Representation of computed tomography data

Abstract

The proposed concepts are for assisting or improving the representation and visualization of CT data. In particular, embodiments provide a method and / or system for normalizing the HU scale for a material of interest (other than air or water) across CT data such that the HU value for the material of interest is substantially constant across multiple CT images.

Description

[Technical Field]

[0001] This invention relates to the field of medical data processing, particularly to the field of processing computed tomography (CT) data for representation. [Background technology]

[0002] Computed tomography (CT) is a technique that measures the transmission of a (multicolor) X-ray beam in all axial directions around an object and reconstructs this information by back projection, enabling the measurement of local attenuation of the object in three dimensions. The reconstructed information represents the local attenuation (μ) at each location.

[0003] A typical way to represent the attenuation characteristics of a subject (e.g., a subject / patient's body tissue) to a user is not to report local attenuation μ, but to use a Haunsfield unit (HU) scale.

[0004] The HU scale normalizes attenuation for air and water. More specifically, the Haunsfield Unit (HU) scale is defined based on the linear attenuation coefficients of water and air at a given X-ray energy level (typically 120 kVp). This is because air represents the conditions outside of body tissue, which mainly consists of water. Specifically, HU is a scale that assigns numerical values ​​to the radiation density of tissues, with air being -1000 HU and water being 0 HU. The scale is defined by the following formula: HU = 1000·(μ-μ water ) / (μ water -μ air ) (i) Here, μ is the linear decay coefficient of the tissue, water μ is the linear damping coefficient for water, and μ is the linear damping coefficient for air. air This is the linear attenuation coefficient of air. The linear attenuation coefficient is a measure of how strongly a material absorbs X-rays; a higher value indicates greater absorption.

[0005] The HU (Heat Element) can vary for different X-ray energy levels used in CT imaging. This is because the HU value depends on the linear decay coefficient of the tissue, which in turn depends on the energy of the X-ray photon. The linear decay coefficient of a material decreases with increasing X-ray energy, and therefore, the HU values ​​obtained at different X-ray energy levels can be different. [Overview of the project] [Problems that the invention aims to solve]

[0006] As a result, switching X-ray energy levels in a spectral single-energy image alters the contrast between materials. This can make interpreting the image difficult. [Means for solving the problem]

[0007] The present invention is defined by the claims.

[0008] According to an embodiment of one aspect of the present invention, a method for representing CT data is provided. This method includes the steps of: identifying first and second materials of interest in CT data of a plurality of CT images, wherein at least one of the first and second materials of interest is neither air nor water; and normalizing the Hounsfield unit scale for the first and second materials of interest across the entire CT data such that the HU values ​​for each of the first and second materials of interest are substantially constant across the plurality of CT images.

[0009] Therefore, the proposed concept aims to provide schemes, solutions, concepts, designs, methods, and systems related to the improvement of the representation or visualization of CT data. In particular, embodiments of the present invention propose that by using one or more different reference materials, the HU scale can be normalized for materials other than air and water. That is, the embodiments propose different scales for normalizing the scale for two given materials (at least one of the materials is neither air nor water) so that the level / window setting in the visualization of CT data may not need to be rescaled. In this way, a material-specific HU scale may be provided.

[0010] The proposed concept may be regarded as similar to the concept of changing the Celsius scale from being normalized with respect to water (0 is the melting point of water and 100 is the boiling point) to being normalized with respect to another material. For example, the proposed concept may be similar to defining an iron-Celsius scale where the melting point of iron is defined as 0 and the boiling point of iron is defined as 100.

[0011] In other words, it is proposed that the modified HU scale can normalize the attenuation for materials other than air and water. As an example, according to the proposed embodiment, the HU scale may be defined based on the linear attenuation coefficients of bone and fat, and across the entire CT data, the HU values for bone and fat remain substantially constant across multiple CT images at different X-ray energy levels.

[0012] The embodiments propose to change the representation of CT data, which may improve the interpretation of the data for a particular material of interest. Therefore, the embodiments may be used in relation to medical evaluation and / or treatment selection to support medical professionals. Such embodiments may also support clinical planning. Therefore, improved clinical decision support (CDS) may be provided by the proposed concept.

[0013] The first or second material of interest may be, for example, one of iodine, bone, bone marrow, fat, iron, calcium, white matter, gray matter, gadolinium, gold, oxygen, xenon, neon, blood, uric acid, NaCl, muscle, water, air, or combinations thereof. In this way, embodiments may support improved representation of specific materials of interest for medical evaluation and / or assessment.

[0014] In some embodiments, normalizing the Hounsfield unit scale for the first and second materials across CT data may include adjusting the Hounsfield unit scale for the first material of interest across the CT data such that the HU value for the first material of interest across a plurality of CT images is substantially equal to zero. In this way, the HU scale may assign a zero value to the radiation density of the first material of interest.

[0015] For example, normalizing the Hounsfield unit scale for the first and second materials across the entire CT data may include adjusting the local attenuation value μ according to the following equation. HU α,β = -T·(μ - μ β ) / (μ β-μα ) (ii) where T is a target value (e.g., 10, 100, 500, -1000, etc.) for defining a reference point / value of the adjusted scale, μ α is the local attenuation value for the first material, and μ β is the local attenuation for the second material.

[0016] Some embodiments further identify a third material of interest for the CT data, where the third material of interest is different from the first and second materials of interest. Normalizing the Hounsfield unit scale for the first and second materials across the entire CT data may include determining whether the difference between the HU values ​​for the third material of interest and the HU values ​​for the first material of interest is non-zero across multiple CT images, and, in response to determining that the difference is not non-zero across multiple CT images, adjusting the Hounsfield unit scale for the first material of interest such that the difference between the HU values ​​for the third material of interest and the HU values ​​for the first material of interest is non-zero across multiple CT images.

[0017] In one embodiment, adjusting the Haunsfield unit scale may include adjusting the local attenuation value μ according to the following formula. HUadj α,β = -T·(μ-max(μ β ,μ α )) / (max(μ β ,μ α )-min(μ β ,μ α )) (iii) Here, T is the target value (e.g., 10, 100, 500, -1000, etc.), and μ is the local attenuation value for the first material. β This is local attenuation for the second material.

[0018] For example only, the multiple CT images may include multiple single-energy spectral images. Thus, embodiments may be employed to ensure that the HU values ​​for each of the first and second materials of interest are substantially constant across multiple single-energy spectral images captured at different X-ray energy levels.

[0019] The embodiments may be employed in combination with conventional / existing CT scanning equipment. In this way, the embodiments may be integrated into legacy systems to improve and / or extend their functions and capabilities. Thus, improved CT scanners / imaging systems may be provided by the proposed embodiments.

[0020] The proposed method may be implemented on a computer. Furthermore, the embodiments may exclude methods for performing such mental acts.

[0021] In another embodiment, a computer program product for representing CT data is provided, the computer program product having a computer-readable storage medium having computer-readable program code configured to perform all the steps of the proposed embodiment.

[0022] Therefore, a computer program product according to the proposed embodiment, and a computer system having one or more processors configured to perform the method according to the proposed concept by executing the computer-readable program code of the computer program product, may also be provided.

[0023] According to yet another aspect of the present invention, a medical data processing system for processing CT data is provided, the system comprising a control unit configured to identify first and second materials of interest with respect to CT data of a plurality of CT images, wherein at least one of the first and second materials of interest is neither air nor water, and a data processor configuration configured to normalize the Hounsfield unit scale for the first and second materials of interest across the entire CT data such that the HU values ​​for each of the first and second materials of interest are substantially constant across the plurality of CT images.

[0024] The system may be located remotely from the user's device for the representation of CT data. In this way, the user (such as a healthcare professional) may have a well-located system that can receive data / information at a location away from the system for processing the CT data. Thus, embodiments may enable the user to visualize, review and / or interpret CT data using a local system (which may have a portable display device such as a laptop, tablet computer, mobile phone, or PDA). As an example, embodiments may provide an application for a mobile computing device which can be run and / or controlled by the user of the mobile computing device.

[0025] The system may further include a server device containing a system for processing CT data, and a client device having a user interface. Therefore, dedicated data processing means may be employed to process CT data according to the proposed concept and thus reduce the processing requirements or performance of other components or devices of the system.

[0026] The system may further include a client device, which has a control unit, a data processor configuration, and a display unit. In other words, a user (such as a physician, scanner technician, or medical professional) may have a well-configured client device (such as a laptop, tablet computer, mobile phone, or PDA) that processes the received data for representation and generates display control signals. Thus, purely as an example, an embodiment may provide a system that enables CT data review / evaluation for one or more subjects (e.g., patients) from a single location, where real-time communication between the CT scanner and the user (e.g., a clinician, technician, medical professional, or physician) is provided, for example. It may have functions that are extended or modified by the proposed concept.

[0027] Therefore, it will be understood that processing capacity can be distributed across the entire system in different ways, depending on predetermined constraints and / or the availability of processing resources.

[0028] Therefore, a proposed concept may exist that employs a material-specific HU scale (other than the conventional HU scale that normalizes attenuation for air and water). This could help improve the representation and / or visualization of CT data by ensuring that the contrast between materials of interest remains constant across CT data captured at different X-ray energy levels.

[0029] These and other aspects of the present invention will become apparent from and be explained with reference to the embodiments described below.

[0030] For a better understanding of the present invention and to more clearly illustrate how the present invention is carried out, the accompanying drawings are referenced merely as examples. [Brief explanation of the drawing]

[0031] [Figure 1] This graph shows the variation in HU (Heat Element) due to X-ray energy levels for various materials of interest using the conventional HU scale, which normalizes the attenuation for air and water. [Figure 2] This graph shows the variation in HU (Heat Element) for various materials with respect to X-ray energy levels, using an HU scale normalized according to the embodiment for water and bone. [Figure 3] This graph shows the variation in HU (Heat Scale) for various materials with respect to X-ray energy levels, using an HU scale normalized according to the embodiment for water and iodine. [Figure 4] This is a simplified flowchart of a method for representing CT data according to one embodiment. [Figure 5] This graph shows the variation in HU (Heat Element) for various materials with respect to X-ray energy levels, using a HU scale normalized according to the embodiment for iodine and bone. [Figure 6] This graph shows the variation in HU (Human Energy) for various materials with respect to X-ray energy levels, using a normalized HU scale according to another embodiment. [Figure 7] This is a simplified block diagram of a computer in which one or more parts of one embodiment may be employed. [Modes for carrying out the invention]

[0032] The present invention will be described with reference to the drawings.

[0033] The detailed descriptions and specific examples illustrate exemplary embodiments of the apparatus, systems, and methods, but should be understood to be for illustrative purposes only and not intended to limit the scope of the invention. These and other features, aspects, and advantages of the apparatus, systems, and methods of the invention will be better understood from the following description, the appended claims, and the appended drawings. The mere fact that certain means are described in different dependent claims does not imply that combinations of these means cannot be used advantageously.

[0034] Modifications of the disclosed embodiments can be understood and implemented by those skilled in the art in carrying out the claimed invention, based on a review of the drawings, disclosures, and appended claims. In the claims, the words “comprising” do not exclude other components or steps, and the indefinite articles “a” or “an” do not exclude plurality.

[0035] Please understand that the drawings are merely schematic and are not drawn to a specific scale. Also, please understand that the same reference number is used throughout the drawings to indicate the same or similar parts.

[0036] The present invention proposes a concept for assisting or improving the representation and visualization of CT data. In particular, embodiments may provide a method and / or system for normalizing the HU scale for a material of interest (other than air or water) across CT data such that the HU value for the material of interest is substantially constant across multiple CT images.

[0037] In particular, the proposed concept may provide an approach that offers a material-specific HU scale. This material-specific HU scale may be used in the image viewer to represent intensity values. However, since users will be familiar with the interpretation of standard / conventional HU values ​​(normalized with respect to air and water), a suitable application would be to convert the level / window setting from one energy level to another, while the viewer still reports the usual air-water HU values. Alternatively, the material-specific HU can also be used directly by the viewer to represent the decomposition of the signal as a function of the two materials. Thus, the embodiment can be used in relation to the representation and evaluation of CT data, thereby supporting improved medical evaluation and improved clinical decision support (CDS).

[0038] For illustrative purposes only, exemplary embodiments may be used in many different types of clinical, medical, or subject-related settings, such as hospitals, clinics, wards, nursing homes, and private homes.

[0039] The proposed concepts may provide schemes, solutions, concepts, designs, methods, and systems related to improving the representation or visualization of CT data. In particular, embodiments of the present invention propose that the HU scale can be normalized for materials other than air and water by using one or more different reference materials. Thus, embodiments may provide different HU scales normalized with respect to two materials of interest (at least one of which is neither air nor water). Material-specific HU scales can therefore be provided by such embodiments.

[0040] Figure 1 is a graph showing the variation in HU (Heat Burden) across various materials of interest at different X-ray energy levels, using the conventional HU scale (which normalizes the attenuation for air and water). From the graph in Figure 1, it can be seen that the HU value for air is equal to -1000 HU across various X-ray energy levels, and the HU value for water is equal to 0 HU across various X-ray energy levels. In other words, using the accepted convention HU scale, the HU values ​​for air and water, respectively, are substantially constant across the entire CT X-ray energy level.

[0041] For materials other than water and air, such as iodine, water, or bone, the HU value varies significantly with respect to the X-ray energy level. This poses a problem in interpreting single-energy images at different energy levels. For example, it can be difficult to review and / or optimize level / window settings when scrolling through images at different energy levels. It is proposed to address this problem by making the HU adaptable to materials of interest other than air or water.

[0042] In particular, it is proposed to normalize the Haunsfield unit scale across the entire CT data for the first and second materials of interest (where at least one of the first and second materials of interest is neither air nor water) such that the HU values ​​for each of the first and second materials of interest are substantially constant across multiple CT images. For example, such normalization of the HU scale can be achieved by adjusting the local attenuation value according to the following equation. HU α,β = -T·(μ-μ β ) / (μ β -μ α ) (ii) Here, T is the target value (e.g., 10, 100, 500, -1000, etc.), and μ α This is the local attenuation value for the first material, μ β This is local attenuation for the second material.

[0043] Referring to Figure 2, an example of the proposed concept is shown where the first material of interest is water and the second material of interest is bone. Specifically, Figure 2 is a graph showing the variation of HU with respect to X-ray energy levels for various materials, according to a HU scale normalized for water and bone. From the graph in Figure 2, it can be seen that the HU value for water is equal to -1000 HU across various X-ray energy levels, and the HU value for bone is equal to 0 HU across various X-ray energy levels. In other words, using a HU scale normalized for water and bone according to the proposed concept, the HU values ​​for water and bone, respectively, are substantially constant across the entire CT X-ray energy level.

[0044] As a further example, Figure 3 shows an embodiment in which the first material of interest is water and the second material of interest is iodine. Specifically, Figure 3 is a graph showing the variation of HU with respect to X-ray energy levels for various materials, according to a HU scale normalized for water and iodine. From the graph in Figure 3, it can be seen that the HU value for water is equal to -1000 HU across various X-ray energy levels, and the HU value for iodine is equal to 0 HU across various X-ray energy levels. That is, using a HU scale normalized for water and iodine according to the proposed concept, the HU values ​​for water and iodine, respectively, are substantially constant across the entire CT X-ray energy level.

[0045] From the graphs in Figures 2 and 3, it can be seen that the contrast of the selected material of interest remains constant across the range of X-ray energy levels, while the contrast of other materials changes across the entire range of X-ray energy levels.

[0046] Taking into account the above-described embodiments in Figures 2 and 3, a method for representing CT data according to one embodiment will now be described with reference to Figure 4.

[0047] Figure 4 is a simplified flowchart of Method 400 for representing CT data according to one embodiment. Here, CT data refers to data from multiple CT images, specifically multiple single-energy spectral images.

[0048] This method begins with step 410, which identifies first and second materials of interest in CT data. At least one of the first and second materials of interest is neither air nor water. In this example, the first material of interest is one of the set of iodine, bone, and fat. The materials of interest may be identified based, for example, on a user input signal (e.g., received via a user interface). This may be defined, for example, by two sample tissues / materials from the scan image (e.g., the user may interact with the scan image to identify a first region of interest defining the first material and a second region of interest defining the second material).

[0049] Next, the method proceeds to step 420, which normalizes the Hounsfield unit scale for the first and second materials of interest across the entire CT data such that the HU values ​​for each of the first and second materials of interest are substantially constant across multiple CT images. Here, the normalization of the Hounsfield unit scale for the first and second materials across the CT data comprises two substeps 422 and 424.

[0050] Step 422 includes adjusting the Hounsfield unit scale for the first material of interest across the entire CT data so that the HU value for the first material of interest across multiple CT images is substantially equal to zero.

[0051] Step 424 involves adjusting the Hounsfield unit scale for the first material of interest across the entire CT data so that the HU value for the second material of interest across multiple CT images is substantially equal to a target value T (e.g., 0, 100, or -1000), and so the target value T defines the reference point / value of the adjusted scale.

[0052] As already shown above, step 420, which normalizes the Haunsfield unit scale for the first and second materials across the entire CT data, may also include adjusting the local attenuation values ​​according to the following formula. HU α,β = -T·(μ-μ β ) / (μ β -μ α ) (ii) Here, T is the target value (e.g., 100, 500, -1000, etc.), and μ α This is the local attenuation value for the first material, μ β This is local attenuation for the second material.

[0053] However, it should be noted that problems can arise if the contrast between the two selected materials (i.e., the first and second materials of interest) is reversed at some point in the spectrum (which can completely reverse the contrast of the visual representation). An example of a combination of selected materials in which this occurs is bone and iodine, and from Figures 2 and 3, it can be seen that the HU variations for iodine and bone cross at an X-ray energy level of approximately 75 keV (depending on the concentration of iodine).

[0054] Furthermore, considering the combination of bone and iodine materials, Figure 5 shows an embodiment in which the first material of interest is iodine and the second material of interest is bone. Specifically, Figure 5 is a graph showing the variation of HU with respect to X-ray energy levels for various materials, according to a HU scale normalized for iodine and bone. From the graph in Figure 5, it can be seen that the HU value for iodine is equal to -1000 HU across various X-ray energy levels, and the HU value for bone is equal to 0 HU across various X-ray energy levels. That is, using a HU scale normalized for iodine and bone, the HU values ​​for iodine and bone, respectively, are substantially constant across the entire CT X-ray energy level (at -1000 HU and 0 HU, respectively).

[0055] From the graph in Figure 5, it can be seen that the contrast of the selected materials of interest (iodine and bone) is constant across the X-ray energy level range, while the contrast of other materials changes across the X-ray energy level range and reverses at approximately 75 keV. Therefore, normalizing the HU scale for iodine and bone reverses the contrast for other materials. For this reason, μ α <μ β Alternatively, it is desirable to confirm that the scale is inverted.

[0056] For example, this can be achieved by adjusting the local attenuation value μ according to the following equation. HUadj α,β = -T·(μ-max(μ β ,μ α )) / (max(μ β ,μ α )-min(μ β ,μ α )) (iii) Here, T is the target value (e.g., 100, 500, -1000, etc.), and μ α This is the local attenuation value for the first material, μ β This is local attenuation for the second material.

[0057] Figure 6 is a graph showing the variation in HU for various materials with respect to X-ray energy levels, using the HU scale normalized for iodine and bone using equation (iii) above. From the graph in Figure 6, it can be seen that the HU values ​​for iodine and bone are generally constant across various X-ray energy levels, but reverse at an X-ray energy level of approximately 75 keV. Furthermore, it can be seen that the HU values ​​for other materials remain lower than those for iodine and bone across the range of X-ray energy levels (i.e., the contrast for other materials does not reverse).

[0058] Figure 7 shows an example of a computer system 800 in which one or more parts of one embodiment may be employed. The various operations described above may utilize the functions of computer 800. For example, one or more parts of the system for providing a subject-specific user interface can be incorporated into any element, module, application and / or component described herein. In this regard, it should be understood that the system function blocks may run on a single computer or may be distributed across several computers and locations (e.g., connected via the Internet).

[0059] Computer 800 includes, but is not limited to, PCs, workstations, laptops, PDAs, palm devices, servers, and storage devices. Generally, with respect to the hardware architecture, computer 800 may include one or more processors 810, memory 820, and one or more I / O devices 870 that are communicatively coupled via a local interface (not shown). The local interface may be one or more buses or other wired or wireless connections, for example, but is not limited to, as known in the art. The local interface may have additional elements such as controllers, buffers (caches), drivers, repeaters, and receivers to enable communication. Furthermore, the local interface may include address, control, and / or data connections to enable appropriate communication between the aforementioned components.

[0060] The processor 810 is a hardware device for executing software that can be stored in memory 820. The processor 810 can effectively be any custom-made or commercially available processor, central processing unit (CPU), digital signal processor (DSP), or auxiliary processor among several processors associated with the computer 800, and the processor 810 can be a semiconductor-based microprocessor or microprocessor (in the form of a microchip).

[0061] Memory 820 can be one or a combination of volatile memory elements (e.g., random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), etc.) and non-volatile memory elements (e.g., ROM, erasable programmable read-only memory (EPROM), electronically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), tape, compact disk read-only memory (CD-ROM), disk, floppy disk, cartridge, cassette, etc.). Furthermore, memory 820 may incorporate electrical, magnetic, optical, and / or other types of storage media. It should be noted that memory 820 can have a distributed architecture, where various components are located geographically separated from each other but are accessible by processor 1.

[0062] The software in memory 820 may include one or more separate programs, each containing an ordered list of executable instructions for implementing a logical function. The software in memory 820 may include, in exemplary embodiments, a suitable operating system (O / S) 850, a compiler 840, source code 830, and one or more applications 860. As shown in the figures, application 860 has multiple functional components for performing the features and operations of the exemplary embodiment. Application 860 of computer 800 may represent various applications, computing units, logic, functional units, processes, operations, virtual entities, and / or modules in exemplary embodiments, but application 860 is not limited to these.

[0063] The operating system 850 controls the execution of other computer programs and provides scheduling, input / output control, file and data management, memory management, communication control, and related services. The inventors intend that application 860 for carrying out exemplary embodiments may be applicable to all commercially available operating systems.

[0064] Application 860 may be a source program, an executable program (target code), a script, or any other entity including a set of instructions to be executed. In the case of a source program, the program is usually translated through a compiler (such as Compiler 840), assembler, interpreter, etc., which may or may not be contained in memory 820 in order to function properly in relation to O / S 850. Furthermore, Application 860 can be written as a target-oriented programming language, which has classes of data and methods, or procedural programming languages, and these languages ​​have routines, subroutines, functions, and include, but are not limited to, C, C++, C#, Pascal, BASIC, API calls, HTML, XHTML, XML, ASP scripts, JavaScript, FORTRAN, COBOL, Perl, Java, ADA, .NET, etc.

[0065] The I / O device 870 may include, but is not limited to, input devices such as a mouse, keyboard, scanner, microphone, or camera. Furthermore, the I / O device 870 may include, but is not limited to, output devices such as a printer or display. Finally, the I / O device 870 may further include, but is not limited to, devices for both input and output communication, such as a network interface card or modulator / demodulator (for accessing remote devices, other files, devices, systems, or networks), radio frequency (RF) or other transceivers, telephone interfaces, bridges, routers, etc. The I / O device 870 also includes components for communication over various networks such as the Internet or an intranet.

[0066] If Computer 800 is a PC, workstation, or intelligent device, the software in memory 820 may also include a Basic Input / Output System (BIOS) (omitted for simplification). The BIOS is a set of essential software routines that initialize and test the hardware at startup, boot the OS 850, and support data transfer between hardware devices. The BIOS is stored in some type of read-only memory, such as ROM, PROM, EPROM, or EEPROM, so that the BIOS can be executed when Computer 800 is started.

[0067] When computer 800 is operating, processor 810 is configured to execute software stored in memory 820, communicate results with memory 820, and generally control the operation of computer 800 according to the software. Application 860 and O / S 850 are read in whole or in part by processor 810, possibly buffered within processor 810, and then executed.

[0068] When Application 860 is implemented in software, it should be noted that Application 860 may be stored in substantially any computer-readable medium for use by or in connection with any computer-related system or method. In the context of this specification, computer-readable medium may be an electronic, magnetic, optical or other physical device or means capable of housing or storing a computer program for use by or in connection with any computer-related system or method.

[0069] Application 860 may be implemented on any computer-readable medium intended for use by or associated with an instruction execution system, device, or other device, such as a computer-based system, a system including a processor, or other system capable of fetching and executing instructions from an instruction execution system, device, or other device. In the context of this document, “computer-readable medium” can be any means on which a program can be stored, communicated, propagated, or transferred for use by or associated with an instruction execution system, device, or device. A computer-readable medium may, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, apparatus, or propagation medium.

[0070] The method in Figure 4 may be implemented in hardware, software, or a combination of both (for example, as firmware running on a hardware device). As long as one embodiment is partially or entirely implemented in software, the functional steps shown in the process flowchart may be executed by one or more appropriately programmed physical computing devices such as a central processing unit (CPU) or graphics processing unit (GPU). Each process, and its individual component steps shown in the flowchart, may be executed by the same or different computing devices. According to one embodiment, a computer-readable storage medium stores a computer program containing computer program code configured to cause one or more physical computing devices to perform the encoding or decoding method described above when the program is executed on one or more physical computing devices.

[0071] The storage medium may include volatile and non-volatile computer memory such as RAM, PROM, EPROM, and EEPROM, optical discs (such as CDs, DVDs, and BDs), and magnetic storage media (such as hard disks and tapes). The various storage media may be installed in a computing device or may be transportable so that one or more programs stored on the storage medium can be loaded into a processor.

[0072] The CT data processed according to one embodiment may be stored on a storage medium. Similarly, such CT data may be transmitted as a signal modulated on an electromagnetic carrier wave. The signal may be defined according to standards for digital communications. The carrier wave may be an optical carrier wave, a high-frequency wave, a millimeter wave, or a short-range communication wave. This may be wired or wireless.

[0073] As long as one embodiment is implemented in hardware, either partially or entirely, the blocks shown in the block diagram of Figure 7 may be separate physical components, logical subdivisions of a single physical component, or all may be implemented as an integrated single physical component. The functionality of one block shown in the drawing may be divided into multiple components in the implementation, or the functionality of multiple blocks shown in the drawing may be combined into a single component in the implementation. Hardware components suitable for use in embodiments of the present invention include, but are not limited to, conventional microprocessors, application-specific integrated circuits (ASICs), and field-programmable gate arrays (FPGAs). One or more blocks may be implemented as a combination of dedicated hardware for performing some functions and one or more programmed microprocessors and associated circuits for performing other functions.

[0074] Modifications of the disclosed embodiments can be understood and implemented by those skilled in the art in carrying out the claimed invention, based on a review of the drawings, disclosures, and appended claims. In the claims, the words “comprising” do not exclude other components or steps, and the indefinite articles “a” or “an” do not exclude plurality. A single processor or other unit can perform the functions of several items enumerated in the claims. The mere fact that certain means are described in different dependent claims does not imply that combinations of these means cannot be used advantageously. Where a computer program is mentioned above, the computer program may be stored / distributed on a suitable medium, such as an optical or solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunications systems. Where the term “adapted” is used in the claims or specification, the term “adapted” is meant to be equivalent to the term “configured.” No reference numeral in the claims should be construed as limiting in scope.

[0075] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or part of an instruction having one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions shown in a block may occur out of the order shown in the figure. For example, two consecutively shown blocks may actually be executed substantially simultaneously, or blocks may sometimes be executed in reverse order depending on the functions they contain. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in a block diagram and / or flowchart, can be implemented by a purpose-specific hardware-based system that performs a specified function or operation, or a combination of purpose-specific hardware and computer instructions.

Claims

1. A method for representing CT data, wherein the method is A step of identifying first and second materials of interest in CT data of multiple CT images, wherein at least one of the first and second materials of interest is neither air nor water. The steps include: normalizing the Hounsfield unit scale for the first and second materials of interest across the entire CT data so that the HU values ​​for each of the first and second materials of interest are substantially constant across the plurality of CT images; The normalization step is The following formula, HU α,β = -T・(μ-μ β ) / (μ β -μ α ) This includes adjusting the local attenuation value μ, T is the target value, μ α μ is the local attenuation value for the first material, and β This is local damping for the second material, method.

2. The method according to claim 1, wherein the first or second material of interest is one of iodine, bone, bone marrow, fat, iron, calcium, brain white matter, brain gray matter, gadolinium, gold, oxygen, xenon, neon, blood, uric acid, NaCl, or a combination thereof.

3. The step of normalizing the Haunsfield unit scale for the first and second materials across the CT data is: A step of adjusting the Hounsfield unit scale for the first material of interest across the CT data such that the HU value for the first material of interest across the plurality of CT images becomes substantially equal to zero. The method according to claim 1 or 2, comprising:

4. A step of identifying a third material of interest in the CT data, wherein the third material of interest is different from the first and second materials of interest. It further possesses, The step of normalizing the Haunsfield unit scale for the first and second materials across the CT data is: A step of determining whether the difference between the HU value for the third material of interest and the HU value for the first material of interest is non-zero across the plurality of CT images, In response to determining that the difference is not non-zero across the plurality of CT images, the steps include adjusting the Hounsfield unit scale for the first material of interest so that the difference between the HU value for the third material of interest and the HU for the first material of interest is non-zero across the plurality of CT images, Having, The method according to any one of claims 1 to 3.

5. The step of adjusting the Houndsfield unit scale is: The following formula, HUadj α,β = -T・(μ-max(μ β ,m α )) / (max(μ β ,m α )-min(μ β ,m α )) A step of adjusting the local attenuation value μ by It has, Here, T is the target value, and μ α μ is the local attenuation value for the first material, and β This is local damping for the second material, The method according to claim 4.

6. The method according to any one of claims 1 to 5, wherein the plurality of CT images include a plurality of single-energy spectral images.

7. A computer program having computer program code means configured to perform the method described in any one of claims 1 to 6 when executed on a computer.

8. In a system that processes CT data, A control unit configured to identify first and second materials of interest in CT data of multiple CT images, wherein at least one of the first and second materials of interest is neither air nor water, and the control unit and A data processor configuration configured to normalize the Hounsfield unit scale across the entire CT data for the first and second materials of interest such that the HU values ​​for each of the first and second materials of interest are substantially constant across the plurality of CT images, wherein the normalization step is: The following formula, HU α,β = -T・(μ-μ β ) / (μ β -μ α ) A step of adjusting the local attenuation value μ by It has, Here, T is the target value, and μ α μ is the local attenuation value for the first material, and β This is local damping for the second material, system.

9. The system according to claim 8, wherein the first or second material of interest is one of iodine, bone, bone marrow, fat, iron, calcium, brain white matter, brain gray matter, gadolinium, gold, oxygen, xenon, neon, blood, uric acid, NaCl, or a combination thereof.

10. The aforementioned data processor configuration is: Adjust the Hounsfield unit scale for the first material of interest across the entire CT data so that the HU value for the first material of interest across the plurality of CT images is substantially equal to zero. The system according to claim 8 or 9, configured as follows.

11. The control unit is further configured to identify a third material of interest to the CT data, wherein the third material of interest differs from the first and second materials of interest. The aforementioned data processor configuration is: Determine whether the difference between the HU value for the third material of interest and the HU value for the first material of interest is non-zero across the multiple CT images. In response to determining that the difference is not non-zero across the plurality of CT images, the Hounsfield unit scale is adjusted for the first material of interest such that the difference between the HU value for the third material of interest and the HU for the first material of interest is non-zero across the plurality of CT images. It is configured in such a way. The system according to any one of claims 8 to 10.

12. Adjusting the aforementioned Houndsfield unit scale The following formula, HUadj α,β = -T・(μ-max(μ β ,m α )) / (max(μ β ,m α )-min(μ β ,m α )) By adjusting the local attenuation value μ, Includes, Here, T is the target value, and μ α μ is the local attenuation value for the first material, and β This is local damping for the second material, The system according to claim 8 or 9.

13. The system according to any one of claims 8 to 12, wherein the plurality of CT images include a plurality of single-energy spectral images.

Images