WO2008034164A1 - Analyse de débit - Google Patents

Analyse de débit Download PDF

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Publication number
WO2008034164A1
WO2008034164A1 PCT/AU2007/000827 AU2007000827W WO2008034164A1 WO 2008034164 A1 WO2008034164 A1 WO 2008034164A1 AU 2007000827 W AU2007000827 W AU 2007000827W WO 2008034164 A1 WO2008034164 A1 WO 2008034164A1
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WIPO (PCT)
Prior art keywords
images
measure
flow
fluid
fluid flow
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PCT/AU2007/000827
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English (en)
Inventor
Kelvin Wong
Pawel Kuklik
Stephen Worthley
Prash Sanders
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Adelaide Research & Innovation Pty Ltd
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Publication date
Priority claimed from AU2006905231A external-priority patent/AU2006905231A0/en
Application filed by Adelaide Research & Innovation Pty Ltd filed Critical Adelaide Research & Innovation Pty Ltd
Publication of WO2008034164A1 publication Critical patent/WO2008034164A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026—Measuring blood flow
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1107—Measuring contraction of parts of the body, e.g. organ, muscle

Definitions

  • the invention relates to the analysis of fluid flow within a body.
  • the present invention will be described, with particular reference to the application of analysing blood flow within a heart.
  • the present invention is not limited to this application.
  • OF optical flow
  • a current method for measuring blood flow within the heart is cardiac elastography.
  • This method takes raw data such as tissue displacement from echocardiograms (ultrasound of the heart) to measure strain on the heart during the contraction and relaxation of heart muscle.
  • two-dimensional slices of the heart can be imaged and its Doppler flow data can be used for flow visualisation of blood in the cardiac structure.
  • Doppler ultrasound can be used to measure blood flow in the heart, in vivo. This allows assessment of the cardiac valve areas and function, any abnormal communications between the left and right side of the heart, any leaking of blood through the valves (valvular regurgitation), and calculation of the cardiac output as well as the ejection fraction.
  • Phase-contrast MRI is another technique that can be used to analyse blood flow, using the property that a uniform motion of blood or tissue in a magnetic field gradient produces a change in the MR signal phase.
  • the fluid flow velocities produced by phase-contrast MRI are considered to be quite accurate. However, to obtain these velocities, it is necessary to adjust the MRI machine out of its standard scanning mode, and takes significant extra time on top of standard MRI procedures.
  • Phase-contrast MRI can also be susceptible to errors from magnetic susceptibility gradients and higher order motions, and it has little dynamic range. It also requires a significant computer processing overhead.
  • a method for analysing fluid flow, from fluid-sensitive images taken at two or more different times comprising:
  • Fluid-sensitive images are considered to be any images on which the motion of fluid can be detected, such as MR or ultrasound images.
  • the method may further comprise: (b) calculating a measure of non-linear fluid flow for one or more locations within the body, from the motion field.
  • the method may further comprise:
  • the method may also further comprise:
  • the method may be used to analyse fluid flow within a body - for instance, blood flow within a heart. Where portions of the images show the wall or substance of the body itself, and not the fluid being analysed, the images may be segmented to define the internal border of the body, in order to exclude the wall and substance of the body (rather than the fluid within) from analysis.
  • the measure of non-linear fluid flow may be displayed by superimposing a representation, of it, at its corresponding location, on one of the images. This may include a 'dot' of a specific intensity or of a specific colour (depending on the value of the measure). Furthermore, the motion field may be concurrently or separately superimposed on the image, with each point of the motion field being displayed at its corresponding location on the image.
  • the motion estimation algorithm may be an OF method that is based on, for instance, the Horn-Schunck algorithm, or a Lucas Kanade algorithm.
  • the present invention may be performed using other motion estimation algorithms such as the Block Matching method.
  • the motion field is a collection of velocity vectors at different points throughout the body. Usually, each of these points will correspond to a pixel of at least one of the images, and this would be typical of OF motion estimation algorithms. However, the present invention encompasses embodiments such as feature tracking wherein the motion field need not include a velocity vector for each and every pixel, to conserve computational load.
  • the measure of non-linear fluid flow may in some embodiments be calculated for all possible locations (depending on the resolution of the imaging modality) within the body. However, within the scope of the present invention, the measure may only be calculated for one location, or a small selection of locations within the body.
  • the points of the motion field are located in three dimensions within the body.
  • each of the velocity vectors can also be a three- dimensional vector, accordingly providing information about motion in three dimensions.
  • two-dimensional image slices of the body may be taken along orthogonal planes, resulting in multiple images at each of the two or more different times.
  • Applying a motion estimation algorithm to each image can result in two-dimensional velocity vectors for points along the plane of the image.
  • the orthogonal vectors at each intersection point can simply be added to produce a three-dimensional vector for that location. In this way, a three- dimensional motion field comprising three-dimensional velocity vectors can be reconstructed from two-dimensional images.
  • the measure of non-linear velocity may be calculated for locations spaced throughout the three dimensions of the body, from a three dimensional motion field.
  • the present invention involves the calculation of a measure of non-linear flow
  • the present invention is quantitative rather than simply qualitative.
  • Turbulence is also a type of non-linear fluid flow that may be quantified in accordance with the present invention - vorticity is one component of turbulence, but turbulence also comprises random or chaotic fluid flow.
  • a system for analysing fluid flow within a body comprising: a receiver to receive images of the body; and a motion estimation element to produce a motion field for fluid within the body by the application of a motion estimation algorithm to the images.
  • the system may further comprise: a calculating element to calculate a measure of non-linear fluid flow for at least one location within the body, from the motion field.
  • the system may further comprise a display element to display the measure of non-linear fluid flow.
  • the display element may be adapted to display a model of the body, the motion field (in two, three or four dimensions, as desired), and/or the calculated measure(s) of non-linear fluid flow.
  • a computer readable medium and computer program element for directing a programmable device to perform the steps of the above method is also provided.
  • the present invention has been designed for a particular application to the analysis of blood flow within a human heart, using images obtained from cardiac magnetic resonance (CMR) image scans, using standard cine-MRl procedures.
  • CMR cardiac magnetic resonance
  • the present invention therefore allows for post-processing of these MR images for non-linear blood flow quantification.
  • the results of the analysis could be used to assist in the diagnosis of various heart defects - non- linear or turbulent blood flow is believed to be implicated in the pathogenesis of several cardiovascular diseases.
  • the present invention could also be used to analyse fluid flow throughout the rest of the body, or in different species.
  • the present invention has clear applicability in relation to the design and testing of biomedical devices such as artificial hearts or mechanical heart valves.
  • the images analysed need not be obtained by MRI, and the present invention may use any imaging technology which is sensitive to the flow of the fluid to be analysed. Nonetheless, the use of MRI scans for flow visualisation is fast, non-invasive and unlimited by opacity of the body and its motion, and (for medical applications) has the advantage of using commonly available technology.
  • the intensity contrast of turbulent and laminar blood flow is a characteristic of certain types of MRI scans. This allows visualisation of blood movement, based on the shifting intensity in the image as a result of signal voids due to de-phasing of nuclear spins.
  • FIGURE 1 is a flow diagram showing the steps of a method according to an embodiment of the present invention
  • FIGURE 2 is a schematic depiction of MR images of a chamber of a human heart
  • FIGURES 3A and 3B are conceptual diagrams of pixel groups at two different times
  • FIGURE 4 is a schematic diagram showing a motion field and non-linear fluid, flow superimposed on one of the images shown in Figure 2;
  • FIGURE 5 is a schematic diagram showing a motion field superimposed on one of the images shown in Figure 2, in an alternative form
  • FIGURE 6 is a schematic diagram showing the slices of a set of MR images in orthogonal planes in three dimensional space
  • FIGURE 7 is a display of a three-dimensional motion field produced in accordance with an embodiment of the present invention.
  • FIGURE 8 is a flow diagram showing the steps in the process of producing the flow three-dimensional motion field of Figure 7;
  • FIGURE 9 is a histogram for the measure of non-linear fluid flow shown in Figure 8.
  • FIGURE 10 is a graph depicting the average measure of non-linear fluid flow calculated at different times.
  • FIGURE 11 is a system diagram showing a system according to an embodiment of the present invention. DETAILED DESCRIPTION
  • Figure 1 is a flow diagram showing the steps of a method according to an embodiment of the present invention.
  • the fluid to be analysed is within a body (particular reference is again made to blood within a heart).
  • Images 120 are first obtained 110 for two or mote different times, and if required these images are segmented 130 to exclude regions of the body from analysis.
  • a motion estimation algorithm is then applied 140 to the images, to produce a motion field 150 for the fluid within the body. From the velocity vectors in the motion field 150, measure(s) of non-linear velocity of the fluid 170 may be calculated 160. These calculated measures 170 may then be displayed 180, along with the motion field 150 itself and/or the images 120.
  • images 120 are required, and this embodiment of the present invention will be described with reference to CMR images.
  • the heart of a human subject may be scanned using standard MRI procedure to output intensity-based slices of the cardiac structure.
  • steady-state free precession cine-MR imaging can be performed using contiguous slices in short axis views through the heart.
  • Figure 2 shows schematic representations of MR images 120 showing the outline of a chamber (the right atrium) of a human heart, at four different phases of the cardiac cycle.
  • Digital images may be stored in any convenient image format (for example, a bitmap format).
  • the method of the present invention is amenable to post processing of images. That is, images 120 may already be in existence, or may be obtained elsewhere before analysis using the present invention. It will be appreciated that the present invention may be applied to different types of MR images, such as phase contrast, gradient-echo or tagged MR images. Furthermore, the present invention may be applied to many other types of fluid-sensitive images, such as particle image velocimetry (PIV) images.
  • PIV particle image velocimetry
  • an advantage of the present invention is that it uses intensity contrasts on standard MR images, and does not require the use of tagged MRI procedures.
  • the region of interest on the images 120 is then segmented 130, to exclude movement of cardiac tissue from analysis.
  • the present invention investigates fluid flow, rather than tissue movement.
  • the cardiac wall is segmented by placement of a two-dimensional contour that forms a computationally elastic wall within the cardiac chamber.
  • Active contouring computes a more accurate contour-line description iteratively by describing the contour as an energy function E contour . It receives information from the preceding contour line and applies energy balancing based on the internal and external energies of this line denoted by E int and E ext respectively to redefine the contour representation.
  • the fitting contour is one that corresponds to the minimum of this energy:
  • the initial curve can be anywhere in the image, and interior contours are automatically detected. In the event of poor segmentation due to over- expansion of the elastic contour the internal wall of the right atrium may manually traced. Because of the semi-automatic nature of this segmentation, contour tracing can be pre-processed.
  • a motion estimation algorithm is then applied 140 to these images 120 to estimate the motion of the fluid for various locations within the body, based on the differences in the images at different times.
  • the motion estimation algorithm may be applied to the two-dimensional image slices described above.
  • MR images are fluid sensitive; the intensity contrast of turbulent and laminar blood flow is a characteristic of certain types of MRI scans. This allows visualisation of blood movement, based on the shifting intensity in the image as a result of signal voids due to de-phasing of nuclear spins. Areas of high turbulence are darker on the MRI scans than areas of low turbulence.
  • Figure 3A and 3B show the operation of an optical flow algorithm.
  • the very simple image is divided into four quadrants or regions, wherein the bottom left region is darker than the other regions.
  • Figure 3B taken at a later time, the top right region is darker.
  • the object (or region representing turbulent fluid in the case of the present invention) causing the dark region is then taken to have moved diagonally across the image.
  • the optical flow algorithm may be applied to regions on various scales, ranging from a fine resolution (i.e. individual pixels) to a very coarse resolution (large region groups).
  • a fine resolution i.e. individual pixels
  • a very coarse resolution large region groups
  • Pixel intensity is denoted by I(x,y,t), Assuming spatiotemporal variation in intensity signal: Applying the chain rule for differentiation.,
  • optical flow constraint equation can be rewritten as:
  • the optical flow vector has two components v x and v y describing the motion of a point feature in x and y direction with the spatial gradient of intensity is denoted by . Therefore, the linearised version of the brightness constancy assumption yields the optical flow constraint:
  • the particular motion estimation method used in this embodiment is a pyramidal Lucas Kanade optical flow method which incorporates a multi-scale approach. This has been applied to support large blood motion and for improved accuracy.
  • a top-down estimation of the flow by using an image pyramid is performed, with the apex representing the CMR image at a coarse scale (useful for obtaining a global representation of fluid flow).
  • Computational results from this level are passed to the next and this process is carried on based on the flow estimated at the preceding scale until a base fine (e.g. individual pixel) resolution scale is reached.
  • This type of algorithm is described in J. Y. Bouguet, "Pyramidal implementation of the Lucas Kanade feature tracker", OpenCV documentation, Microprocessor Research Labs, Intel Corp., 2000.
  • the motion field may only include velocity vectors for these turbulent regions.
  • Figure 4 depicts in two dimensions a motion field for the MR images shown in Figure 2 (phase 8) .
  • the motion field is superimposed on a schematic diagram of the corresponding MR image 120.
  • the motion field 150 is produced by applying a pyramidal Lucas Kanade OF scheme to the images, as described above. It shows the flow patterns of blood in the right atrium at this phase.
  • the arrows 151 represent velocity vectors within the motion field. The length of the arrow corresponds to the magnitude of the velocity vector.
  • Figure 5 depicts an alternative way of displaying motion field 150, where the regions of high turbulence are shown as darker areas on the image 120.
  • the intensity of the region corresponds to the magnitude of velocity.
  • Three Dimensional Analysis Fluid flow is usually not limited to a single plane. Accordingly, for a more accurate analysis of flow within a heart, MRI slices from the axial, sagittal and coronal scans can be taken and constructed into a three-dimensional stack grid or scaffold 125 as shown in Figure 6. These planes intersect at different locations within the body. In Figure 6, the points of interception of the three image slices are represented by spherical anchor points 126. Note that the axial planes are hidden to reveal these points.
  • Figure 7 displays the motion field 150 comprising X, Y and Z velocity vectors from the interception points.
  • the three-dimensional velocity vectors comprise the sum of the orthogonal velocity component vectors in three-dimensional space through the intersection points of the slices. That is, for each interception point (shown by an anchor sphere 126), a resultant velocity . vector based on the addition of orthogonal velocity components from the two- dimensional slices can be computed.
  • FIG. 8 shows the procedure used in this embodiment to generate the three- dimensional motion field 150.
  • Three processing streams may be performed in parallel, for each of the axial 121, sagittal 122 and coronal 123 scans. These processing streams may be initialised by a parent process, which starts 101 the parallel processing option.
  • Each processing stream reads 131, 132, 133 the respective CMRI scans, and then analyses them on a phase-by-phase basis, for each phase of the cardiac cycle. Each iteration, it advances to the next phase 105, which initially will be the first phase. It then applies 142 a motion estimation algorithm to the respective scans, to produce an intermediate motion field 151, 152, 153 for the first phase.
  • the parallel processing will exit 102, having produced intermediate motion fields 151, 152, 153 for each phase shown in the CMR scans.
  • the parent process can then merge 143 these intermediate motion fields 151, 152, 153 adding the intermediate vector components to form a motion field 150 (for each phase).
  • This motion field 150 will comprise three dimensional velocity vectors for each intersection point, which are located in three- dimensional space - i.e. the resulting motion field 150 is therefore a three- dimensional motion field of three-dimensional velocity vectors, as shown in Figure 7.
  • the vorticity ( ⁇ ) represents the rotation of blood in the right atrium of the heart being examined in this embodiment.
  • the shear strain ( ⁇ ) represents the shear that the blood experiences.
  • the normal strain ( ⁇ ) determines pressure experience by the blood at local positions, which has some implications in strain of the bio-fluid.
  • the present invention may quantify non-linear blood flow by calculating the number and/or magnitude of vortices or areas of turbulence within the body.
  • the calculated measures 170 of non-linear fluid flow may be displayed to a user in many forms. They may, in one embodiment, simply be displayed by providing raw values or averages of the ⁇ , ⁇ or ⁇ measurements.
  • Figure 4 depicts another way of displaying the calculated measures.
  • an image 120 of the body (the right atrium of a human heart) is displayed (schematically in this instance).
  • Contours 171 are displayed on the image 120, showing regions of similar vorticity magnitude.
  • contours 171 could be used to show regions of similar shear or normal strain. This type of display enables easy observation of the centre of the dominant vortex.
  • Figure 9 shows a vorticity histogram. Where the vorticity has been calculated for many locations within the body, this histogram can give a guide as to the general spread of vortices within the body.
  • Figure 10 depicts a basic line graph of the average calculated vorticity, shear strain and normal strain within the heart, throughout different phases of the heart. In clinical diagnosis, this graph could be displayed for a given subject, and the shape of the graph compared to that of a healthy heart, to look for abnormalities.
  • the colour of a region superimposed on an image 120 may indicate the magnitude of the vorticity, and its direction - i.e. the colour may distinguish between clockwise rotation (e.g. red) and anti-clockwise morion (e.g. blue) of the blood.
  • the displayed information can of course be further processed and analysed for use in clinical diagnosis.
  • Figure 11 shows the operation of a system according to an embodiment of the present invention.
  • images 120 taken at two or more different times can be obtained by a magnetic resonance imager 210, or from a scanner 220 or disk drive 230. Regardless of how the images 120 are obtained, they are then received by a, receiver 240 residing in software on a processor. Where the images require segmentation, this can be performed by a segmentation element 250, to exclude non-fluid structures from analysis.
  • the segmentation element 250 may allow a user to assist in the segmentation process via an input device such as a keyboard 260 or mouse 270.
  • a motion estimation element 320 then applies a motion estimation algorithm to the images, to produce a motion field 150 for the fluid.
  • the motion field 150 may be displayed, along with the images 120, by a display element 280, which may communicate with a projector 290 or monitor 300 to display the motion field 150 and/or images 120 in the manner desired.
  • system may further comprise a calculating element 310 to calculate a measure 170 of non-linear fluid flow, for at least one location within the body, from the motion field 150. This measure may also be displayed by the display element 280.
  • the display element may be adapted to display the motion field and the measure(s) 170 of non-linear fluid flow in three dimensions.
  • Non-linear or turbulent blood flow is believed to be implicated in the pathogenesis of several cardiovascular diseases. Therefore, the results of analysis using the present invention may be useful in the diagnosis of myocardial abnormalities.
  • septal defect for example (which may be either ventricular or atrial)
  • oxygenated blood is forced from the left to the right side of the heart through a hole in the septum.
  • abnormal blood flow within the heart results in abnormal patterns of blood flow within the heart, which may be observed by the present invention, as for example described in Wong et al, "Motion Estimation of Vortical Blood Flow Within the Right Atrium in a, Patient with Atrial Septal Defect," 2007 IEEE/ICME Int. Conf. on Complex Med. Eng. (CME2007), (ISBN#1-4244-1078-9), Beijing, China, 23-27th May 2007, pp. 865-875.
  • abnormal blood flow patterns may also be caused by atherosclerosis and other cardiac or arterial diseases.
  • prosthetic valves which in turn can cause the formation of blood clots and stroke - meaning that recipients of these valves require lifelong courses of anticoagulant therapies.
  • the present invention could be used in the design and optimisation of prosthetic valves, and also to identify risks that may arise after heart valve transplants.
  • Another application may be to analyse a heart after cardiac surgery, to determine the surgical success for the patient and to aid management decisions in stabilising the cardiac condition.
  • Flow information generated by the present invention may be used to examine the amount of energy wasted by a heart that may need to pump blood through an abnormal heart valve to maintain the required human circulation.
  • the present invention offers potential for the non-invasive flow visualisation and quantification in cardiac structures such as in vivo natural and bio- prosthetic heart valves in a beating heart that changes its spatial position with time.
  • the present invention could be used to analyse blood flow throughout the rest of the body (e.g. in arteries, in particular atherosclerotic arteries), or in different species. It may be used to analyse other biological fluids, such as cerebrospinal fluid. It may even be used for general, non- biological applications where flow analysis is required, such as the analysis of fluid flow in mechanical engineering - for instance, the development of artificial hearts or prosthetic cardiac valves, the analysis of air flow in aeronautical engineering (e.g. reduction in turbulence of air flow over an aircraft structure), or fluid flow in ducts or pipes (e.g. optimising the efficiency of ink flow in printers).
  • the present invention may be applied to any of the areas that PIV is currently used in.
  • the method should not be limited to only include the use of the particular optical flow algorithm mentioned above, as there are other motion estimation algorithms that may also be appropriate.
  • the present invention can be implemented in numerous ways, including as a process, an apparatus, a system, or a computer readable medium such as a computer readable storage medium or a computer network wherein program instructions are sent over optical or electronic communication links. It should be noted that the order of the steps of disclosed processes may be altered within the scope of the invention.

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Abstract

Cette invention concerne un procédé et un système permettant d'analyser un débit de liquide à l'intérieur d'un corps, notamment le débit sanguin dans le cœur. Des images du corps sensibles aux liquides peuvent être obtenues à l'aide de divers mécanismes, tels que la technologie de l'imagerie par résonance magnétique (IRM). Un algorithme d'estimation de mouvement (tel qu'un algorithme de flux optique) est ensuite appliqué aux images afin de produire un champ de mouvement, lequel peut être utilisé par la suite pour quantifier le débit de liquide à l'intérieur d'un corps. En particulier, diverses mesures de débit sanguin non linéaires sont calculées, telles que la contrainte de cisaillement, la contrainte normale et le tourbillonnement, pour divers endroits à l'intérieur du corps. Ces données peuvent ensuite être présentées à un usager (tel qu'un cardiologue) par superposition de représentations des mesures calculées sur une image du corps.
PCT/AU2007/000827 2006-09-22 2007-06-15 Analyse de débit WO2008034164A1 (fr)

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Application Number Priority Date Filing Date Title
AU2006905231A AU2006905231A0 (en) 2006-09-22 Flow analysis
AU2006905231 2006-09-22
AU2007901700A AU2007901700A0 (en) 2007-03-30 Flow analysis (2)
AU2007901700 2007-03-30

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CN112568888A (zh) * 2020-12-08 2021-03-30 中国科学院深圳先进技术研究院 一种体内流体流动分析方法、系统、终端以及存储介质
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2742866B1 (fr) * 2009-09-16 2021-10-27 4DMedical Limited Vélocimétrie par image de particules appropriée à l'imagerie par projection de rayons X
EP2749223A4 (fr) * 2011-08-26 2015-08-12 Ebm Corp Système de diagnostic de caractéristiques d'écoulement sanguin, procédé afférent et logiciel informatique
US9814531B2 (en) 2011-08-26 2017-11-14 EBM Corporation System for diagnosing bloodflow characteristics, method thereof, and computer software program
CN112568888A (zh) * 2020-12-08 2021-03-30 中国科学院深圳先进技术研究院 一种体内流体流动分析方法、系统、终端以及存储介质
WO2022120761A1 (fr) * 2020-12-08 2022-06-16 中国科学院深圳先进技术研究院 Procédé et système d'analyse de circulation de fluide in vivo, terminal et support de stockage

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