Spectral remediation of contrast-enhanced ct examinations

Abstract

To improve contrast-enhanced CT examinations, an image quality assurance device (10) is provided. The image quality assurance device (10) comprises an input unit (12), a processing unit (14), and an output unit (16). The input unit is configured to receive image data acquired by a spectral computed tomography (CT) scanner. The processing unit is configured to perform an analysis of contrast enhancement in a region of interest in the acquired image data and to compare the contrast enhancement of the region of interest to a desired contrast enhancement defined by an examination protocol to determine whether the contrast enhancement of the region of interest is sufficient. In response to determining that the contrast enhancement of the region of interest is not sufficient, the processing unit is configured to generate a trigger signal configured to trigger the spectral CT scanner to derive spectral data. The output unit is configured to output the generated trigger signal.

Description

Technical Field

[0001] This invention relates to contrast-enhanced computed tomography (CT) examination. In particular, this invention relates to image quality assurance equipment, imaging systems, image quality assurance methods, computer program products, and computer-readable media. Background Technology

[0002] Contrast-enhanced CT accounts for approximately 50% of all CT acquisitions. In contrast-enhanced CT, contrast materials (also known as contrast agents or contrast media) are used to enhance the diagnostic value of those imaging studies. Iodine- and barium sulfate-based compounds are commonly used in X-ray and CT imaging. When iodine- and barium sulfate-based contrast materials are present in specific areas of the body, they block or limit the penetrating power of X-rays. Therefore, the appearance of blood vessels, organs, and other body tissues temporarily containing iodine- or barium-based compounds will change on X-ray or CT images. Contrast-enhanced CT is more complex in clinical workflows due to the additional steps required and the complex scanning parameters to be considered. Depending on the clinical problem and the target anatomy, iodine needs to be placed in specific locations in the patient's tissues or blood vessels to produce the desired enhancement and subsequently allow for a reliable diagnosis. Modern spectral CT systems record radiation at two energy levels and have the ability to retrospectively partition the detected radiation into various energy bins. This allows for so-called monoenergetic reconstruction at lower energy levels, resulting in a stronger iodine contrast enhancement. In routine clinical practice, this allows for the use of smaller amounts of contrast agent when performing spectral acquisitions.

[0003] Unfortunately, even though the scanners have energy spectrum capabilities, many of the scans performed on those machines are not configured to record energy spectrum information and imaging data together, which essentially discards the ability to reconstruct monoenergetic images. Summary of the Invention

[0004] Improved contrast-enhanced CT scans may be necessary.

[0005] The objective of this invention is achieved through the subject matter of the independent claims, wherein further embodiments are incorporated in the dependent claims. It should be noted that the various aspects of the invention described below are also applicable to image quality assurance devices, imaging systems, image quality assurance methods, computer program products, and computer-readable media.

[0006] According to a first aspect of the present invention, an image quality assurance apparatus is provided. The image quality assurance apparatus includes an input unit, a processing unit, and an output unit. The input unit is configured to receive image data acquired by an energy-spectrum CT scanner. The processing unit is configured to: perform analysis of contrast enhancement in a region of interest (ROI) in the acquired image data, and compare the contrast enhancement of the ROI with a desired contrast enhancement defined by an inspection protocol to determine whether the contrast enhancement of the ROI is sufficient. In response to determining that the contrast enhancement of the ROI is insufficient, the processing unit is configured to generate a trigger signal configured to trigger the energy-spectrum CT scanner to export energy-spectrum data. The output unit is configured to output the generated trigger signal.

[0007] In other words, an image quality assurance device is provided that performs analysis of contrast enhancements in routine scans given imaging data and clinical instructions. Upon detecting suboptimal contrast enhancement, the image quality assurance device triggers the additional export of spectral data to a data repository (e.g., a Picture Archiving and Communication System (PACS)). Notifications (e.g., alerts) can be created for users (e.g., radiologists) to read the additional images for a better diagnosis. The proposed image quality assurance device allows routine CT acquisitions to be performed on spectral systems and spectral data to be stored only retrospectively, thereby enabling more reliable diagnosis of clinical problems. This will be discussed below and particularly regarding... Figure 2 The embodiments shown are described in detail below.

[0008] According to an exemplary embodiment of the first aspect of the present invention, in response to determining that the contrast enhancement of the region of interest is insufficient, the processing unit is further configured to generate a notification indicating that the contrast enhancement of the target anatomical structure is insufficient.

[0009] For example, notifications can provide visual and / or auditory cues in the form of LEDs, messages on displays, and / or sounds.

[0010] According to an exemplary embodiment of the first aspect of the invention, the notification further includes one or more of the following information: a recommended reconstruction level that produces sufficient contrast enhancement, and a quantization result of the contrast enhancement of the determined region of interest.

[0011] Therefore, such a notification may include additional information, such as recommended reconstructed energy levels that produce improved enhancement modes and / or quantification results of the measured enhancements.

[0012] According to an exemplary embodiment of the first aspect of the present invention, the processing unit is further configured to reconstruct an improved diagnostic image using the acquired image data and energy spectrum data.

[0013] Therefore, information from both conventional and spectral data can be used to reconstruct improved diagnostic images, which can then be stored in a data repository along with the conventional images for later retrieval.

[0014] According to an exemplary embodiment of the first aspect of the present invention, the processing unit is configured to perform an image segmentation operation on the acquired image data to determine the region of interest.

[0015] According to an exemplary embodiment of the first aspect of the invention, contrast enhancement includes an enhancement mode for the region of interest, wherein the enhancement mode is the distribution of contrast enhancement in two or more anatomical structures, spatial regions and / or the distribution over time.

[0016] According to an exemplary embodiment of the first aspect of the invention, the region of interest includes regions that are expected to be enhanced and / or regions that are expected to remain unenhanced.

[0017] Figure 3 An exemplary imaging volume is schematically illustrated, showing areas that are expected to be enhanced (e.g., target anatomical structures) and areas that are expected to remain unenhanced (e.g., background).

[0018] According to an exemplary embodiment of the first aspect of the present invention, the energy spectrum data is in the form of an energy spectrum basis image (SBI).

[0019] According to a second aspect of the invention, a CT imaging system is provided, the CT imaging system comprising an energy-spectral CT scanner configured to acquire image data of an object, and an imaging quality assurance device according to the first aspect and any related examples.

[0020] This will be discussed below, and specifically regarding... Figure 1 The embodiments shown are described in detail below.

[0021] According to a third aspect of the present invention, an image quality assurance method is provided, the image quality assurance method comprising: a) The processor receives image data acquired by the energy-spectrum computed tomography (CT) scanner; b) The processor performs contrast enhancement analysis on the regions of interest in the acquired image data; c) The processor compares the contrast enhancement of the region of interest with the expected contrast enhancement defined by the inspection protocol to determine whether the contrast enhancement of the region of interest is sufficient; and d) In response to insufficient contrast enhancement in the region of interest, a trigger signal is generated by the processor, which is configured to trigger the energy spectrum CT scanner to export energy spectrum data.

[0022] This will be discussed below, and specifically regarding... Figure 4 The embodiments shown are described in detail below.

[0023] According to an exemplary embodiment of the third aspect of the present invention, the image quality assurance method further includes the step of: generating a notification indicating insufficient contrast enhancement of the target anatomical structure in response to determining that the contrast enhancement of the region of interest is insufficient.

[0024] According to an exemplary embodiment of the third aspect of the present invention, the notification includes one or more of the following: a recommended reconstruction level that produces sufficient contrast enhancement, and a quantization result of the contrast enhancement of the determined region of interest.

[0025] According to an exemplary embodiment of the third aspect of the present invention, the image quality assurance method further includes the step of reconstructing an improved diagnostic image using the acquired image data and energy spectrum data.

[0026] According to another aspect of the present invention, a computer program product including instructions is provided, which, when executed by a processor, cause the processor to perform the steps of a method of a first aspect of a related example.

[0027] According to another aspect of the invention, a computer-readable medium having a computer program product stored thereon is provided.

[0028] As used herein, the term "unit" may refer to, be part of, or include the following items: application-specific integrated circuits (ASICs), electronic circuits, (shared, dedicated, or grouped) processors and / or (shared, dedicated, or grouped) memories that execute one or more software or firmware programs, combinational logic circuits, and / or other suitable components that provide the described functionality. Attached Figure Description

[0029] These and other aspects of the invention will become apparent and further elucidated from the embodiments described by way of example in the following description and with reference to the accompanying drawings, in which: Figure 1 An exemplary imaging system is schematically illustrated.

[0030] Figure 2 An exemplary image quality assurance device is schematically illustrated.

[0031] Figure 3 An exemplary imaging volume is schematically illustrated.

[0032] Figure 4 An exemplary image quality assurance method is illustrated.

[0033] It should be noted that the accompanying drawings are purely schematic and not drawn to scale. In the drawings, elements corresponding to those already described may have the same reference numerals. Examples, embodiments, or optional features, whether or not they are indicated as non-limiting, should not be construed as limiting the claimed invention. Detailed Implementation

[0034] Figure 1 An exemplary imaging system 200 is illustrated, which includes a spectral CT scanner 100 configured to acquire image data of an object (e.g., a person or animal). Figure 1 In the example shown, the spectral CT scanner 100 includes a fixed gantry 102 and a rotating gantry 104, the rotating gantry 104 being rotatably supported by the fixed gantry 102. The rotating gantry 104 rotates about the examination area 106 about the longitudinal axis or z-axis.

[0035] The spectral CT scanner 100 includes at least one radiation source 108 (e.g., an X-ray tube) supported by a rotating gantry 104 and rotating with the gantry 104 around an examination area 106. At least one radiation source 108 emits radiation through the examination area 106. If two or more radiation sources 108 are present, each source can be configured to emit radiation with a different average emission spectrum. Additionally or alternatively, one or more of the at least two sources 108 can be configured to controllably switch between at least two different emission voltages (kVp) during scanning of multiple sources, and / or kVp switching can be used for spectral CT acquisition.

[0036] The spectral CT scanner 100 also includes a radiation-sensitive detector array 110 located opposite at least one radiation source 108 across an examination region 106. The radiation-sensitive detector array 110 may include an array of detector pixels that detect radiation passing through the examination region 106 and generate projection data indicating that radiation. In some examples, the radiation-sensitive detector array 110 may include an energy-resolved detector, such as a direct conversion detector and / or a scintillator-based multispectral detector comprising at least two scintillators with different X-ray energy sensitivities, each optically attached to at least two photosensors (e.g., a stacked detector or a dual-layer detector) with corresponding optical sensitivities. The energy-resolved detector can be used for spectral CT acquisition. In some examples, the radiation-sensitive detector array 110 may include photon-counting detector pixels (e.g., CdTe, CdZnTe, etc.). The photon-counting detector pixels are configured to acquire the spectral properties of the X-ray source rather than the energy integral properties in the acquired data. In order to obtain the energy spectrum properties of transmitted X-ray data, the photocounting detector pixels divide the X-ray beam into its component energy bins or energy spectrum bins and count the number of photons in each bin.

[0037] The spectral CT scanner 100 may also include an object support 112 (e.g., a bed) to support an object (e.g., a person or animal) or target in the examination area 106 and may be used to position the object relative to the x-axis, y-axis and / or z-axis and the examination area 106 before, during and / or after the scan.

[0038] The imaging system 200 may also include a reconstructor 114 to reconstruct projection data and generate volumetric image data indicating the inspection area 106 and portions therein of a target or object. When energy spectrum data is acquired, the reconstructor 112 may reconstruct individual energy spectrum images for each energy range in different energy ranges and / or reconstruct combined images based on individual energy spectrum images corresponding to two or more energy ranges in different energy ranges. The reconstructor 114 may also employ conventional non-spectral reconstruction algorithms.

[0039] The imaging system 200 may also include an operator console 116, which may include output devices (e.g., a monitor) and input devices (e.g., a keyboard, a mouse). Software residing on the console 116 may allow the operator to control the operation of the spectral CT scanner 100, thereby allowing the operator to select a spectral imaging protocol, initiate a scan, etc.

[0040] Data repository 118 can be used to store reconstructed images and can be accessed by one or more of console 116 and / or other devices. Data repository 118 can be local to imaging system 200, remote from imaging system 200, distributed, etc. Data repository 118 may include databases, servers, PACS, Radiology Information System (RIS), Hospital Information System (HIS), Electronic Medical Record (EMR), and / or other electronic storage devices or memories.

[0041] As mentioned above, contrast-enhanced CT scans allow for the use of a smaller amount of contrast agent when performing spectral acquisition. Unfortunately, even when scanners have spectral capabilities, many scans performed on those machines are not configured to record spectral information and imaging data together, which essentially discards the ability to reconstruct monoenergetic images.

[0042] To address the aforementioned problems, an image quality assurance device 10 is provided. For example... Figure 1 As shown, the image quality assurance device 10 is configured to receive image data acquired by the spectral CT scanner 100 via a wired or wireless connection (including USB, Ethernet, Bluetooth, Wi-Fi, etc.). The image quality assurance device 10 is configured to perform an analysis of contrast enhancement in regions of interest (ROIs) within the acquired image data, and to compare the contrast enhancement of the ROIs with the expected contrast enhancement defined by an examination protocol to determine whether the contrast enhancement of the ROIs is sufficient. In response to determining that the contrast enhancement of the ROIs is insufficient, the image quality assurance device 10 is configured to generate a trigger signal and output the generated trigger signal to the spectral CT scanner 100 via a wired or wireless connection (including USB, Ethernet, Bluetooth, Wi-Fi, etc.). The trigger signal is configured to trigger the spectral CT scanner to export spectral data (e.g., in the form of a spectral base image (SBI)). Therefore, the image quality assurance device 10 allows routine CT acquisition to be performed on a spectral system, and the spectral data (e.g., in the form of SBI) is stored or saved only retrospectively, thereby enabling more reliable diagnosis of clinical problems. In the contrast example, image quality assurance device 10 can analyze “routine” acquired imaging data to enhance contrast in desired anatomical structures (e.g., tissue / blood vessels). If the module detects low enhancement, spectral data is reconstructed and stored in a data repository 118 (e.g., PACS) along with the routine imaging results. Therefore, when reviewing images, a user (e.g., a radiologist) can choose to use the spectral information to reconstruct additional monoenergetic images with brighter enhancement characteristics. While Figure 1The image quality assurance device 10 may be shown as a standalone device, but it should be understood that in another embodiment, the image quality assurance device 10 may be implemented as or in other devices (e.g. via console 116), such as as software residing on console 116.

[0043] Figure 2 An example of an image quality assurance device 10 is illustrated. For example... Figure 2 As shown, the image quality assurance device 10 includes an input unit 12, a processing unit 14, and an output unit 16.

[0044] Generally, the image quality assurance device 10 may include various physical and / or logical components for communicating and manipulating information. These physical and / or logical components may be implemented as hardware components (e.g., computing devices, processors, logic devices), executable computer program instructions (e.g., firmware, software) to be executed by the various hardware components, or any combination thereof, as desired for a given set of design parameters or performance constraints. Although Figure 2 A limited number of components may be shown by way of example, but it will be understood that for a given implementation, more or fewer components may be used.

[0045] In some implementations, the image quality assurance device 10 may be embodied as a device or apparatus (e.g., a server, workstation, or mobile device), or may be embodied within a device or apparatus (e.g., a server, workstation, or mobile device). Apparatus 10 may include one or more microprocessors or computer processors executing appropriate software. The processing unit 14 of the image quality assurance device 10 may be embodied by one or more of these processors. The software may have been downloaded and / or stored in a corresponding memory, such as volatile memory (e.g., RAM) or non-volatile memory (e.g., flash memory). The software may include instructions that configure one or more processors to perform the functions described herein.

[0046] It should be noted that the image quality assurance device 10 can be implemented with or without a processor, and can also be implemented as a combination of dedicated hardware performing some functions and a processor (e.g., one or more programmed microprocessors and associated circuitry) performing other functions. For example, the functional units of the image quality assurance device 10 (e.g., input unit 12, one or more processing units 14, and output unit 16) can be implemented in a device or apparatus in the form of programmable logic devices (e.g., in the form of a field-programmable gate array (FPGA)). Generally, each functional unit of the apparatus can be implemented in the form of a circuit.

[0047] In some implementations, the image quality assurance device 10 may also be implemented in a distributed manner. For example, some or all of the units of the device 10 may be arranged as independent modules in a distributed architecture and connected to a suitable communication network (e.g., 3GPP network, LTE network, Internet, LAN, wireless LAN, WAN, etc.).

[0048] Input unit 12 is configured to receive image data acquired by spectral CT scanner 100. Input unit 12 may be implemented as a wired interface (e.g., Ethernet interface or USB interface) or a wireless interface (e.g., Wi-Fi, Bluetooth) or any similar interface (e.g., 3GPP network interface, LTE network interface, etc.) that enables data transmission between spectral CT scanner 100 and image quality assurance device 10.

[0049] Processing unit 14 is configured to: perform analysis of contrast enhancement in regions of interest (ROIs) within the acquired image data, and compare the contrast enhancement of the ROIs with the expected contrast enhancement defined by an inspection protocol to determine whether the contrast enhancement of the ROIs is sufficient. The intensity of the contrast enhancement can be measured in Heinz units (HUs), and the intensity of the contrast enhancement can be compared with the expected contrast enhancement defined by the inspection protocol. It should be noted that the ROI may include regions expected to be enhanced, such as... Figure 3 The target anatomical structure shown can be a blood vessel, organ, pathological tissue (e.g., tumor), etc. The region of interest may alternatively or additionally include areas expected to remain unenhanced, such as... Figure 3 The background area shown.

[0050] In some implementations, processing unit 14 may be configured to perform image segmentation operations on the acquired image data to determine regions of interest. In some examples, processing unit 14 may apply a graph-based method for automatic segmentation. Graph-based methods use image registration to propagate predefined structural contours to the image to be segmented. In some examples, processing unit 14 may apply a model-based method that utilizes a statistical shape model for automatic segmentation. In some examples, processing unit 14 may apply a deep learning-based medical image segmentation method. Examples of deep learning-based medical image segmentation methods may include, but are not limited to, convolutional neural networks (CNNs), U-Net, Mask R-CNN, RefineNet, and DeconvNet. Figure 3An example of a target anatomical structure 30 (e.g., blood vessel, organ) segmented from the imaging volume in the acquired image data 20 is illustrated. Contrast enhancement analysis can be performed in the region where enhancement is expected (e.g., target anatomical structure 30) and / or in the region where it is expected to remain unenhanced (e.g., background 40).

[0051] Depending on the desired enhancement, different types of contrast enhancement exist. For example, in angiography, the target anatomical structure is the blood in the vessels. Ideally, the scan is performed relatively quickly after injection to allow the contrast agent to reach the target area without “leaking” into the surrounding tissue and enhancing the “background.” Because timing is critical in these applications, missing the ideal acquisition window can result in insufficient contrast agent in the region of interest. For other applications, the desired effect is that the contrast agent saturates the entire target anatomical structure. In those cases, there is often a longer scan delay, and the effects of missing the timing are more evident in areas of uneven enhancement. Therefore, contrast enhancement can include an enhancement pattern in the region of interest. The enhancement pattern can include the distribution of contrast enhancement across two or more anatomical and / or spatial regions. Alternatively or additionally, the enhancement pattern can include the distribution of contrast enhancement over time, such as the dynamic enhancement pattern of intrahepatic cholangiocarcinoma in cirrhosis. Thus, in some embodiments, the processing unit 14 can be configured to measure the actual enhancement pattern (which may depend on timing and organ) in the segmented region of interest and compare that enhancement pattern with the desired enhancement pattern defined by the examination protocol.

[0052] Back Figure 2 In response to insufficient contrast enhancement in the determined region of interest, processing unit 14 is configured to generate a trigger signal and provide the trigger signal to the spectral CT scanner 100 via output unit 16. Output unit 16 may be implemented as a wired interface (e.g., Ethernet or USB interface) or a wireless interface (e.g., Wi-Fi, Bluetooth) or any similar interface (e.g., 3GPP network interface, LTE network interface, etc.) enabling data transfer between the spectral CT scanner 100 and the image quality assurance device 10. The trigger signal is used to trigger the spectral CT scanner to export spectral data (e.g., SBI spectral information). Therefore, as... Figure 1 As shown, in the event of insufficient contrast enhancement (e.g., insufficient contrast enhancement mode), the image quality assurance device 10 generates a trigger signal that triggers the additional export of spectral data (e.g., SBI spectral information) from the spectral CT scanner 100 to the data repository 118 (e.g., PACS).

[0053] In addition to exporting spectral data, the processing unit 14 of the image quality assurance device 10 can also be configured to generate notifications for radiologists to read additional available images for better diagnosis. The notifications can provide visual and / or auditory instructions in the form of, for example, LEDs, messages on a display, and / or sound. For example, the notification can be displayed on a display 120, which may be the display of the operator console 116. In this way, radiologists can read images with greater confidence and mitigate the effects of insufficient contrast enhancement. Such notifications can include additional information, such as recommended reconstruction levels that produce sufficient contrast enhancement, and / or quantification results of the contrast enhancement for the identified region of interest.

[0054] In some implementations, information from both conventional and energy dispersive spectroscopy (EDS) data can be used to reconstruct an improved diagnostic image, which can be stored alongside the conventional image in a data repository 118 (e.g., a PACS) for retrieval. Image reconstruction can be performed by... Figure 1 The reconstruction is performed by the reconstruction unit 14 or the image quality assurance device 10 shown.

[0055] Figure 4 The illustration shows a flowchart describing an exemplary image quality assurance method 300.

[0056] At box 310 (i.e., step a), method 300 includes the step of receiving image data acquired by an energy-spectrum CT scanner. For example, as Figure 1 As shown, the image quality assurance device 10 can receive image data acquired by the energy spectrum CT scanner 100 via wired or wireless connections (including USB, Ethernet, Bluetooth, Wi-Fi, etc.).

[0057] At box 320 (i.e., step b), method 300 includes the step of performing an analysis of contrast enhancement in a region of interest in the acquired image data. The intensity of the contrast enhancement can be measured in HU values.

[0058] In some examples, the region of interest (ROI) may include areas expected to be enhanced, such as target anatomical structures (e.g., blood vessels and organs). In some examples, the ROI may include areas expected to remain unenhanced (e.g., the background within the imaging volume). Areas expected to remain unenhanced may alternatively or additionally include other anatomical structures. For example, in angiography, blood vessels are expected to be enhanced, but contrast agent should not leak into the surrounding soft tissue. In this example, the surrounding soft tissue could be considered an area expected to remain unenhanced. In some examples, the ROI may include both areas expected to be enhanced and areas expected to remain unenhanced. Various techniques, such as atlas-based automatic segmentation methods, model-based segmentation methods, and deep learning-based medical image segmentation methods, can be used to segment the desired ROI from the imaging volume.

[0059] In some examples, the actual enhancement pattern can be measured within a segmented region of interest. The enhancement pattern can include the distribution of contrast enhancement across two or more anatomical structures, spatial regions, and / or the distribution of contrast enhancement over time. As an example, the enhancement pattern can include the distribution of contrast enhancement determined by comparing two images acquired from pre-contrast and post-contrast scans.

[0060] At box 330 (i.e., step c), method 300 further includes a step of comparing the contrast enhancement of the region of interest with the expected contrast enhancement defined by the inspection protocol to determine whether the contrast enhancement of the region of interest is sufficient.

[0061] For example, the intensity of contrast enhancement can be measured using the HU value, and the measured intensity of contrast enhancement can be compared with the expected contrast enhancement defined by the inspection protocol to determine whether the contrast enhancement of the region of interest is sufficient.

[0062] If insufficient contrast enhancement is determined (e.g., insufficient enhancement mode), step d) is performed at box 340. At box 340, a trigger signal is generated, which is configured to trigger the spectral CT scanner to export spectral data (e.g., SBI spectral information).

[0063] In addition to the step of generating a trigger signal, method 300 may also include a step of generating a notification indicating insufficient contrast enhancement of the target anatomical structure. The notification may additionally include a recommended reconstruction energy level that produces sufficient contrast enhancement and / or a quantization result of the contrast enhancement of the identified region of interest.

[0064] In some examples, method 300 may also include the step of reconstructing an improved diagnostic image using the acquired image data and energy spectrum data.

[0065] In another exemplary embodiment of the present invention, a computer program or computer program unit is provided, characterized in that it is adapted to perform the method steps of the method according to one of the foregoing embodiments on a suitable system.

[0066] Therefore, a computer program unit may be stored on a computer unit, which may also be part of an embodiment of the present invention. The computing unit may be adapted to perform or cause the execution of the steps of the described methods. Furthermore, the computing unit may be adapted to operate components of the described apparatus. The computing unit may be adapted to automatically operate and / or execute user commands. The computer program may be loaded into the working memory of a data processor. Therefore, a data processor may be configured to perform the methods of the present invention.

[0067] This exemplary embodiment of the invention covers both computer programs that use the invention from the outset and computer programs that convert existing programs into programs that use the invention through updates.

[0068] Furthermore, the computer program unit may be able to provide all the necessary steps to implement the exemplary embodiments of the method described above.

[0069] According to another exemplary embodiment of the present invention, a computer-readable medium (e.g., CD-ROM) is provided, wherein the computer-readable medium has a computer program unit stored thereon, which has been described in the preceding sections.

[0070] Computer programs can be stored and / or distributed on suitable media, such as optical storage media or solid-state media supplied together with or as part of other hardware, but can also be distributed in other forms, such as via the Internet or other wired or wireless telecommunications systems.

[0071] However, computer programs can also be presented via networks such as the World Wide Web, and can be downloaded from such networks to the working memory of a data processor. According to another exemplary embodiment of the invention, a medium is provided for making a computer program unit available for download, the computer program unit being arranged to perform the method described in one of the foregoing embodiments of the invention.

[0072] It should be noted that embodiments of the present invention are described with reference to different subjects. In particular, some embodiments are described with reference to method claims, while others are described with reference to apparatus claims. However, those skilled in the art will understand from the above and below description that, unless otherwise stated, any combination of features relating to different subjects is also considered to be disclosed in this application, except for any combination of features belonging to one type of subject. However, all features can be combined together to provide synergistic effects beyond the simple addition of features.

[0073] Although the invention has been illustrated and described in detail in the accompanying drawings and the foregoing description, such illustrations and descriptions are to be considered illustrative or exemplary rather than limiting. The invention is not limited to the disclosed embodiments. Other variations of the disclosed embodiments will be understood and implemented by those skilled in the art in practicing the claimed invention by studying the drawings, the disclosure, and the appended claims.

[0074] In the claims, the word "comprising" does not exclude other elements or steps, and the quantifiers "a" or "an" do not exclude a plurality. A single processor or other unit may perform the functions of several items recited in the claims. The mere fact that certain measures are recited in dissimilar dependent claims does not indicate that combinations of these measures cannot be advantageously used. No reference numerals in the claims should be construed as limiting the scope.

Claims

1. An image quality assurance device (10), comprising: Input unit (12); Processing unit (14); as well as Output unit (16); The input unit is configured to receive image data acquired by an energy-dispersive computed tomography (EDT) scanner. The processing unit is configured to: perform analysis of contrast enhancement in regions of interest in the acquired image data, and compare the contrast enhancement in the regions of interest with the expected contrast enhancement defined by an inspection protocol to determine whether the contrast enhancement in the regions of interest is sufficient; In response to determining that the contrast enhancement of the region of interest is insufficient, the processing unit is configured to generate a trigger signal, which is configured to trigger the energy-dispersive CT scanner to export energy-dispersive spectral data; and The output unit is configured to output the generated trigger signal.

2. The image quality assurance device according to claim 1, in, In response to determining that the contrast enhancement of the region of interest is insufficient, the processing unit is also configured to generate a notification indicating the insufficient contrast enhancement of the target anatomical structure.

3. The image quality assurance device according to claim 2, in, The notification may also include one or more of the following information: Recommended reconstruction energy levels to produce sufficient contrast enhancement; and Quantification results of contrast enhancement for the identified region of interest.

4. The image quality assurance device according to any one of the preceding claims, in, The processing unit is also configured to reconstruct an improved diagnostic image using the acquired image data and the energy spectrum data.

5. The image quality assurance device according to any one of the preceding claims, in, The processing unit is configured to perform image segmentation operations on the acquired image data to determine the region of interest.

6. The image quality assurance device according to any one of the preceding claims, in, The contrast enhancement includes an enhancement mode for the region of interest, wherein the enhancement mode includes the distribution of the contrast enhancement in two or more anatomical structures, spatial regions and / or the distribution over time.

7. The image quality assurance device according to any one of the preceding claims, in, The region of interest includes regions that are expected to be enhanced and / or regions that are expected to remain unenhanced.

8. The image quality assurance device according to any one of the preceding claims, in, The energy spectrum data is in the form of a basic energy spectrum image (SBI).

9. An imaging system (100), comprising: A spectrum computed tomography (CT) scanner (100) is configured to acquire image data of an object; as well as The imaging quality assurance device (10) according to any one of the preceding claims.

10. An image quality assurance method (300), comprising: a) The processor receives (310) image data acquired by the energy spectrum computed tomography (CT) scanner; b) The processor performs (320) an analysis of contrast enhancement in the regions of interest in the acquired image data; c) The processor compares the contrast enhancement of the region of interest with the expected contrast enhancement defined by the inspection protocol (330) to determine whether the contrast enhancement of the region of interest is sufficient; as well as d) In response to determining that the contrast enhancement of the region of interest is insufficient, the processor generates a (340) trigger signal configured to trigger the spectral CT scanner to export spectral data SBI.

11. The image quality assurance method according to claim 10, further comprising: In response to determining that the contrast enhancement of the region of interest is insufficient, a notification indicating the insufficient contrast enhancement of the target anatomical structure is generated.

12. The image quality assurance method according to claim 11, in, The notification includes one or more of the following information: Recommended reconstruction energy levels to produce sufficient contrast enhancement; and Quantification results of contrast enhancement for the identified region of interest.

13. The image quality assurance method according to any one of claims 10 to 12, further comprising: An improved diagnostic image is reconstructed using the acquired image data and the energy spectrum data.

14. A computer program product comprising instructions that, when executed by a processor, cause the processor to perform the steps of the method according to any one of claims 10 to 13.

15. A computer-readable medium having thereon a computer program product according to claim 14.

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