CN113724207B - Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI - Google Patents
Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI Download PDFInfo
- Publication number
- CN113724207B CN113724207B CN202110924795.5A CN202110924795A CN113724207B CN 113724207 B CN113724207 B CN 113724207B CN 202110924795 A CN202110924795 A CN 202110924795A CN 113724207 B CN113724207 B CN 113724207B
- Authority
- CN
- China
- Prior art keywords
- blood vessel
- dimensional space
- dimensional
- region
- interest
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
- G06T2207/30104—Vascular flow; Blood flow; Perfusion
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
本发明提供一种基于4D Flow MRI的流速测量方法、装置、计算机和存储介质，该方法包括基于4D Flow MRI对血管进行流速测量，获得血管的三维图像和三维速度流场数据；根据预设规则对血管的三维图像选取感兴趣区域，获得目标血管感兴趣区域；根据血管的所述三维速度流场数据，提取所述目标血管感兴趣区域内的流速信息。通过直接在三维空间对目标血管进行感兴趣区域的选取，无需Reslice层的获取和目标血管感兴趣区域的手工勾画，降低了操作难度，减少了操作工作量。
The present invention provides a flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI, the method comprising: measuring the flow velocity of a blood vessel based on 4D Flow MRI, obtaining a three-dimensional image and three-dimensional velocity flow field data of the blood vessel; selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule, obtaining a target blood vessel region of interest; extracting the flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity flow field data of the blood vessel. By directly selecting the region of interest of the target blood vessel in three-dimensional space, there is no need to obtain a Reslice layer and manually outline the region of interest of the target blood vessel, thereby reducing the difficulty of operation and the workload of operation.
Description
Technical Field
The invention relates to the technical field of Flow velocity measurement based on magnetic resonance imaging, in particular to a Flow velocity measurement method, a Flow velocity measurement device, a Flow velocity measurement computer and a Flow velocity measurement storage medium based on 4D Flow MRI.
Background
The continued development of MR (Magnetic Resonance ) devices and techniques has resulted in significant improvements in the spatial resolution and soft tissue resolution of magnetic resonance imaging. With the improvement of the performance of radio frequency and gradient systems in a magnetic resonance imaging system and the continuous improvement and application of retrospective electrocardiographic gating and respiratory navigation technologies, a three-dimensional dynamic phase contrast imaging method capable of providing Flow velocity information which changes with time in three directions on a three-dimensional space is gradually developed and matured, and the imaging method is also called 4D Flow MRI. In recent years, the 4D Flow MRI method is continuously reported in domestic and foreign documents to directly obtain real blood Flow speed and Flow information in blood vessels, which is very important for researching in-vivo blood Flow dynamics, and the principle is that bipolar gradients are added in an imaging sequence to encode liquid flowing in a test body, and quantitative Flow speed information is finally obtained by comparing phase differences.
Before the development of 4D Flow MRI technology matured, computational fluid dynamics (Computational Fluid Dynamics, CFD) was the widely used method of studying hemodynamics. With the maturation and wide application of the 4DFlow MRI technology, the 4DFlow MRI technology is expected to replace the CFD method to become a target for in vivo hemodynamic research. Compared with the CFD method, the 4D Flow MRI method has three main advantages in the study of the body blood Flow dynamics, 1) the 4D Flow MRI method can directly measure the blood Flow velocity under the actual condition of the human body, and the result difference of the CFD method caused by the discrepancy between the assumed parameters in the simulation calculation and the actual physiological state of the human body is avoided. 2) The 4D Flow MRI method is a non-invasive nuclear magnetic resonance examination, and the three-dimensional image model adopted by the CFD method is mostly derived from an invasive DSA examination at present, and the DSA examination not only needs to receive a large dose of X-ray radiation, but also has serious complications such as cerebral infarction, cerebral hemorrhage and the like. 3) The 4D Flow MRI method is simple, convenient and quick, and can finish the acquisition of dynamic parameters such as three-dimensional imaging of blood vessels, blood Flow speed, wall shear stress and the like in about one hour. In recent years, the technology of 4DFlow MRI is used abroad to perform hemodynamic study on the cardiovascular and cerebrovascular systems, for example, retrospectively performing MR reconstruction on an arbitrary imaging plane in an imaging area to obtain flow velocity and flow information of the planar blood vessel, and deducing hemodynamic parameters such as blood flow relative pressure, calculated pulse wave velocity, wall shear stress and the like by utilizing the three-dimensional flow velocity information. These widespread applications all show a good prospect of the 4DFlow MRI technology in the hemodynamic study of the cardiovascular and cerebrovascular systems.
However, current 4D Flow MRI techniques suffer from the following drawbacks:
1) The directions of Reslice (slice reorganization) layers are respectively adjusted in the three-phase direction so that the slices are perpendicular to a target blood vessel, the operations are needed to be performed repeatedly in the three-phase direction, an operator can complete the operations through a certain space imagination, and the requirements on the operator are high. Overall, the operation is complicated and not simple.
2) After Relice layers are selected, the target outline needs to be further drawn on Reslice layers, and the operation amount is large.
3) The Reslice layers only cover a certain cross section of the target blood vessel, the range is smaller, the measured result has large dependence on the cross section where the Reslice layers are positioned, and the repeatability of the measured result value of the blood vessel with larger curvature is poor.
Disclosure of Invention
Based on this, it is necessary to provide a Flow velocity measurement method, apparatus, computer and storage medium based on 4D Flow MRI in view of the above technical problems.
A 4D Flow MRI-based Flow rate measurement method, comprising:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
And extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
In one embodiment, the step of selecting the region of interest from the three-dimensional image of the blood vessel according to a preset rule, and obtaining the target blood vessel region of interest includes:
acquiring a pre-constructed regular polyhedron three-dimensional space;
and selecting an interested region from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel interested region.
In one embodiment, the step of selecting the region of interest from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel region of interest includes:
Moving the regular polyhedron three-dimensional space to a target blood vessel, so that the target blood vessel passes through the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, when two opposite faces of the regular polyhedron three-dimensional space are parallel to the cross-section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the step of selecting the target blood vessel in the regular polyhedron three-dimensional space as the target blood vessel region of interest includes:
Rotating the regular polyhedron three-dimensional space such that two opposing faces of the regular polyhedron three-dimensional space are parallel to a cross-section of the target vessel;
reducing or enlarging the regular polyhedron three-dimensional space so that the target blood vessel is completely located in the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space.
In one embodiment, the step of obtaining the three-dimensional image and the three-dimensional velocity Flow field data of the blood vessel by performing Flow velocity measurement on the blood vessel based on the 4D Flow MRI further includes:
preprocessing the three-dimensional velocity flow field data of the blood vessel to obtain preprocessed three-dimensional velocity flow field data;
The step of extracting flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity flow field data of the blood vessel comprises the following steps:
and extracting flow velocity information in the target vessel region of interest according to the preprocessed three-dimensional velocity flow field data.
In one embodiment, the preprocessing the three-dimensional velocity flow field data of the blood vessel comprises:
And respectively removing background noise, vortex correction and vessel segmentation from the three-dimensional velocity flow field data of the vessel.
A 4D Flow MRI-based Flow rate measurement device, comprising:
the Flow field data acquisition module is used for measuring the Flow velocity of the blood vessel based on the 4D Flow MRI to obtain a three-dimensional image and three-dimensional velocity Flow field data of the blood vessel;
The region of interest acquisition module is used for selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
and the flow velocity information extraction module is used for extracting flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity flow field data of the blood vessel.
A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor when executing the computer program performs the steps of:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
And extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
And extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
According to the Flow velocity measurement method, the Flow velocity measurement device, the Flow velocity measurement computer and the Flow velocity measurement storage medium based on the 4D Flow MRI, the target blood vessel is directly selected in the three-dimensional space, the Reslice layers are not required to be acquired and the target blood vessel region of interest is not required to be manually sketched, the operation difficulty is reduced, and the operation workload is reduced.
In addition, in some embodiments, the target blood vessel based on the regular polyhedron three-dimensional space pair is selected from the region of interest, so that a larger blood vessel segment range can be freely coated, more intraluminal blood flow information is contained, the dependence of a measurement result on a single section of the blood vessel is reduced, and the repeatability and consistency of the measurement result are improved.
Drawings
FIG. 1 is a Flow diagram of a Flow rate measurement method based on 4D Flow MRI in one embodiment;
FIG. 2 is a block diagram of a Flow rate measurement device based on 4D Flow MRI in one embodiment;
FIG. 3 is an internal block diagram of a computer device in one embodiment;
FIG. 4 is a Flow chart of a Flow rate measurement method based on 4D Flow MRI in another embodiment;
FIG. 5 is a schematic diagram of a selection of a region of interest in three-dimensional space based on a regular hexahedron in one embodiment;
Fig. 6 is a schematic diagram of a target vessel segment flow rate measurement in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Example 1
In this embodiment, as shown in fig. 1, there is provided a Flow rate measurement method based on 4D Flow MRI, which includes:
Step 110, performing Flow velocity measurement on the blood vessel based on the 4D Flow MRI, and obtaining a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data.
Specifically, a 4D Flow MRI technology is adopted to measure the Flow velocity of the blood vessel and construct a three-dimensional image based on the blood vessel, so as to obtain the three-dimensional image and three-dimensional velocity Flow field data of the blood vessel.
And 120, selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest.
In this embodiment, a preset rule is adopted to extract a region of interest from the three-dimensional image of the blood vessel, where the region of interest is the target blood vessel segment, that is, the target blood vessel region of interest. In one embodiment, the preset rule is to select the region of interest using a pre-constructed regular polyhedron three-dimensional space.
And 130, extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
In this step, after the target vessel region of interest is determined, since the three-dimensional velocity flow field data of the vessel has been calculated in the foregoing step, the three-dimensional velocity flow field data of the target vessel region of interest can be extracted, and the flow velocity information of the target vessel region of interest can be obtained.
In this embodiment, the flow rate information of the target vessel region of interest includes a minimum flow rate, a maximum flow rate, and an average flow rate at different time points.
In the embodiment, the target blood vessel is directly selected in the three-dimensional space, so that Reslice layers of acquisition and manual sketching of the target blood vessel region of interest are not needed, the operation difficulty is reduced, and the operation workload is reduced.
In one embodiment, the step of selecting the region of interest from the three-dimensional image of the blood vessel according to the preset rule and obtaining the target blood vessel region of interest comprises the steps of obtaining a pre-built regular polyhedron three-dimensional space, selecting the region of interest from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space and obtaining the target blood vessel region of interest.
In this embodiment, a regular polyhedron three-dimensional space is previously constructed, and the shape of the regular polyhedron three-dimensional space is a three-dimensional space surrounded by regular polyhedrons.
As shown in fig. 5, the pre-constructed regular polyhedron three-dimensional space 510 is located in the three-dimensional image of the blood vessel, and the regular polyhedron three-dimensional space 510 is transparent in the three-dimensional image of the blood vessel, the position of the regular polyhedron three-dimensional space 510 is adjustable, the size of the regular polyhedron three-dimensional space 510 is adjustable, and the regular polyhedron three-dimensional space 510 and the blood vessel can be overlapped. In this way, the segment of the target vessel in the regular polyhedron three-dimensional space 510 is determined as the target vessel region of interest by moving the position of the regular polyhedron three-dimensional space 510 within the three-dimensional image of the vessel such that the segment of the target vessel is located within the regular polyhedron three-dimensional space 510.
In one embodiment, the step of selecting the region of interest for the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space and obtaining the target blood vessel region of interest comprises the steps of moving the regular polyhedron three-dimensional space to a target blood vessel so that the target blood vessel passes through the regular polyhedron three-dimensional space, and selecting the target blood vessel in the regular polyhedron three-dimensional space as the target blood vessel region of interest when two opposite faces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space.
In this embodiment, the regular polyhedron three-dimensional space has at least two oppositely disposed faces, and the two oppositely disposed faces are parallel to each other, in this embodiment, the two oppositely arranged surfaces of the regular polyhedron three-dimensional space are a group of parallel surfaces, the regular polyhedron three-dimensional space is provided with a plurality of groups of parallel surfaces, and the two surfaces of each group of parallel surfaces are oppositely arranged and are mutually parallel.
In this embodiment, the direction of the regular polyhedron three-dimensional space is determined by the parallelism of the two opposite and parallel surfaces of the regular polyhedron three-dimensional space and the cross section of the target blood vessel, and when the two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel, the direction of the regular polyhedron three-dimensional space is correct, and the posture is correct. And when all the target blood vessels are positioned in the regular polyhedron three-dimensional space, indicating that the target blood vessel region of interest is determined, selecting the segment of the target blood vessel in the regular polyhedron three-dimensional space as the target blood vessel region of interest, thereby completing the selection of the target blood vessel region of interest. Through the regular polyhedron three-dimensional space selection, the selection of the target vessel region of interest can be more convenient, the region of interest does not need to be manually sketched, the operation difficulty is effectively reduced, and the workload is reduced.
In one embodiment, the regular polyhedron three-dimensional space is a regular polyhedron prismatic three-dimensional space, i.e. the cross-section of the regular polyhedron three-dimensional space is polygonal.
In one embodiment, the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space. In one embodiment, the three-dimensional regular hexahedral space is a three-dimensional regular hexahedral prism space having a hexagonal cross-section.
In one embodiment, the regular polyhedron three-dimensional space is a regular octahedron three-dimensional space. In one embodiment, the regular octahedral three-dimensional space is a regular octahedral prism three-dimensional space having an octagonal cross-section.
In other embodiments, the regular polyhedron three-dimensional space may be a regular tetrahedron three-dimensional space, a regular decahedron three-dimensional space, where the regular polyhedron three-dimensional space has several groups of parallel faces, for example, the faces of the regular polyhedron are even numbers, and several groups of parallel faces, and all these regular polyhedron three-dimensional spaces belong to those skilled in the art, and can be derived from the above description, and are not listed in this embodiment.
In one embodiment, when two opposite faces of the regular polyhedron three-dimensional space are parallel to the cross-section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the step of selecting the target blood vessel in the regular polyhedron three-dimensional space as the target blood vessel region of interest includes:
The method comprises the steps of rotating the regular polyhedron three-dimensional space to enable two opposite faces of the regular polyhedron three-dimensional space to be parallel to the cross section of a target blood vessel, shrinking or enlarging the regular polyhedron three-dimensional space to enable the target blood vessel to be completely located in the regular polyhedron three-dimensional space, and selecting the target blood vessel in the regular polyhedron three-dimensional space as an interested region of the target blood vessel when the two opposite faces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space.
In this embodiment, as shown in fig. 5, the regular polyhedron three-dimensional space 510 can move, rotate, adjust the direction, shrink and enlarge in the three-dimensional image of the blood vessel, so that the regular polyhedron three-dimensional space 510 is moved to coincide with the target blood vessel by moving the regular polyhedron three-dimensional space 510, then adjusting the direction of the regular polyhedron three-dimensional space 510, rotating the regular polyhedron three-dimensional space 510, so that the cross section of the head and tail of the segment of the target blood vessel is parallel to two opposite faces of the regular polyhedron three-dimensional space 510, and then shrinking or enlarging the regular polyhedron three-dimensional space 510, so that the segment of the target blood vessel in the regular polyhedron three-dimensional space 510 is the region of interest of the target blood vessel, thereby completing the selection of the region of interest of the target blood vessel. Through the regular polyhedron three-dimensional space selection, the selection of the target vessel region of interest can be more convenient, the region of interest does not need to be manually sketched, the operation difficulty is effectively reduced, and the workload is reduced.
In one embodiment, the step of obtaining the three-dimensional image and the three-dimensional velocity Flow field data of the blood vessel based on the 4D Flow MRI further comprises preprocessing the three-dimensional velocity Flow field data of the blood vessel to obtain the preprocessed three-dimensional velocity Flow field data, and the step of extracting the Flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity Flow field data of the blood vessel comprises extracting the Flow velocity information in the target blood vessel region of interest according to the preprocessed three-dimensional velocity Flow field data.
It should be appreciated that the image quality of the 4D Flow MRI data is affected by the phase shift differences caused by noise and eddy currents during acquisition, and therefore data preprocessing is required to remove the noise and phase shift. In this embodiment, through preprocessing, noise of the three-dimensional velocity flow field data can be effectively removed, and phase deviation is reduced or removed, so that accuracy of flow velocity information is effectively improved.
In one embodiment, the preprocessing of the three-dimensional velocity flow field data of the blood vessel includes removing background noise, vortex shedding, and vessel segmentation, respectively, of the three-dimensional velocity flow field data of the blood vessel.
In this embodiment, after the processing of removing background noise, correcting vortex and dividing blood vessels is performed on the three-dimensional velocity Flow field data obtained by the 4D Flow MRI measurement, three-dimensional velocity Flow field data in the lumen of the blood vessel with better quality can be obtained, so that the accuracy of Flow velocity information is effectively improved.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
Example two
In this embodiment, please refer to fig. 4, firstly, the Flow velocity measurement based on the 4D Flow MRI is completed, three-dimensional velocity Flow field data of the blood vessel is obtained, the three-dimensional velocity Flow field data is preprocessed, then ROI (region of interest) is selected according to the measurement position of the target blood vessel in the three-dimensional space, the region of interest is selected, and finally, the Flow velocity information of the voxel covered by the ROI is automatically calculated according to the selected ROI.
The method comprises the steps of preprocessing three-dimensional speed flow field data:
during the acquisition process of the 4D Flow MRI data, the image quality is affected by noise and phase offset difference caused by eddy current, so that data preprocessing is required to remove the noise and the phase offset. The preprocessing step of the 4D Flow MRI data includes removing background noise, vortex correction, and vessel segmentation. After the steps, three-dimensional velocity flow field data in the lumen of the blood vessel with better quality can be obtained.
Three-dimensional spatial ROI selection:
After obtaining the intravascular flow field data in the three-dimensional space, as shown in fig. 5, the application directly selects the target vessel ROI in the three-dimensional space. The selection of the target vessel ROI is realized based on a regular hexahedron which can be stretched and rotated in three-dimensional space and multiple degrees of freedom. The selection of the ROI in three-dimensional space is accomplished by 1) translating a freely rotatable and extendable regular hexahedron to the target vessel segment such that the target vessel passes through the regular hexahedron, 2) rotating the regular hexahedron such that its diametrically opposed two planes are parallel to the cross-section of the target vessel segment, 3) scaling the regular hexahedron such that the target vessel segment is completely enclosed within the regular hexahedron. The ROI of the target vessel selected in three dimensions is shown in the following figure.
And (3) measuring flow rate information:
After the target blood vessel ROI is selected, the voxels coated in the ROI are extracted, and the flow velocity information at the target blood vessel is measured according to the speed data at which the voxels are positioned. The 4DFlowMRI technique can collect velocity data at multiple time points within a heartbeat cycle, where the technique calculates and summarizes the minimum flow rate, the maximum flow rate, and the average flow rate at all time points at the target vessel ROI, and the calculated results are shown in fig. 6 below.
Furthermore, after obtaining flow rate information at all time points, the present application can calculate the pulsatility index (Pulsatility Index, PI) and resistance index (RESISTANCE INDEX, RI) at the target vessel ROI based on this. The calculation formulas of the pulsation index and the resistance index are respectively as follows:
PI=2(S-D)/(S+D)
RI=(S-D)/S
where S is the peak value of arterial blood flow systole, i.e. the maximum blood flow velocity measured at all time points, and D is the valley value of arterial blood flow end diastole, i.e. the minimum blood flow velocity measured at all time points.
The beneficial effects of this embodiment are:
1. The free selection of the target blood vessel segment ROI can be directly realized in the three-dimensional space, the acquisition of Reslice layers and the manual sketching of the target blood vessel ROI are not needed, and the user friendliness is improved.
2. The target blood vessel ROI based on the regular hexahedron can be freely coated with a larger blood vessel segment range, so that more intraluminal blood flow information is contained, the dependence of a measurement result on a single section of the blood vessel is reduced, and the repeatability and consistency of the measurement result are improved.
Example III
In this embodiment, as shown in fig. 2, there is provided a Flow rate measurement device based on 4D Flow MRI, including:
the Flow field data acquisition module 210 is configured to perform Flow velocity measurement on a blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
the region of interest obtaining module 220 is configured to select a region of interest from a three-dimensional image of a blood vessel according to a preset rule, and obtain a target blood vessel region of interest;
The flow velocity information extraction module 230 is configured to extract flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
In one embodiment, the region of interest acquisition module includes:
the regular polyhedron three-dimensional space acquisition unit is used for acquiring a pre-constructed regular polyhedron three-dimensional space;
The region of interest acquisition unit is used for selecting a region of interest from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel region of interest.
In one embodiment, the region of interest acquisition unit includes:
A regular polyhedron three-dimensional space moving subunit, configured to move the regular polyhedron three-dimensional space to a target blood vessel, so that the target blood vessel passes through the regular polyhedron three-dimensional space;
And the region-of-interest acquisition subunit is used for selecting the target blood vessel in the regular polyhedron three-dimensional space as the region of interest of the target blood vessel when two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely positioned in the regular polyhedron three-dimensional space.
In one embodiment, the region of interest acquisition subunit is further configured to rotate the regular polyhedron three-dimensional space such that two opposing faces of the regular polyhedron three-dimensional space are parallel to a cross-section of the target vessel;
the region of interest acquisition subunit is further configured to reduce or enlarge the regular polyhedron three-dimensional space, so that the target blood vessel is completely located in the regular polyhedron three-dimensional space;
The region of interest acquisition subunit is further configured to select, when two opposite surfaces of the regular polyhedron three-dimensional space are parallel to a cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space as the target blood vessel region of interest.
In one embodiment, the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space.
In one embodiment, the Flow rate measurement device based on 4D Flow MRI further includes:
The pretreatment module is used for carrying out pretreatment on the three-dimensional velocity flow field data of the blood vessel to obtain the pretreated three-dimensional velocity flow field data;
the flow velocity information extraction module is also used for extracting flow velocity information in the target vessel region of interest according to the preprocessed three-dimensional velocity flow field data.
In one embodiment, the preprocessing module is configured to perform background noise removal, vortex correction and vessel segmentation on the three-dimensional velocity flow field data of the vessel, respectively.
For specific limitations on the Flow rate measurement device based on 4D Flow MRI, reference may be made to the above limitations on the Flow rate measurement method based on 4D Flow MRI, and will not be described here. Each of the units in the above-described 4D Flow MRI-based Flow rate measurement device may be implemented in whole or in part by software, hardware, and combinations thereof. The units can be embedded in hardware or independent of a processor in the computer equipment, and can also be stored in a memory in the computer equipment in a software mode, so that the processor can call and execute the operations corresponding to the units.
Example IV
In this embodiment, a computer device is provided. The internal structure thereof can be shown in fig. 3. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database for storing three-dimensional images and three-dimensional velocity flow field data. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used to communicate with other computer devices in which application software is deployed. The computer program, when executed by a processor, implements a Flow rate measurement method based on 4D Flow MRI. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
And extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring a pre-constructed regular polyhedron three-dimensional space;
and selecting an interested region from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel interested region.
In one embodiment, the processor when executing the computer program further performs the steps of:
Moving the regular polyhedron three-dimensional space to a target blood vessel, so that the target blood vessel passes through the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, the processor when executing the computer program further performs the steps of:
Rotating the regular polyhedron three-dimensional space such that two opposing faces of the regular polyhedron three-dimensional space are parallel to a cross-section of the target vessel;
reducing or enlarging the regular polyhedron three-dimensional space so that the target blood vessel is completely located in the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space.
In one embodiment, the processor when executing the computer program further performs the steps of:
preprocessing the three-dimensional velocity flow field data of the blood vessel to obtain preprocessed three-dimensional velocity flow field data;
and extracting flow velocity information in the target vessel region of interest according to the preprocessed three-dimensional velocity flow field data.
In one embodiment, the processor when executing the computer program further performs the steps of:
And respectively removing background noise, vortex correction and vessel segmentation from the three-dimensional velocity flow field data of the vessel.
Example five
In this embodiment, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
And extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a pre-constructed regular polyhedron three-dimensional space;
and selecting an interested region from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel interested region.
In one embodiment, the computer program when executed by the processor further performs the steps of:
Moving the regular polyhedron three-dimensional space to a target blood vessel, so that the target blood vessel passes through the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, the computer program when executed by the processor further performs the steps of:
Rotating the regular polyhedron three-dimensional space such that two opposing faces of the regular polyhedron three-dimensional space are parallel to a cross-section of the target vessel;
reducing or enlarging the regular polyhedron three-dimensional space so that the target blood vessel is completely located in the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
In one embodiment, the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space.
In one embodiment, the computer program when executed by the processor further performs the steps of:
preprocessing the three-dimensional velocity flow field data of the blood vessel to obtain preprocessed three-dimensional velocity flow field data;
and extracting flow velocity information in the target vessel region of interest according to the preprocessed three-dimensional velocity flow field data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
And respectively removing background noise, vortex correction and vessel segmentation from the three-dimensional velocity flow field data of the vessel.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A 4D Flow MRI-based Flow rate measurement method, comprising:
performing Flow velocity measurement on the blood vessel based on 4D Flow MRI to obtain a three-dimensional image of the blood vessel and three-dimensional velocity Flow field data;
Selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
Extracting flow velocity information in the region of interest of the target blood vessel according to the three-dimensional velocity flow field data of the blood vessel;
The step of selecting the region of interest from the three-dimensional image of the blood vessel according to the preset rule to obtain the region of interest of the target blood vessel comprises the following steps:
acquiring a pre-constructed regular polyhedron three-dimensional space;
and selecting an interested region from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel interested region.
2. The method of claim 1, wherein the regular polyhedron three-dimensional space is transparent within the three-dimensional image of the blood vessel, the position of the regular polyhedron three-dimensional space is adjustable, and the size of the regular polyhedron three-dimensional space is adjustable.
3. The method according to claim 2, wherein the step of selecting a region of interest from the three-dimensional image of the vessel based on the regular polyhedron three-dimensional space, and obtaining the target vessel region of interest comprises:
Moving the regular polyhedron three-dimensional space to a target blood vessel, so that the target blood vessel passes through the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
4. A method according to claim 3, wherein when two opposite faces of the regular polyhedron three-dimensional space are parallel to the cross-section of the target vessel and the target vessel is located entirely within the regular polyhedron three-dimensional space, the step of selecting the target vessel within the regular polyhedron three-dimensional space as the target vessel region of interest comprises:
Rotating the regular polyhedron three-dimensional space such that two opposing faces of the regular polyhedron three-dimensional space are parallel to a cross-section of the target vessel;
reducing or enlarging the regular polyhedron three-dimensional space so that the target blood vessel is completely located in the regular polyhedron three-dimensional space;
When two opposite surfaces of the regular polyhedron three-dimensional space are parallel to the cross section of the target blood vessel and the target blood vessel is completely located in the regular polyhedron three-dimensional space, the target blood vessel in the regular polyhedron three-dimensional space is selected as the target blood vessel region of interest.
5. The method of any one of claims 2-4, wherein the regular polyhedron three-dimensional space is a regular hexahedral three-dimensional space.
6. The method of claim 1, wherein the step of obtaining three-dimensional images and three-dimensional velocity Flow field data of the blood vessel based on the Flow measurement of the blood vessel by 4D Flow MRI further comprises:
preprocessing the three-dimensional velocity flow field data of the blood vessel to obtain preprocessed three-dimensional velocity flow field data;
The step of extracting flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity flow field data of the blood vessel comprises the following steps:
and extracting flow velocity information in the target vessel region of interest according to the preprocessed three-dimensional velocity flow field data.
7. The method of claim 6, wherein the preprocessing the three-dimensional velocity flow field data of a blood vessel comprises:
And respectively removing background noise, vortex correction and vessel segmentation from the three-dimensional velocity flow field data of the vessel.
8. A 4D Flow MRI-based Flow rate measurement device, comprising:
the Flow field data acquisition module is used for measuring the Flow velocity of the blood vessel based on the 4D Flow MRI to obtain a three-dimensional image and three-dimensional velocity Flow field data of the blood vessel;
The region of interest acquisition module is used for selecting a region of interest from the three-dimensional image of the blood vessel according to a preset rule to obtain a target blood vessel region of interest;
The flow velocity information extraction module is used for extracting flow velocity information in the target blood vessel region of interest according to the three-dimensional velocity flow field data of the blood vessel;
the region of interest acquisition module includes:
the regular polyhedron three-dimensional space acquisition unit is used for acquiring a pre-constructed regular polyhedron three-dimensional space;
The region of interest acquisition unit is used for selecting a region of interest from the three-dimensional image of the blood vessel according to the regular polyhedron three-dimensional space, and obtaining the target blood vessel region of interest.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110924795.5A CN113724207B (en) | 2021-08-12 | 2021-08-12 | Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110924795.5A CN113724207B (en) | 2021-08-12 | 2021-08-12 | Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113724207A CN113724207A (en) | 2021-11-30 |
| CN113724207B true CN113724207B (en) | 2024-12-31 |
Family
ID=78675675
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110924795.5A Active CN113724207B (en) | 2021-08-12 | 2021-08-12 | Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113724207B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114820664B (en) * | 2022-06-28 | 2022-09-30 | 浙江大学 | Image data processing method, device, image data processing device and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886312A (en) * | 2014-03-21 | 2014-06-25 | 华东师范大学 | Method for rapidly selecting and displaying interested blood vessel in magnetic resonance blood vessel image |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7123766B2 (en) * | 2002-02-11 | 2006-10-17 | Cedara Software Corp. | Method and system for recognizing and selecting a region of interest in an image |
| US10241180B2 (en) * | 2015-01-30 | 2019-03-26 | Northwestern University | System and method for mapping and quantifying in-vivo blood flow stasis |
| US20200315547A1 (en) * | 2019-04-02 | 2020-10-08 | Tencent America LLC | Vertebral artery dissection risk evaluation method, computer device, and storage medium |
| CN113076705A (en) * | 2021-03-26 | 2021-07-06 | 北京阅影科技有限公司 | Method and device for simulating blood flow dynamics |
-
2021
- 2021-08-12 CN CN202110924795.5A patent/CN113724207B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886312A (en) * | 2014-03-21 | 2014-06-25 | 华东师范大学 | Method for rapidly selecting and displaying interested blood vessel in magnetic resonance blood vessel image |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113724207A (en) | 2021-11-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Tamada et al. | Motion artifact reduction using a convolutional neural network for dynamic contrast enhanced MR imaging of the liver | |
| Pan et al. | Fast tracking of cardiac motion using 3D-HARP | |
| Frakes et al. | Application of an adaptive control grid interpolation technique to morphological vascular reconstruction | |
| Wen et al. | An accurate and effective FMM-based approach for freehand 3D ultrasound reconstruction | |
| US11940578B2 (en) | Super resolution in positron emission tomography imaging using ultrafast ultrasound imaging | |
| Long et al. | Magnetic resonance image processing and structured grid generation of a human abdominal bifurcation | |
| CN104582567B (en) | Magnetic resonance imaging apparatus | |
| WO2020033566A1 (en) | Neural networks for volumetric segmentation and parcellated surface representations | |
| CN115830016B (en) | Medical image registration model training method and equipment | |
| CN105303547A (en) | Multiphase CT image registration method based on grid matching Demons algorithm | |
| CN113724207B (en) | Flow velocity measurement method, device, computer and storage medium based on 4D Flow MRI | |
| CN108780134A (en) | The magnetic susceptibility of mobile object maps | |
| Materka et al. | Automated modeling of tubular blood vessels in 3D MR angiography images | |
| Köhler et al. | Motion-aware stroke volume quantification in 4D PC-MRI data of the human aorta | |
| Liu et al. | Meta-QSM: an image-resolution-arbitrary network for QSM reconstruction | |
| Rubert et al. | Four-dimensional fetal cardiac imaging in a cohort of fetuses with suspected congenital heart disease | |
| Hutter et al. | Low-rank and sparse matrix decomposition for compressed sensing reconstruction of magnetic resonance 4D phase contrast blood flow imaging (loSDeCoS 4D-PCI) | |
| Yang et al. | A comparative study of different level interpolations for improving spatial resolution in diffusion tensor imaging | |
| CN104793160B (en) | A kind of method of the frequency aliasing effect for reducing lack sampling magnetic resonance imaging | |
| Waldkirch | Methods for three-dimensional registration of multimodal abdominal image data | |
| Haddad et al. | A realistic anthropomorphic numerical model of the beating heart | |
| Wang et al. | Spectrum-sine interpolation framework for DTI processing | |
| CN115251884B (en) | A magnetic resonance (MR) imaging method and system | |
| Liu et al. | Optimization of reconstruction of 2D medical images based on computer 3D reconstruction technology | |
| WO2023203722A1 (en) | Information processing device, information processing method, and recording medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |