normalized SUV.

[0085] It should be noted that the above descriptions of process 200, process 500 and process 600 are only for illustration and description, and do not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to process 200, process 500 and process 600 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0086] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0087] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0088] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0089] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0090] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0091] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0092] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A method for normalizing a standard uptake value, characterized in that: The method is executed by a processor, comprising: determining a normalization factor based on the phantom image and the reference standard; The image to be processed is normalized using the normalization factor to determine a normalized standard uptake value.

2. The method according to claim 1, characterized in that: The reference standard includes EARL V1.0, the normalization factor includes at least one of a first factor, a second factor, and a third factor; and determining the normalization factor based on the phantom image and the reference standard includes: Iteratively performing the normalization process on the phantom image based on standard parameters in EARL V1.0 to determine the first factor and the second factor, wherein the standard parameters in EARL V1.0 include a maximum recovery coefficient and an average recovery coefficient; The third factor is determined by a first preset method based on the first factor and the second factor.

3. The method according to claim 2, characterized in that The first preset method includes determining the third factor based on a maximum value of the first factor and the second factor.

4. The method according to claim 1, characterized in that: The reference standard includes EARL V2.0, the normalization factor includes at least one of a first factor, a second factor, and a third factor; and determining the normalization factor based on the phantom image and the reference standard includes: Based on the upper bound and the lower bound of the standard parameter in the EARL V2.0, the expected value of the standard parameter is calculated by a second preset method, wherein the standard parameter in the EARL V2.0 includes at least one of the highest restitution coefficient, the average restitution coefficient and the average value of the highest restitution coefficient region; Based on the expected value of the standard parameter, the normalization process is iteratively performed on the phantom image to determine at least one of the first factor, the second factor, and the third factor.

5. The method according to claim 4, characterized in that The second preset method includes determining the expected value based on an average value of the upper bound and the lower bound of the standard parameter.

6. A standard uptake value normalization system, characterized in that: The system comprises: A first determination module, configured to determine a normalization factor based on a phantom image and a reference standard; The second determination module is used to perform normalization processing on the image to be processed using the normalization factor to determine a normalized standard uptake value.

7. The system according to claim 6, characterized in that The reference standard includes EARL V1.0, the normalization factor includes at least one of a first factor, a second factor, and a third factor; and the first determination module is further used for: Iteratively performing the normalization process on the phantom image based on standard parameters in EARL V1.0 to determine the first factor and the second factor, wherein the standard parameters in EARL V1.0 include a maximum recovery coefficient and an average recovery coefficient; The third factor is determined by a first preset method based on the first factor and the second factor.

8. The system according to claim 7, characterized in that The first preset method includes determining the third factor based on a maximum value of the first factor and the second factor.

9. The system according to claim 6, characterized in that The reference standard includes EARL V2.0, the normalization factor includes at least one of a first factor, a second factor, and a third factor; and the first determination module is further used for: Based on the upper bound and the lower bound of the standard parameter in the EARL V2.0, the expected value of the standard parameter is calculated by a second preset method, wherein the standard parameter in the EARL V2.0 includes at least one of the highest restitution coefficient, the average restitution coefficient and the average value of the highest restitution coefficient region; Based on the expected value of the standard parameter, the normalization process is iteratively performed on the phantom image to determine at least one of the first factor, the second factor, and the third factor.

10. The system according to claim 9, characterized in that The second preset method includes determining the expected value based on an average value of the upper bound and the lower bound of the standard parameter.

Images