CN113100803A - Method, apparatus, computer device and medium for displaying venous thrombosis - Google Patents

Method, apparatus, computer device and medium for displaying venous thrombosis Download PDF

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CN113100803A
CN113100803A CN202110426162.1A CN202110426162A CN113100803A CN 113100803 A CN113100803 A CN 113100803A CN 202110426162 A CN202110426162 A CN 202110426162A CN 113100803 A CN113100803 A CN 113100803A
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赵喜
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Siemens Digital Medical Technology Shanghai Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/02—Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computerised tomographs
    • A61B6/032—Transmission computed tomography [CT]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/48—Diagnostic techniques
    • A61B6/482—Diagnostic techniques involving multiple energy imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/50—Clinical applications
    • A61B6/504—Clinical applications involving diagnosis of blood vessels, e.g. by angiography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5205—Devices using data or image processing specially adapted for radiation diagnosis involving processing of raw data to produce diagnostic data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]

Abstract

The present disclosure provides a method, an apparatus, a computer device, a readable storage medium and a computer program product for displaying venous thrombosis. The method for displaying venous thrombosis of the present disclosure includes: acquiring dual-energy CT flat scanning data of a measured object, wherein the measured object comprises a plurality of voxels; based on a three-material decomposition algorithm, transforming the dual-energy CT flat scan data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scan data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; and generating a venous thrombosis area for identifying the measured object according to the difference degree of each voxel and the first base material.

Description

Method, apparatus, computer device and medium for displaying venous thrombosis
Technical Field
The present disclosure relates to the field of medical imaging and medical image processing technology, and in particular, to a method, an apparatus, a computer device, a readable storage medium, and a computer program product for displaying venous thrombosis.
Background
Venous Thrombosis (VT), also known as Venous Thrombosis, refers to thrombophlebitis and secondary Thrombosis caused by Venous blood flow blockage, hypercoagulability, intimal injury, etc.
At present, blood vessel imaging is generally performed by using Computer Tomography (CT) containing a Contrast Medium (also called Contrast Medium), i.e., enhanced CT, to identify venous thrombosis. Iodine-containing contrast agents are currently the most commonly used contrast agents. Despite its high safety factor, it may cause damage to the human body, such as causing allergies or injury to renal function. Furthermore, depending on the different periods of contrast agent development, it is often necessary to perform multiple CT scans on the patient, which subjects the patient to a large radiation dose, which is detrimental to the patient's health.
Disclosure of Invention
In view of this, the present disclosure proposes a method, an apparatus, a computer device, a readable storage medium and a computer program product for displaying a venous thrombus.
According to a first aspect of the present disclosure, there is provided a method for visualizing venous thrombosis, comprising: acquiring dual-energy CT (computed tomography) flat scan data of a measured object, wherein the measured object comprises a plurality of voxels; based on a three-material decomposition algorithm, transforming the dual-energy CT flat scan data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scan data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; and generating an image for identifying the venous thrombosis area of the measured object according to the difference degree of each voxel and the first base material.
According to a second aspect of the present disclosure, there is provided an apparatus for displaying venous thrombosis, comprising: a tomographic unit configured to acquire dual energy CT scan data of a measured object, the measured object including a plurality of voxels; a computing unit configured to: acquiring collected dual-energy CT flat scanning data; based on a three-material decomposition algorithm, transforming the dual-energy CT flat scan data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scan data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; generating an image for identifying a venous thrombus area of the measured object according to the difference degree of each voxel and the first base material; and a display unit configured to display the image.
According to a third aspect of the present disclosure, there is provided a computer device comprising: a memory, a processor, and a computer program stored on the memory. The processor is configured to execute the computer program as described above to implement the steps of the method for displaying venous thrombosis as described above.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having a computer program stored thereon. The computer program realizes the above-mentioned steps of the method for displaying a venous thrombus when being executed by a processor.
According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program. The computer program realizes the above-mentioned steps of the method for displaying a venous thrombus when being executed by a processor.
According to one or more embodiments of the present disclosure, dual-energy CT scan data is transformed onto a scale based on first and second basis material configurations based on a three-material decomposition algorithm, resulting in enhanced data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; and generating an image for identifying the venous thrombosis area according to the difference degree of each voxel and the first base material. According to the embodiment of the disclosure, the difference degree between different voxels is increased by converting the dual-energy CT flat scan data into the enhanced data on the scale, so that the difference degree between the voxels corresponding to the venous thrombosis and the voxels corresponding to the normal blood is increased, the contrast between the venous thrombosis region and the normal blood region in the generated image is more obvious, and the venous thrombosis region can be accurately identified. The venous thrombosis area can be accurately identified only by acquiring the dual-energy CT (computed tomography) flat scan data of the measured object without using a contrast medium, so that adverse reactions of a patient caused by using the contrast medium are avoided; the patient does not need to be scanned for multiple times, so that radiation damage to the patient is reduced.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
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The above and other features and advantages of the present disclosure will become more apparent to those of ordinary skill in the art by describing in detail embodiments thereof with reference to the attached drawings, in which:
FIG. 1 is a flow chart of a method for displaying venous thrombosis in accordance with an embodiment of the present disclosure;
FIG. 2 is a schematic illustration of dual energy CT flat scan data according to an embodiment of the present disclosure;
FIG. 3 shows a schematic diagram of CT values of different substances according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of an exemplary attenuation profile according to an embodiment of the present disclosure;
fig. 5A to 5C are schematic diagrams respectively illustrating the display effects of a single-energy CT flat scan, a dual-energy CT flat scan, and a single-energy CT enhancement on a venous thrombus region according to an embodiment of the present disclosure;
FIG. 6 shows a schematic view of an apparatus for displaying venous thrombosis in accordance with an embodiment of the present disclosure; and
FIG. 7 illustrates a block diagram of an exemplary computer device that can be used to implement embodiments of the present disclosure.
Detailed Description
For a more clear understanding of the technical features, objects, and effects of the present disclosure, embodiments of the present disclosure will now be described with reference to the accompanying drawings, in which like reference numerals refer to like parts throughout.
"exemplary" means "serving as an example, instance, or illustration" herein, and any illustration, embodiment, or steps described as "exemplary" herein should not be construed as a preferred or advantageous alternative.
For the sake of simplicity, only the parts relevant to the present disclosure are schematically shown in the drawings, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled.
In this document, "one" means not only "only one" but also a case of "more than one". In this document, "first", "second", and the like are used only for distinguishing one from another, and do not indicate the degree of importance and order thereof, and the premise that each other exists, and the like.
Exemplary embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
Fig. 1 shows a flow diagram of a method for displaying venous thrombosis in accordance with an embodiment of the present disclosure. The method may be performed, for example, by a computer device including, but not limited to, a desktop computer, a laptop computer, a mobile device, a smart wearable device, and the like. As shown in fig. 1, the method includes:
step S2, acquiring dual-energy CT (computed tomography) flat scan data of a measured object, wherein the measured object comprises a plurality of voxels;
step S4, based on a three-material decomposition algorithm, converting the dual-energy CT flat scan data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scan data;
step S6, determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data;
step S8 is to generate an image for identifying a venous thrombus region of the object based on the degree of difference between each voxel and the first base material.
According to an embodiment of the present disclosure, dual-energy CT planform data is transformed onto a scale constructed based on a first basis material and a second basis material based on a three-material decomposition algorithm, resulting in enhanced data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; and generating an image for identifying the venous thrombosis area according to the difference degree of each voxel and the first base material. According to the embodiment of the disclosure, the difference degree between different voxels is increased by converting the dual-energy CT flat scan data into the enhanced data on the scale, so that the difference degree between the voxels corresponding to the venous thrombosis and the voxels corresponding to the normal blood is increased, the contrast between the venous thrombosis region and the normal blood region in the generated image is more obvious, and the venous thrombosis region can be accurately identified. The venous thrombosis area can be accurately identified only by acquiring the dual-energy CT (computed tomography) flat scan data of the measured object without using a contrast medium, so that adverse reactions of a patient caused by using the contrast medium are avoided; the patient does not need to be scanned for multiple times, so that radiation damage to the patient is reduced.
The individual steps of the method for displaying a venous thrombus shown in fig. 1 are described in detail below.
In step S2, dual energy CT scan data of the object under test is acquired.
Dual-Energy CT (DECT) scout refers to scanning and imaging an object with X-rays of two different energies without using a contrast agent. The dual-energy CT scan data may be acquired, for example, by a computed tomography device (i.e., a CT device) and then transmitted to a computer device for performing the method shown in fig. 1. Accordingly, the computer device obtains dual energy CT flat scan data of the measured object.
According to some embodiments, the dual energy CT scan data acquired in step S2 includes CT values at the first and second ray energies for each voxel of the object under test.
The object to be measured may be, for example, a head, a chest, a liver, a spleen, a pancreas, or the like of a patient. Various tissues of the human body (including normal and abnormal tissues) have unequal absorption of X-rays and have different attenuation coefficients μ. CT exploits this property to divide the object under test into a number of cube patches, called voxels, along a selected slice plane. That is, the object under test includes a plurality of voxels. When the X-ray passes through the object to be measured, each voxel along the ray direction absorbs a part of the ray to a certain extent, so that the X-ray is attenuated. The radiation after passing through the object to be measured is received by a detector located opposite the X-ray tube. The CT device can obtain the X-ray attenuation coefficient of each voxel by analyzing the X-ray energy received by the detector, and further obtain the CT value of each voxel.
Clinically, the CT value CT of the substance MMDefined as the attenuation coefficient mu of the substanceMAttenuation coefficient mu with waterWater (W)The difference between the two and the attenuation coefficient mu of waterWater (W)The ratio of (d) is multiplied by 1000, i.e.:
Figure BDA0003029610300000041
CT values are expressed in HU. CT values for some common human tissues are as follows:
CTwater (W)＝0HU
CTAir (a)＝﹣1000HU
CTBone＝1000HU
In a dual energy CT scan, the first radiation energy is different from the second radiation energy. Typically, one of the two is high energy and one is low energy. In some embodiments, the first ray energy may be, for example, 140kVp (peak voltage), and the second ray energy may be, for example, 80 kVp. It should be appreciated that in other embodiments, the first and second ray energies may have other values. Also, the first radiation energy may be less than the second radiation energy.
As previously mentioned, dual energy CT scan data includes CT values at a first ray energy and a second ray energy for each voxel of the object under test. If the CT value at the first radiation energy is taken as the horizontal axis (x-axis) and the CT value at the second radiation energy is taken as the vertical axis (y-axis), the dual-energy CT scan data can be presented in a two-dimensional map. Each voxel of the measured object corresponds to a voxel point in the two-dimensional map, and the coordinate of the voxel point corresponding to the voxel i is (x)i，yi) Wherein x isiFor the CT value, y, of voxel i at the first ray energyiIs the CT value of voxel i at the second ray energy.
For example, the object under test includes two voxels, voxel 1 and voxel 2. The first ray energy is 140kVp and the second ray energy is 80 kVp. Accordingly, the dual-energy CT scan data acquired at step S2 includes the CT value x of voxel 1 at 140kVp ray energy1CT value y at 80kVp ray energy1And CT value x of voxel 2 at 140kVp ray energy2CT value y at 80kVp ray energy2. Fig. 2 shows a schematic diagram of a two-dimensional map corresponding to the dual energy CT scan data. As shown in FIG. 2, the horizontal axis represents CT values at 140kVp ray energy and the vertical axis represents CT values at 80kVp ray energy, voxel 1 corresponds to point A in FIG. 2 and has the coordinate (x)1，y1) (ii) a Voxel 2 corresponds to point B in FIG. 2 and has the coordinate (x)2，y2)。
It should be understood that fig. 2 is intended as an example only, and is intended to illustrate the way dual-energy CT scan data is presented in a two-dimensional map by a simplified scenario (the object under test comprises two voxels). In practical cases, the number of voxels comprised by the object under test is usually much larger than 2.
It should be understood that CT values of some common substances at the first and second radiation energies may also be presented in the form of a two-dimensional map. Fig. 3 shows a two-dimensional graph of CT values for air, fat, water, blood, iodine, calcium at a first radiation energy and a second radiation energy. Each substance corresponds to a point in fig. 3. The CT values for air and water are calibrated to 0HU and-1000 HU (independent of the ray energy), and the Line connecting the points for both is the Identity Line.
After the dual energy CT scan data of the object to be measured is acquired through step S2, step S4 is performed.
In step S4, the dual-energy CT scan data is transformed onto a scale constructed based on the first and second basis materials based on a three-material decomposition algorithm, resulting in enhanced data. Wherein the degree of difference of the two voxels according to the enhanced data metric is greater than the degree of difference of the two voxels according to the dual-energy CT scan data metric.
It is understood that the three species include a first base species, a second base species, and a third base species. The first, second and third base materials can be flexibly selected by those skilled in the art according to the actual situation. Preferably, the first and second base substances may be two different substances having ray absorption characteristics closer to the air-water line (see fig. 3). For example, the first substrate material may be soft tissue, blood, etc.; the second base substance may be fat, water, etc. The third base substance may be a substance having a radiation absorption characteristic away from the air-water line (see fig. 3), such as iodine, calcium, or the like.
According to some embodiments, the step S4 further includes the following steps S42 and S44, based on the selected three substances:
generating an attenuation feature map of the measured object, which includes voxel points corresponding to each voxel, a first base material point corresponding to the first base material, a second base material point corresponding to the second base material, and a third base material point corresponding to the third base material, from the dual-energy CT scan data acquired in step S2, in step S42, wherein the scale is a connecting line between the first base material point and the second base material point;
in step S44, each voxel point is projected on the scale from the third base material point, and enhancement data is obtained.
Specifically, the horizontal axis of the attenuation feature map generated in step S42 represents the CT value at the first radiation energy, and the vertical axis represents the CT value at the second radiation energy. In the attenuation feature map, each voxel corresponds to a voxel point. The voxel point corresponding to the voxel i has the coordinate (x)i，yi) Wherein x isiFor the CT value, y, of voxel i at the first ray energyiIs the CT value of voxel i at the second ray energy.
Similarly, in the attenuation characteristic diagram, the first base material, the second base material, and the third base material correspond to the first base material dot, the second base material dot, and the third base material dot, respectively. Coordinates of j (j is 1,2,3) th base material pointIs (x)j，yj) Wherein x isjIs the CT value, y, of the jth base material at the first ray energyjAnd the CT value of the jth base material at the second ray energy. The CT values of the respective base materials at the first and second radiation energies may be measured in advance.
For example, the object under test includes two voxels, voxel 1 and voxel 2. The first ray energy is 140kVp and the second ray energy is 80 kVp. The first base material is soft tissue, the second base material is fat, and the third base material is iodine. Figure 4 shows the corresponding attenuation profile of the object under test. As shown in fig. 4, the horizontal axis of the attenuation profile is CT at 140kVp ray energy and the vertical axis is CT at 80kVp ray energy. The attenuation characteristic map comprises a voxel point A and a voxel point B corresponding to the voxel 1 and the voxel 2 respectively, and a soft tissue point M corresponding to the soft tissue, fat and iodine respectively1Fat point M2Iodine spot M3。
After the attenuation feature map of the measured object is generated through step S42, step S44 is performed.
In step S44, each voxel point is projected on the scale from the third base material point, and enhancement data is obtained.
In the attenuation feature map, the set of all voxel points corresponds to the original dual-energy CT flat scan data acquired in step S2; after each voxel point is projected onto the scale by step S44, a set of projections of each voxel point on the scale corresponds to the enhancement data.
In an embodiment of the invention, the degree of difference of the two voxels according to the enhanced data metric is larger than the degree of difference of the two voxels according to the dual-energy CT scan data metric. The magnitude relationship of the difference between the two voxels measured from the enhanced data and the difference between the two voxels measured from the original dual-energy CT scan data can be represented in the attenuation profile.
For example, in some embodiments, the degree of difference of two voxels as measured from dual-energy CT pan data is the distance between corresponding voxel points in the attenuation profile; the degree of difference of the two voxels according to the enhancement data metric is the distance between the projections on the scale of the corresponding voxel points in the attenuation map. Because the two individual pixel points are projected onto the ruler according to the third base material point, the projection process is equivalent to that two rays are emitted from the third base material point, and one ray is intersected with the ruler after passing through one individual pixel point to obtain a projection; the other ray crosses the scale after passing through another voxel point to obtain another projection. It will be appreciated that as the rays diverge, the distance between corresponding points on the two rays will be greater and greater, and accordingly, the distance between two projections of two voxel points on the scale will be greater than the distance between two voxel points, i.e., the degree of difference of two voxels measured from the enhanced data is greater than the degree of difference of two voxels measured from the dual energy CT scan data. By projecting each voxel point onto the scale, the difference degree between different voxels is increased, so that the difference degree between the voxel corresponding to the venous thrombus and the voxel corresponding to the normal blood is increased, the contrast between the venous thrombus area and the normal blood area in the generated image is more obvious, and the venous thrombus area can be accurately identified.
For example, still referring to FIG. 4, in FIG. 4, the scale is the soft tissue point M1And fat point M2Connecting line M1M2. According to iodine point M3Projecting the voxel point A to a scale M1M2At the upper, i.e. dropping iodine into spot M3Connected to voxel point A and extending to scale M1M2Intersecting, the intersection point A' is the voxel point A on the scale M1M2Projection of (2). Similarly, voxel point B is projected to scale M1M2Up, voxel point B on scale M1M2The projection on is point B'. As shown in FIG. 4, the degree of difference between voxel 1 and voxel 2, measured based on the raw dual-energy CT flat scan data (i.e., voxel point A and voxel point B), is the distance d between the corresponding voxel point A and voxel point B1The degree of difference between voxel 1 and voxel 2 based on the enhancement data metric (i.e., projection A ' and projection B ') is the distance d between the respective projection A ' and projection B1'. As shown in fig. 4, distance d1' greater than distance d1It can be seen that by projecting each voxel point onto the scale, the size of the different voxels is increasedThe degree of difference therebetween.
After transforming the dual-energy CT scan data onto a scale constructed based on the first and second base substances by step S44 to obtain enhanced data, step S6 is performed.
In step S6, the degree of difference between each voxel of the measurement object and the first base material is determined based on the enhancement data.
According to some embodiments, in step S6, the distances of the first base material dot projected on the scale by the individual pixel dots are calculated respectively; this distance is taken as the degree of difference of the corresponding voxel from the first base material.
For example, still referring to FIG. 4, point A' goes to soft tissue point M1A distance A' M1I.e. the degree of difference between the corresponding voxel 1 and the soft tissue.
The smaller the distance of the voxel point projected on the scale to the first base material point, the smaller the degree of difference between the corresponding voxel and the first base material. On the premise that the first base substance is selected to be a substance having a radiation absorption characteristic similar to that of venous thrombosis (for example, the first base substance is soft tissue or the like), and a voxel is not the first base substance, the smaller the degree of difference between the voxel and the first base substance, the more likely the voxel is venous thrombosis; the greater the degree of difference between a voxel and the first base substance, the more likely the voxel is normal blood.
On the premise that the first base substance is selected as a substance having a ray absorption characteristic similar to that of normal blood (for example, the first base substance is blood or the like), the greater the degree of difference between a voxel and the first base substance, the more likely the voxel is a venous thrombus; the smaller the degree of difference between a voxel and the first base substance, the more likely the voxel is normal blood.
After the degree of difference between each voxel of the object to be measured and the first base material is determined in step S6, step S8 is performed.
In step S8, an image representing a venous thrombus region of the object is generated based on the degree of difference between each voxel and the first base material.
According to some embodiments, step S8 further includes: determining the maximum difference degree of each voxel and the first base material; for each voxel, determining a gray value corresponding to the voxel according to the difference degree between the voxel and the first base material, the maximum difference degree and a preset maximum gray value; and generating an image for identifying a venous thrombosis area of the tested object according to the corresponding gray value of each voxel, wherein each voxel corresponds to one pixel in the image, and the venous thrombosis area is an area of which the gray value in the image belongs to a preset range.
For example, the object to be measured includes 256 voxels, and the degree of difference between each voxel and the first base material is d1，d2，…，d256. Accordingly, the maximum degree of difference between each voxel and the first base material is dmax＝max(d1，d2，…，d256). The preset maximum gray-scale value can be set by those skilled in the art according to actual conditions, for example, the maximum gray-scale value g can be setmaxSet to 127. Gray value g corresponding to voxel iiFor example, it can be calculated as follows:
Figure BDA0003029610300000081
an image representing the venous thrombus region of the test image can be generated based on the gray scale values corresponding to the respective voxels. Where each voxel corresponds to a pixel in the image. The venous thrombosis area is an area of which the gray value in the image belongs to a preset range. The preset range can be represented by a lower gray value limit and/or an upper gray value limit, that is, the venous thrombus region is a region composed of pixels of which the gray value is greater than or equal to the lower gray value limit and/or less than or equal to the upper gray value limit in the image.
When the first base substance is selected as a substance having a radiation absorption characteristic similar to that of venous thrombosis (for example, the first base substance is soft tissue or the like), the smaller the gradation value corresponding to a voxel, the more likely the voxel is venous thrombosis. Accordingly, an upper limit of the gray value may be set, and the venous thrombus region is a region in which the gray value in the image is smaller than the upper limit of the gray value. Or, an upper gray value limit and a lower gray value limit may be set at the same time, and the venous thrombus region is a region in which the gray value in the image is greater than the lower gray value limit and less than the upper gray value limit, in this case, if the gray value corresponding to a certain voxel is less than or equal to the lower gray value limit, the voxel may be considered as the first base substance; if the gray value corresponding to a certain voxel is greater than or equal to the upper limit of the gray value, the voxel is considered to correspond to the normal blood region.
When the first base substance is selected as a substance having a ray absorption characteristic similar to that of normal blood (for example, the first base substance is selected as blood or the like), the larger the gray value corresponding to a voxel, the more likely the voxel is a venous thrombus. Accordingly, a lower gray value limit may be set, the venous thrombus region being a region in the image having a gray value greater than the lower gray value limit. In this case, if the gray-scale value of a certain voxel is equal to or lower than the lower limit of the gray-scale value, the voxel can be considered to correspond to the normal blood region.
The preset range (lower gray value limit and/or upper gray value limit) can be set by those skilled in the art with reference to the actual situation, and the value thereof is not limited by the present disclosure.
According to some embodiments, in order to improve the display effect of the venous thrombus, the image of the gray scale generated in the above embodiments may be further converted into a color image, that is: determining a color value corresponding to each voxel according to the gray value corresponding to each voxel; and generating a color image for identifying a venous thrombosis area of the tested object according to the color value corresponding to each voxel, wherein each voxel corresponds to one pixel in the color image, and the venous thrombosis area is an area with a preset color in the color image.
The conversion relationship between the gray value and the color value can be set by a person skilled in the art with reference to the actual situation. For example, conversion formulas of the gray value and color values of R, G, B three color channels may be set, respectively, R, G, B color values corresponding to the gray value are calculated according to the corresponding conversion formulas, and then the three are superimposed to obtain corresponding RGB color pixels. The color pixel combination corresponding to each voxel generates a color image for identifying the venous thrombus area of the measured object. The venous thrombosis area is an area with a preset color in the color image. The preset color is determined by a conversion relationship between the gray value and the color value, for example, when the first base substance is selected as a substance having a radiation absorption characteristic similar to that of the venous thrombus (for example, the first base substance is soft tissue, etc.), the conversion relationship between the gray value and the color value may be set such that the smaller the gray value, the larger the B channel color value, the smaller the R, G channel color value, and accordingly, the venous thrombus region may be a blue region in the color image.
According to the embodiment of the disclosure, the difference degree between different voxels is increased by converting the dual-energy CT scan data into the enhanced data on the scale, so that the difference degree between the voxels corresponding to the venous thrombus and the voxels corresponding to the normal blood is increased, the contrast between the venous thrombus area and the normal blood area in the generated image is more obvious, and the venous thrombus area can be accurately identified. The venous thrombosis area can be accurately identified only by acquiring the dual-energy CT (computed tomography) flat scan data of the measured object without using a contrast medium, so that adverse reactions of a patient caused by using the contrast medium are avoided; the patient does not need to be scanned for multiple times, so that radiation damage to the patient is reduced.
Fig. 5A to 5C are schematic diagrams respectively illustrating the effects of single-energy CT scout scan (120kVp), dual-energy CT scout scan (80kVp-140kVp), and single-energy CT enhanced scan (120kVp, injected with iodine contrast agent) on the venous thrombus region according to an embodiment of the present disclosure. As shown in fig. 5A, in the single-energy CT flat scan image, the venous thrombus region E and the normal blood region F appear in similar gray scales, and the degree of difference is small, so that the venous thrombus region E and the normal blood region F cannot be distinguished from each other. As shown in fig. 5B, in the image generated by processing the dual-energy CT scan data by the method of the embodiment of the present disclosure, the gray value of the venous thrombus region E is smaller and appears as a dark region, while the gray value of the normal blood region F is larger and appears as a bright region, and the venous thrombus region E and the normal blood region F have a larger difference, so that the contrast is obvious and the boundary is clear. As shown in fig. 5C, in the single-energy CT enhanced scan image, the venous thrombus region E is darker than the normal blood region F, and can be distinguished from the normal blood region F. The venous thrombus region identified in fig. 5C is identical to that in fig. 5B, but the contrast of the venous thrombus region E with the normal blood region F is less apparent than in fig. 5B. Therefore, the embodiment of the disclosure can accurately identify the venous thrombus area by processing the dual-energy CT flat scan data, and the identification effect on the venous thrombus area is even better than that of CT enhanced scanning containing a contrast agent.
It will be appreciated that the method for displaying venous thrombosis of the above embodiments may be analogically applicable to displaying other target tissues. For example, the first base substance may be set to be fat in order to reveal fatty liver. Similarly to the method for displaying venous thrombosis of the above embodiment, the method for displaying fatty liver may include: acquiring dual-energy CT flat scanning data of a measured object; based on a three-substance decomposition algorithm, the dual-energy CT flat scanning data are transformed to a ruler constructed based on fat and other base substances (such as soft tissues and the like) to obtain enhanced data; determining the difference degree between each voxel of the measured object and the fat according to the enhanced data; and generating an image for identifying the fatty liver region of the tested object according to the difference degree between each voxel and the fat.
Fig. 6 shows a schematic view of an apparatus 600 for displaying venous thrombosis in accordance with an embodiment of the present disclosure. As shown in fig. 6, the apparatus 600 includes a tomographic scanning unit 610, a calculation unit 620, and a display unit 630:
the tomography unit 610 may be configured to acquire dual energy CT scan data of a measured object, the measured object including a plurality of voxels;
the calculation unit 620 may be configured to: acquiring the collected double-energy CT flat scanning data; based on a three-material decomposition algorithm, transforming the dual-energy CT flat scan data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scan data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; generating an image for identifying a venous thrombus area of the measured object according to the difference degree of each voxel and the first base material;
the display unit 630 may be configured to display the above-described image.
According to the embodiment of the disclosure, the calculating unit 610 can acquire dual-energy CT scan data acquired by the tomography unit 610, process the dual-energy CT scan data based on a three-substance decomposition algorithm, transform the dual-energy CT scan data onto a scale constructed based on a first base substance and a second base substance to obtain enhanced data, and determine the difference between each voxel of the measured object and the first base substance according to the enhanced data; an image for identifying the venous thrombus region of the object to be measured is generated based on the degree of difference between each voxel and the first base material, and displayed on the display unit 630. According to the embodiment of the disclosure, the difference degree between different voxels is increased by converting the dual-energy CT flat scan data into the enhanced data on the scale, so that the difference degree between the voxels corresponding to the venous thrombosis and the voxels corresponding to the normal blood is increased, the contrast between the venous thrombosis region and the normal blood region in the generated image is more obvious, and the venous thrombosis region can be accurately identified. The venous thrombosis area can be accurately identified only by acquiring the dual-energy CT (computed tomography) flat scan data of the measured object without using a contrast medium, so that adverse reactions of a patient caused by using the contrast medium are avoided; the patient does not need to be scanned for multiple times, so that radiation damage to the patient is reduced.
Specifically, the tomographic unit 610 may be any type of computed tomography apparatus (CT apparatus), such as a dual-source (i.e., including two X-ray tubes) dual-energy CT apparatus, a single-source single-energy CT apparatus capable of rapidly switching ray energy, and so on. The tomography unit 610 is used for acquiring dual-energy CT scan data of the measured object, including CT values of each voxel of the measured object under the first ray energy and the second ray energy.
Details of the dual-energy CT scan data can be found in the above description of step S2, and are not repeated here.
The tomography unit 610 may be in communication connection with the computing unit 620 in a wired or wireless manner, and transmit the acquired dual-energy CT scan data to the computing unit 620.
The calculation unit 620 acquires dual-energy CT scan data acquired by the tomography unit 610, processes the dual-energy CT scan data based on a three-substance decomposition algorithm, and transforms the dual-energy CT scan data onto a scale constructed based on a first base substance and a second base substance to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT scan data; determining the difference degree between each voxel of the measured object and the first base material according to the enhanced data; and generating an image for identifying the venous thrombosis area of the measured object according to the difference degree between each voxel and the first base material.
Specifically, the three species include a first base species, a second base species, and a third base species. The first, second and third base materials can be flexibly selected by those skilled in the art according to the actual situation. Preferably, the first and second base substances may be two different substances having ray absorption characteristics closer to the air-water line (see fig. 3). For example, the first substrate material may be soft tissue, blood, etc.; the second base substance may be fat, water, etc. The third base substance may be a substance having a radiation absorption characteristic away from the air-water line (see fig. 3), such as iodine, calcium, or the like.
According to some embodiments, the calculation unit 620 is further configured to transform the dual-energy CT scan data onto a scale constructed based on the first and second basis substances by: generating an attenuation feature map of the measured object according to the dual-energy CT scanning data, wherein the attenuation feature map comprises a voxel point corresponding to each voxel, a first base material point corresponding to a first base material, a second base material point corresponding to a second base material and a third base material point corresponding to a third base material, and a scale is a connecting line of the first base material point and the second base material point; and projecting each voxel point to a scale according to the third base material point to obtain enhancement data. The horizontal axis of the attenuation map represents the CT value at the first radiation energy, and the vertical axis represents the CT value at the second radiation energy.
According to some embodiments, the degree of difference of two voxels according to the dual-energy CT panning data metric is the distance between corresponding voxel points in the attenuation profile; the degree of difference of two voxels according to the enhancement data metric is the distance between the projections on the corresponding voxel stippling scale in the attenuation profile.
According to some embodiments, the calculation unit 620 is further configured to determine the degree of difference of each voxel from the first base substance by: respectively calculating the distance from the projection of each individual pixel point on the scale to the first base material point; this distance is taken as the degree of difference of the corresponding voxel from the first base material.
According to some embodiments, the calculation unit 620 is further configured to generate an image for identifying a venous thrombus area of the object under test by: determining the maximum difference degree of each voxel and the first base material; for each voxel, determining a gray value corresponding to the voxel according to the difference degree between the voxel and the first base material, the maximum difference degree and a preset maximum gray value; and generating an image for identifying a venous thrombosis area of the tested object according to the corresponding gray value of each voxel, wherein each voxel corresponds to one pixel in the image, and the venous thrombosis area is an area of which the gray value in the image belongs to a preset range.
According to an embodiment, the calculation unit 620 is further configured to generate an image for identifying a venous thrombus area of the object under test by: determining a color value corresponding to each voxel according to the gray value corresponding to each voxel; and generating a color image for identifying a venous thrombosis area of the tested object according to the color value corresponding to each voxel, wherein each voxel corresponds to one pixel in the color image, and the venous thrombosis area is an area with a preset color in the color image.
The display unit 630 may be in communication connection with the computing unit in a wired or wireless manner, and is used for displaying the image generated by the computing unit 620 for identifying the venous thrombosis area of the measured object.
It should be understood that the calculation unit 620 shown in fig. 6 is configured to perform the various steps in the method described with reference to fig. 1. Thus, the operations, features and advantages described above with respect to the method of fig. 1 apply equally to the computing unit 620 as well as to the apparatus 600. Certain operations, features and advantages may not be described in detail herein for the sake of brevity.
According to an aspect of the disclosure, a computer device is provided that includes a memory, a processor, and a computer program stored on the memory. The processor is configured to execute the computer program to implement the steps of any of the method embodiments described above.
According to an aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, implements the steps of any of the method embodiments described above.
According to an aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of any of the method embodiments described above.
Illustrative examples of such computer devices, non-transitory computer-readable storage media, and computer program products are described below in connection with FIG. 7.
Fig. 7 illustrates an example configuration of a computer device 700 that may be used to implement the methods described herein. For example, the computing unit 620 shown in fig. 6 may include an architecture similar to the computer device 700. The above-described method for displaying venous thrombosis may also be implemented in whole or at least in part by a computer device 700 or similar device or system.
The computer device 700 may be a variety of different types of devices, such as a server of a service provider, a device associated with a client (e.g., a client device), a system on a chip, and/or any other suitable computer device or computing system. Examples of computer device 700 include, but are not limited to: a desktop computer, a server computer, a notebook or netbook computer, a mobile device (e.g., a tablet, a cellular or other wireless telephone (e.g., a smartphone), a notepad computer, a mobile station), a wearable device (e.g., glasses, a watch), an entertainment device (e.g., an entertainment appliance, a set-top box communicatively coupled to a display device, a gaming console), a television or other display device, an automotive computer, and so forth. Thus, the computer device 700 may range from a full resource device with substantial memory and processor resources (e.g., personal computers, game consoles) to a low-resource device with limited memory and/or processing resources (e.g., traditional set-top boxes, hand-held game consoles).
The computer device 700 may include at least one processor 702, memory 704, communication interface(s) 706, presentation device 708, other input/output (I/O) devices 710, and one or more mass storage devices 712, which may be capable of communicating with each other, such as through a system bus 714 or other suitable connection.
The processor 702 may be a single processing unit or multiple processing units, all of which may include single or multiple computing units or multiple cores. The processor 702 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitry, and/or any devices that manipulate signals based on operational instructions. The processor 702 may be configured to retrieve and execute computer-readable instructions, such as program code for an operating system 716, program code for an application 718, program code for other programs 720, and the like, stored in the memory 704, mass storage device 712, or other computer-readable medium, among other capabilities.
Memory 704 and mass storage device 712 are examples of computer-readable storage media for storing instructions that are executed by processor 702 to implement the various functions described above. By way of example, memory 704 may generally include both volatile and nonvolatile memory (e.g., RAM, ROM, and the like). In addition, mass storage device 712 may generally include a hard disk drive, a solid state drive, removable media, including external and removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., CDs, DVDs), storage arrays, network attached storage, storage area networks, and the like. The memory 704 and mass storage device 712 may both be referred to herein collectively as memory or computer-readable storage media, and may be non-transitory media capable of storing computer-readable, processor-executable program instructions as computer program code that may be executed by the processor 702 as a particular machine configured to implement the operations and functions described in the examples herein.
A number of program modules may be stored on the mass storage device 712. These programs include an operating system 716, one or more application programs 718, other programs 720, and program data 722, which can be loaded into memory 704 for execution. Examples of such applications or program modules may include, for example, computer program logic (e.g., computer program code or instructions) for implementing the methods for displaying venous thrombosis of embodiments of the present disclosure.
Although illustrated in fig. 7 as being stored in memory 704 of computer device 700, modules 716, 718, 720, and 722, or portions thereof, may be implemented using any form of computer-readable media that is accessible by computer device 700. As used herein, "computer-readable media" includes at least two types of computer-readable media, namely computer storage media and communication media.
Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information for access by a computer device.
In contrast, communication media may embody computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism. Computer storage media, as defined herein, does not include communication media.
The computer device 700 may also include one or more communication interfaces 706 for communicating with it, such as over a network, direct connection, or the likeHis device exchanges data as discussed previously. Such communication interfaces may be one or more of the following: any type of network interface (e.g., a Network Interface Card (NIC)), wired or wireless (such as IEEE 802.11 Wireless LAN (WLAN)) wireless interface, worldwide interoperability for microwave Access (Wi-MAX) interface, Ethernet interface, Universal Serial Bus (USB) interface, cellular network interface, BluetoothTMAn interface, a Near Field Communication (NFC) interface, etc. The communication interface 706 may facilitate communications within a variety of networks and protocol types, including wired networks (e.g., LAN, cable, etc.) and wireless networks (e.g., WLAN, cellular, satellite, etc.), the Internet, and so forth. The communication interface 706 may also provide for communication with external storage devices (not shown), such as in storage arrays, network attached storage, storage area networks, and so forth.
In some examples, a display device 708, such as a monitor, may be included for displaying information and images to a user. Other I/O devices 710 may be devices that receive various inputs from a user and provide various outputs to the user, and may include touch input devices, gesture input devices, cameras, keyboards, remote controls, mice, printers, audio input/output devices, and so forth.
The above description is only exemplary of the present disclosure and should not be taken as limiting the disclosure, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims (21)

1. A method for visualizing venous thrombosis, comprising:
acquiring dual-energy CT flat scanning data of a measured object, wherein the measured object comprises a plurality of voxels;
based on a three-material decomposition algorithm, transforming the dual-energy CT flat scanning data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scanning data;
determining the difference degree between each voxel of the measured object and a first base material according to the enhancement data; and
and generating an image for identifying the venous thrombosis area of the measured object according to the difference degree of each voxel and the first base material.
2. The method of claim 1 wherein the dual energy CT scan data includes CT values at a first ray energy and a second ray energy for respective voxels of the object under test.
3. The method of claim 1, wherein the three species comprise the first base species, the second base species, and a third base species;
the transforming the dual-energy CT scan data onto a scale constructed based on a first basis material and a second basis material comprises:
generating an attenuation feature map of the measured object according to the dual-energy CT scan data, wherein the attenuation feature map comprises a voxel point corresponding to each voxel, a first base material point corresponding to a first base material, a second base material point corresponding to a second base material and a third base material point corresponding to a third base material, and the scale is a connecting line of the first base material point and the second base material point; and
and projecting each voxel point onto the scale according to the third base material point to obtain the enhancement data.
4. The method according to claim 3, wherein the first base substance comprises any one of soft tissue and blood, the second base substance comprises any one of fat and water, and the third base substance comprises any one of iodine and calcium.
5. The method of claim 3, wherein a horizontal axis of the attenuation profile represents CT values at a first radiation energy and a vertical axis represents CT values at a second radiation energy.
6. The method of any one of claims 3 to 5,
determining the difference degree of two voxels according to the dual-energy CT flat scan data measure as the distance between corresponding voxel points in the attenuation feature map;
the difference degree of the two voxels according to the enhancement data measure is the distance between the projections of the corresponding voxel points in the attenuation feature map on the scale.
7. The method of any of claims 3 to 5, wherein the determining a degree of difference of each voxel of the measurand from a first base substance from the enhancement data comprises:
respectively calculating the distance from the projection of each individual pixel point on the scale to the first base material point; and
the distance is taken as the degree of difference of the corresponding voxel from the first base material.
8. The method of claim 1, wherein the generating an image identifying venous thrombus regions of the subject according to the degree of difference of each voxel from a first base material comprises:
determining a maximum degree of difference between the respective voxel and the first base material;
for each voxel, determining a gray value corresponding to the voxel according to the difference degree between the voxel and the first base material, the maximum difference degree and a preset maximum gray value; and
and generating an image for identifying a venous thrombosis region of the tested object according to the corresponding gray value of each voxel, wherein each voxel corresponds to one pixel in the image, and the venous thrombosis region is a region of which the gray value in the image belongs to a preset range.
9. The method of claim 8, wherein the generating an image identifying a venous thrombus region of the subject from the gray scale values corresponding to each voxel comprises:
determining a color value corresponding to each voxel according to the gray value corresponding to each voxel; and
and generating a color image for identifying a venous thrombosis area of the tested object according to the color value corresponding to each voxel, wherein each voxel corresponds to one pixel in the color image, and the venous thrombosis area is an area with a preset color in the color image.
10. An apparatus for displaying venous thrombosis, comprising:
a tomography unit configured to acquire dual energy CT scout scan data of a measured object, the measured object including a plurality of voxels;
a computing unit configured to: acquiring the acquired dual-energy CT flat scanning data; based on a three-material decomposition algorithm, transforming the dual-energy CT flat scanning data to a scale constructed based on a first base material and a second base material to obtain enhanced data, wherein the difference degree of two voxels measured according to the enhanced data is greater than the difference degree of two voxels measured according to the dual-energy CT flat scanning data; determining the difference degree between each voxel of the measured object and a first base material according to the enhancement data; generating an image for identifying a venous thrombosis area of the measured object according to the difference degree of each voxel and the first base material; and
a display unit configured to display the image.
11. The apparatus of claim 10 wherein the dual energy CT scan data includes CT values at a first ray energy and a second ray energy for respective voxels of the object under test.
12. The device of claim 10, wherein the three substances comprise the first base substance, the second base substance, and a third base substance;
the computing unit is further configured to:
generating an attenuation feature map of the measured object according to the dual-energy CT scan data, wherein the attenuation feature map comprises a voxel point corresponding to each voxel, a first base material point corresponding to a first base material, a second base material point corresponding to a second base material and a third base material point corresponding to a third base material, and the scale is a connecting line of the first base material point and the second base material point; and
and projecting each voxel point onto the scale according to the third base material point to obtain the enhancement data.
13. The device according to claim 12, wherein the first base substance comprises any one of soft tissue, blood, the second base substance comprises any one of fat, water, the third base substance comprises any one of iodine, calcium.
14. The apparatus of claim 12, wherein the attenuation profile has a horizontal axis representing CT values at a first radiation energy and a vertical axis representing CT values at a second radiation energy.
15. The apparatus of any one of claims 12 to 14,
determining the difference degree of two voxels according to the dual-energy CT flat scan data measure as the distance between corresponding voxel points in the attenuation feature map;
the difference degree of the two voxels according to the enhancement data measure is the distance between the projections of the corresponding voxel points in the attenuation feature map on the scale.
16. The apparatus of any of claims 12 to 14, wherein the computing unit is further configured to:
respectively calculating the distance from the projection of each individual pixel point on the scale to the first base material point; and
the distance is taken as the degree of difference of the corresponding voxel from the first base material.
17. The apparatus of claim 10, wherein the computing unit is further configured to:
determining a maximum degree of difference between the respective voxel and the first base material;
for each voxel, determining a gray value corresponding to the voxel according to the difference degree between the voxel and the first base material, the maximum difference degree and a preset maximum gray value; and
and generating an image for identifying a venous thrombosis region of the tested object according to the corresponding gray value of each voxel, wherein each voxel corresponds to one pixel in the image, and the venous thrombosis region is a region of which the gray value in the image belongs to a preset range.
18. The apparatus of claim 17, wherein the computing unit is further configured to:
determining a color value corresponding to each voxel according to the gray value corresponding to each voxel; and
and generating a color image for identifying a venous thrombosis area of the tested object according to the color value corresponding to each voxel, wherein each voxel corresponds to one pixel in the color image, and the venous thrombosis area is an area with a preset color in the color image.
19. A computer device, comprising:
a memory, a processor, and a computer program stored on the memory,
wherein the processor is configured to execute the computer program to implement the steps of the method of any one of claims 1 to 9.
20. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the method of any of claims 1 to 9.
21. A computer program product comprising a computer program, wherein the computer program realizes the steps of the method of any one of claims 1 to 9 when executed by a processor.
CN202110426162.1A 2021-04-20 2021-04-20 Method, apparatus, computer device and medium for displaying venous thrombosis Pending CN113100803A (en)

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