CN1531904A - Method of operating imaging medical detection device - Google Patents
Method of operating imaging medical detection device Download PDFInfo
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- CN1531904A CN1531904A CNA2004100300657A CN200410030065A CN1531904A CN 1531904 A CN1531904 A CN 1531904A CN A2004100300657 A CNA2004100300657 A CN A2004100300657A CN 200410030065 A CN200410030065 A CN 200410030065A CN 1531904 A CN1531904 A CN 1531904A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/02—Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computerised tomographs
- A61B6/032—Transmission computed tomography [CT]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/46—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with special arrangements for interfacing with the operator or the patient
- A61B6/461—Displaying means of special interest
- A61B6/463—Displaying means of special interest characterised by displaying multiple images or images and diagnostic data on one display
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- 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
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
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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
- A61B5/05—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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10076—4D tomography; Time-sequential 3D tomography
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
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- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30048—Heart; Cardiac
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- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Abstract
This image forming medical inspection system is equipped with imaging units (3, 3A), data processing units (5, 5A), and image forming units (7, 7A). A raw image data set (3R) is measured by the imaging units (3, 3A) in a measuring cycle, a processing cycle, and an image forming cycle. The raw image data set (3R) is processed by the data processing unit (5, 5A) to be formed into image data set (5B). At least one segment data set (5S) is almost simultaneously calculated by a segmented algorithm. The segment data set (5S) represents spacial progress of a segment in an image data set (5B). The segment data set (5S) and the image data set (5B) are commonly displayed by image forming units (7, 7A). The displays are almost simultaneously carried out for the measurement and the data processing.
Description
Technical field
The present invention relates to a kind of method that is used for operation imaging medical examination apparatus in measurement, processing and an imaging cycle, this checkout facility has one and takes unit, a data processing unit and an image-generating unit.
Background technology
When utilizing the imaging medical examination apparatus to carry out the heart disease inspection, for example carry out so-called CINE-Studie (film-research) and measure, show the kinetics of heart with animation by the cardiac tomogram image.For this reason, on the workbench of oneself, a series of photos that for example utilize nuclear magnetic resonance equipment (MR equipment) to take are loaded in the data analysis and the poster processing soft on the work station that is installed in workbench.This data analysis and the poster processing soft automatically or semi-automatically for example carry out segmentation along the inside and outside profile comparison film of cardiac muscle.Bidimensional or three dimensional analysis are carried out in these segmentations, thereby the heart disease doctor obtains the kinetics physiological data of patient's heart.The heart disease inspection comprises the photo that obtains the patient on the one hand, comprises the secondary analysis of comparison film on the other hand.This secondary analysis quite expends time in and manpower.In most cases after leaving checkout facility, the patient just analyzes.If heart disease doctor checks again according to the definite needs of perform an analysis, then this means the medical examination of planning again and image.Concerning doctor, hospital and patient, do not only time-consuming but also expensive like this.
For utilizing the imaging medical examination apparatus to carry out vascular test (angiography), carry out same step.At first take the blood vessel data group by checkout facility.Then, after the patient leaves checkout facility, on the workbench of oneself, blood vessel data is loaded in another data analysis and the poster processing soft more mostly, so that for example diagnose by damaged (as the narrow or aneurysm) that quantize to form.Thisly be divided into two-part process equally---on checkout facility, measure and not only expended time in but also labor intensive in the enterprising line data analysis of own workbench.If check that the doctor analyzes definite needs according to it and checks that again so that for example stenosis is made detailed measurements, this means once more spended time and money equally for doctor, hospital and patient.
It is for example open by WO 02/093188 to be used for sectional method.Wherein introduced a kind of segmentation cardiac image that is used for, especially for propagating the method that (Konturpropagierung) comes the segmentation left ventricle by profile.
Summary of the invention
Therefore, the technical problem to be solved in the present invention provides a kind of saving time and carries out the method for imaging medical examination and analysis economically.
According to the present invention, above-mentioned technical problem is to be used in measurement, processing and an imaging cycle one of operation and to have a method of taking the imaging medical examination apparatus of unit, a data processing unit and an image-generating unit and solve by a kind of: wherein at first utilize and take unit measurement image original data set; By data processing unit original data set is processed into image data set then, and side by side at least one segment data group is calculated basically, wherein said calculating is finished by segmentation algorithm, described segment data group has been described a sectional spatial variations, especially its profile and/or change in volume in the image data set; Show described segment data group and image data set together by image-generating unit at last, wherein said demonstration is finished simultaneously with measurement and date processing basically.
The advantage of said method is to utilize the data processing unit of checkout facility to analyze with online (inline) mode comparison film.Herein, be interpreted as data are handled rather than post processing immediately, that is to say that online technology is illustrated in the image reproduction period and handles in real time for online (online technology).This means that the processing of view data is finished at image computer or in the computer of for example control survey heart photo, thereby can after and then measuring, diagnose or plan subsequent examination immediately.This can realize, because in measurement, processing and imaging cycle view data is analyzed.By providing the important information of image data set to extract (extrahiert) form, for example sectional spatial variations, the availability of the segment data group of Chan Shenging also has another advantage at this moment: only need seldom additional storage medium for calculating and store these information.
Another advantage is, the doctor who checks is according to on-line processing, for example the shrinkage by heart or obtain information through visualization processing immediately by other parameter of describing the patient physiological state.Like this, for example can be by the information of the acquisition of segment data group as beat amplitude (Schlagvolumen), ejection fraction (Auswurffraktion) or cardiac mass (Herzmasse).
Another advantage is, can utilize one for example to compare the analysis software that significantly reduces with the poster processing soft with analysis and diagnose.At this moment, for example in cardiology, no longer check and analyze, but check independently by the cardiology doctor by the radiologist, and the follow-up measurement of plan under may situation.Thereby such inspection and analysis also adapt to the requirement of cardiology except gaining time.
In a particularly preferred embodiment of the inventive method, the operator of this checkout facility can be enabled in second measurement, processing and the imaging cycle that is right after phase the last week on the time according to the demonstration on the image-generating unit.Herein, " being right after in time " is interpreted as and also will be used to clarify the follow-up measurement (Folgemessung) of the problem that may occur during once checking, thereby need not to readjust the patient, the preparation of checking.This has obviously accelerated the processing to the patient.Thereby this embodiment of this method has the following advantages: also finished this subsequent examination except analyzing and planning the subsequent examination.This has been avoided unnecessary repeated measurement, has significantly improved the efficient of checking workflow.For example, the total residence time of patient in imaging checker shortened greatly.
In another embodiment, the sectional geometry of being described by described segment data group is analyzed,, and be shown as figure or table by image-generating unit so that calculate especially in time or spatial change in volume and/or absolute volume size.Have the following advantages like this: can make on-line analysis and the doctor's that implement to check different demands harmonious, (heart-penetrate blood-mark, myocardial mass, diastole and systaltic amplitude, pollex amplitude, heartbeat efficient, maximum ejection rate, peak filling rate, reach maximum and penetrate the time of blood, heart rate thereby directly present important medical treatment and physiological parameter visually to this doctor ...).
In another embodiment, just all the last part of calculating of operational segment data group or this segment data group is visual together with image data set during carrying out segmentation algorithm.This make have advantage, provide the demonstration of information to become possibility immediately by on-line analysis.
Produce a plurality of two dimensions (2D) image data set in another particularly preferred embodiment, the segment data group of spatial variations characteristic under it, that characterize specific type of tissue is utilized by the processing unit piecewise and is implemented measurement, processing and imaging cycle and be combined into a three-dimensional and/or reproduce three-dimensional (3D) the segment data group of this tissue with the time relevantly.This has the following advantages: owing to showing dynamically or spatial relationship has been improved diagnosis.Such 3D segment data group can process and display easily, is data set extremely compression, that require the store little device because it is compared with image data set.Thereby can for example rotate the such quick operation of perspective.
In a preferred embodiment, image data set is the three-dimensional data group, especially the three-dimensional data group that produces by the angiographic measurement of CT or MR equipment.
In a preferred embodiment, select a blood vessel as segmentation by segmentation algorithm, described segment data group has especially been described this angiocentric variation and/or its especially relevant with direction radius.
In a preferred embodiment, the maximum and/or the minima of the labelling radius relevant in demonstration with direction.
In a preferred embodiment, specific type of tissue is interior cardiac muscle and/or outer cardiac muscle.
In a preferred embodiment, the 2D image data set is combined into a 3D rendering data set that shows with 3D segment data group.
In a preferred embodiment, image data set that accompanies before and after will the time going up and/or the segment data group that belongs to this image data set are visual with the film display mode.
Description of drawings
Describe below in conjunction with Fig. 1 to 11 pair of a plurality of embodiments of the present invention:
Fig. 1 carries out the sketch map of human computer conversation's probability for explanation method of the present invention and doctor;
Fig. 2 is the general picture figure that is used to implement the imaging medical examination apparatus of the inventive method;
Fig. 3 is the image during the heartbeat that shows by display unit, wherein a) schematically segmentation MR photo, the b of expression cardiac muscle) 3D segment data group and c described) shown myocardium diameter over time;
Fig. 4 represents the image of the myocardial contraction situation that gone out by the 3D Model Calculation;
Fig. 5 has described the vascular tree (Gef β baum) when segmentation begins;
Fig. 6 has described the vascular tree when continuing segmentation;
Fig. 7 has described the vascular tree of finishing after the segmentation;
Vascular tree when Fig. 8 has described a kind of segmentation that can follow segmentation algorithm particularly well and begins;
Fig. 9 has described the vascular tree with two labellings;
Figure 10 is used for illustrating the structure of segment data group in the angiography;
Figure 11 has provided the relation of branch vessel radius and blood vessel course among Figure 10.
The specific embodiment
Fig. 1 shows the sketch map that is used to illustrate method of the present invention.Imaging medical examination apparatus 1 comprises that one takes unit 3, a data processing unit 5 and an image-generating unit 7.This checkout facility for example can be nuclear magnetic resonance equipment, computer tomograph or ultrasonic instrument.In addition, one side shows the doctor 9 who is responsible for this inspection among Fig. 1, shows on the other hand to be used to represent that each unitary relation and doctor 9 carry out the arrow of human computer conversation's probability.
Utilize shooting unit 3 to carry out for example two dimension or three-dimensional measurement, this measurement sends to processing unit 5 with the form of original data set 3R.Processing unit 5 for example comprises metering computer and/or special-purpose pattern process computer.There original data set 3R is scaled image data set 5B, and simultaneously it is carried out data analysis.At this, this analysis is undertaken by one or more segmentation algorithms specific, that for example discern MR photo midplane structure.Obtain one with of the segmentation of its geometry by this algorithm, for example by obtaining the method on border (R nder) as segment data group 5S.When segmentation, can consider different input parameters.For example algorithm can adopt a plurality of canonical parameters that for example comprise that this treats sectional identical value or segmentation starting point in first kind of scheme.
Utilize the image-generating unit 7 on the one hand can image data set 5B and/or all is visual to the measurement general picture of being carried out at this moment.The segment data group 5S that can show generation in addition.For example, doctor 9 can revise initial parameters after showing the segment data group 5S that at first calculates, thereby all segmentation algorithms of proceeding are all with amended parameter operation.
Segment data group 5S can be shown as two dimension, also can be shown as three-dimensional when having a plurality of photo.In addition, the data analysis that for example can also utilize image-generating unit 7 to show to segment data group 5S.
Support to patient diagnosis is provided from the visual information that provides to him doctor 9 who accompanies inspection.He can measure the continuation that will carry out in identical inspection position and adjust possible measurement parameter simultaneously.Except segmented mode was exerted one's influence, doctor 9 can also select display mode.
Fig. 2 is example explanation this method with MR equipment 11.This equipment has the shooting unit 3A that for example comprises main field Magnet and transmission and reception antenna.Placing crouches, and collapse patient 13 on 15 is admitted to the shooting area of MR equipment 11.Patient 13 MR photo is converted to image data set by graphics processing unit 5A.Utilize one or more segmentation algorithms from this image data set, to produce the segment data group.This image data set and segment data group are shown by the image-generating unit 7A with screen.Doctor 9A can diagnose by the demonstration of MR photo, or whether decision needs to do further to measure for diagnosis.At this, this demonstration can provide at medical practitioner, for example cardiology doctor.So just cancelled the intermediate link of at first data that obtained being handled by the radiologist.
Therefore, a very big advantage of the inventive method is, the doctor knows as the measurement result relevant with patient physiological with on-line mode after checking immediately, for example with 3D model, figure and/or table illustrate measurement result (the contraction situation of heart, volume data ...).This just finishes when the patient also lies low in checkout facility.Independently carry out the process (Vorgehensweise) that data analysis handles checking for common, this method has the following advantages: patient 13 location only need be carried out once, repeatedly the workflow of Jian Chaing has obtained optimization, and patient 13 is reduced to minimum the time of staying in checkout facility 11.
Multiple segmentation algorithm can be integrated in the date processing, so that for example shape (Formen) and Strength Changes are carried out segmentation.Corresponding algorithm and parameter thereof can be used for repeatedly taking, and that is to say, these algorithms and parameter thereof can be used each image data set, thereby image data set is carried out consistent processing.The algorithm that is used to search profile can for example carry out automatically, also can need additional input.
The following describes three kinds of situations that may be used to obtain left ventricle or right ventricle lattice structure (Gitterstruktur) form 3D model.
First kind of situation (Szenario) described the segmentation that utilizes heart minor axis cross section and implemented and the automatic heart 3D model that produces.At this, the first minor axis cross section of heart is measured as " film-research ".That is to say that take circular myocardium cross section with time series, this sequence can be play as image sequence on the monitor of display unit.In " film-research " of this two dimension, as can be seen should the cardiac muscle ring how smoke tight and lax in the diastole stage in the contraction phase.At this moment, the demonstration of " film-research " is corresponding to locating as display graphics tomography when implementing the MR measurement.
For " film-research " carried out in segmentation, the doctor clicks the cardiac muscle middle part when showing myocardium cross section, starts a kind of like this segmentation and profile inner around cardiac muscle or that cardiac muscle is outside and describes.Perhaps utilize to measure and carry out segmentation automatically, wherein with the basis of standard initial parameter as this algorithm.The profile that produces is like this offered doctor's reference.He can accept this profile or proofread and correct as required.Also during measuring or with demonstration, simultaneously all MR photos of " film-research " are finished the segmentation algorithm of this approval, thereby can be transmitted this profile, and be reflected in this " film-research " at all heart states.
Other minor axis cross section of this heart of doctor measuring wherein also is applied to segmentation algorithm in the MR photo of this " film-research " as " film-research ".Provide and comprise heart and corresponding MR photo with the profile that centers on cardiac muscle.
Except two dimension shows the cross section, set up the 3D model of heart concurrently, and in a window of monitor, show.The 3D model progressively is made of the profile that produces gradually, up to revealing whole left ventricle or right ventricle again.Its space power that cardiac activity is shown is on the one hand learned, and its time kinetics is shown on the other hand.
Under certain condition, its advantage is: take away if measured MR photo can be added in the 3D model or from the 3D model, so the doctor can testing model and the concordance of measurement.
In second kind of situation, utilize a plurality of minor axises and major axis cross section to produce the 3D model semi-automatedly.These cross sections are the myocardium cross section of circle or Horseshoe.In the 3D " " that is constituted as can be seen the cardiac muscle kinetics.Corresponding with first kind of situation, the doctor starts segmentation and profile inner around cardiac muscle and that cardiac muscle is outside and describes by click the middle part of cardiac muscle ring at least one width of cloth minor axis cross-sectional image.Then, automatically propagate the profile that produces so once more at all heart states in minor axis cross section.
When the major axis cross section of segmentation heart, the doctor clicks the inner outline and the outer contour of cardiac muscle, so that the point of visable representation is set.He repeats this hand labeled to a plurality of time points with different major axis cross section.
To be combined into a 3D model according to the segment data of major axis cross section and the acquisition of minor axis cross section concurrently with measurement once more, this model is formed gradually by the profile that produces and the point in major axis cross section, up to revealing whole left ventricle or right ventricle again.Here, in order to check this model also can compare with the cross section of measuring.
The third situation explanation manually is that main segmentation starts.This mode especially has advantage in ultrasonic examination.Once more a plurality of minor axises and the major axis cross section of heart are measured as " film-research ".The doctor to a plurality of time points in the mode got ready the not only inside and the exterior contour of mark cardiac muscle in the major axis cross section but also in the minor axis cross section.
In a split window once more with measure the segmentation that shows concurrently as the heart 3D model that can be complementary with this measurement.
For what all three kinds of situations all were suitable for be, the 3D model of heart is by successive measurement and indicate profile and constitute, and can for example show the time dependent volume curve of heart size during the reflection heartbeat in another window.This volume curve changes during measuring, because as long as for example photograph the profile in another cross section in the 3D model or manually change the 3D model, this curve will be brought in constant renewal in.
The advantage that heart minor axis cross section and major axis cross section are made up is: only need less measurement just be enough to produce the 3D model based on orthogonal cross-sectional image.But this 3D model is more rough through the measurement of Accurate Analysis than minor axis cross section, and with a large amount of conditions that additionally is input as, but enough mostly concerning cardiopathic resolution.
Fig. 3 explanation is especially changing the layout of making the different display modes that may carry out when geometry is analyzed in time to measured value when the 3D three-dimensional.In this embodiment, viewing area (being presented in the window of MR, CT or US display unit) is divided into 3 parts, wherein schematically shows the minor axis cross section 19 of heart among the image-region A of on the left side.Only taken important myocardium physiological structure in the figure.In addition, the segmentation of the cardiac muscle 21 that annular is changed shows simultaneously with in this case minor axis cross section 19.In cardiac muscle 21, have the doctor of being used for and start sectional click-point 23.This segmentation is represented by cardiac muscle 21 two annulus wheel profile 25A, 25B outside and myocardium 21 inside.Cardiac muscle has thickness D in the position by the arrow indication, and it can calculate according to this segment data batch total.
The heart 3D model 25 that has shown an online calculating in intermediary image-region B has marked the minor axis cross section 19 that left image zone A shows in this model.This 3D model 25 is based upon on the basis of the minor axis cross-sectional image of this heart of segmentation automatically or semi-automatically and/or major axis cross-sectional image, and for example is made up of contour line 25A, the 25B in a series of minor axises cross section of this heart.This 3D model 25 can be shown as with the active 3D of animation mode reflecting myocardium " film-research ".
Shown the time dependent curve of the myocardial thickness D that calculates among the image-region C on the right, this thickness is at the relaxing period thickening, in systolic thinning.
Fig. 4 shows the data analysis C` as a result that another kind can be used to represent the segment data group in this minor axis cross section 19.At this, the activity of segmentation calculating myocardium 21 (form with target shows).The percentage rate that given each section myocardial thickness changes can be represented with additional colour code mode.
Usually can carry out on-line analytical processing to the shrinkage of each tomography cardiac muscle by this 3D model.In addition can other physiological data of online calculating, for example be described in the volume curve of the myocardium dynamic performance in the whole cardiac cycle.These data can for example offer the doctor with the form of showing in the window in MR, CT or US display unit.
Be that example (especially those with the space size is carried out geometry analyze relevant situation) is discussed method of the present invention below with the angiography.Can detect and mark form in people's the vascular system damaged automatically by this method.This detection is online finishing, and promptly and then measures and carries out after the blood vessel data group, and be not or have under the situation of user's input and finish.
This method for example allows automatically to be determined by the defective that forms immediately and show stenosis or aneurysm size after measuring.At this moment, for example in a subregion of image-generating unit monitor, show three-dimensional blood vessel data group.In another subregion, belonging on the damaged segment data group and damagedly to make the visible marking what form.In the 3rd subregion, for example narrow/aneurysmal analysis result is made an explanation by the numerical value that is calculated (diameter).
According to the present invention, vascular system has been carried out automatic segmentation at a certain computer of graphics processing unit or on the metering computer of control angiographic measurement.In most cases need the doctor to import and which blood vessel to carry out segmentation to.Selection to blood vessel is for example finished by measuring for the first time.
In order to make the doctor can follow sectional process, for example only show vascular tree by sectional part, perhaps last sectional part is at that time highlighted it with the variation of blood vessel is for example colored.Reflect that may there be angiostenosis in the position that blood vessel diameter shrinks.Reflection blood vessel diameter thickening and and the position that narrows down may have an aneurysm.
In order to indicate narrow or aneurysm, make chromatic fixation mark respectively in described position.Thereby these labellings are informed the doctor, and may there be deformity in which position in the vascular system.The vascular tree of making this labelling can be presented in the subregion as described above, and compares with primary vascular tree measurement.
If the doctor clicks this labelling, then can in another subregion, show stenosis or the aneurysm size of this position through calculating.Perhaps, begin to carry out another time this marked region is done the more measurement of high resolution shooting.Method of the present invention helps doctor's diagnosis.In addition, he can plan and implement further inspection immediately after possible narrow or aneurysm is quantized.
The segmentation of Fig. 5,6 and 7 pairs of vascular trees 41 is illustrated.Fig. 5 shows the initial situation of fragmentation procedure.Starting point 43 beginnings that this segmentation is provided with during for example each a mouse click during measure showing from the doctor.Segmentation algorithm by the pixel that belongs to this main blood vessel (Pixel), comparable, higher intensity identifies the variation of main blood vessel 47 in this case.
Fig. 6 has described the fragmentation procedure in the later moment.Segmentation algorithm has identified the branch location 45 of this vascular tree 41, follows main blood vessel 47 on the one hand now, follows branch vessel 49 on the other hand.
Fig. 7 is corresponding to the three dimensional display of finishing behind the areal survey.Whole blood vessel changes by algorithm identified, and use with the form of segment data group this moment.Calculate the position 50A that blood vessel narrows down or identify possible aneurysm 50B by the segment data batch total quite easily.
The another kind of display mode that can follow fragmenting process has been shown among Fig. 8.At this moment, move along main blood vessel 47 from starting point 43 in a zone that highlights 51.This zone 51 is limited in the last segment data group part of calculating.Corresponding having obtained should zone 51 proal impression in vascular tree 41.This regional split becomes two parts at vessel branch 51 places.A part is followed main blood vessel 47, and another part is followed thinner blood vessel 49.The advantage of this display mode is that the dynamic of fragmentation procedure clearly has been described.The special character of blood vessel diameter (stenosis, aneurysm) shows (referring to Fig. 9) with fixation mark 51A, 51B in the vascular tree.
Figure 10 has illustrated the topology example of the segment data group in the angiography.This segment data group comprises the center line 57,59 of all segmentation blood vessels 47,49 and the radius 61,63 of blood vessel 47,49 on the one hand.This radius for example or relevantly with direction or as mean radius is stored with maximum and minima that the blood vessel that is checked through changes.In addition, in the segment data group, mark position X0, the X1 that occurs deviation in the variation of record blood vessel.
Figure 11 shows the change curve of branch vessel 49 mean radius R.This radius R has minima at the X0 place.When for example can being positioned at the labelling at X0 place in clicking the 3D model, this change curve shows by display unit.
Claims (13)
1. method that is used to move imaging medical examination apparatus (1,11), this equipment have one take the unit (3,3A), data processing unit (5,5A) and image-generating unit (7,7A); This method has following method feature in measurement, processing and an imaging cycle:
-utilize described shooting unit (3,3A) measurement image original data set (3R),
-by described data processing unit (5,5A) original image data group (3R) is processed into image data set (5B), and by segmentation algorithm at least one segment data group (5S) is calculated simultaneously basically, wherein this segment data group (5S) has been described sectional spatial variations in the image data set (5B), especially its profile and/or change in volume
-by image-generating unit (7,7A) show described segment data group (5S) and image data set (5B) together, wherein said demonstration is finished simultaneously with measurement and date processing basically.
2. in accordance with the method for claim 1, it is characterized in that: the operator of described checkout facility (1,11) (9,9A) can (7,7A) demonstration on be enabled in second measurement, processing and the imaging cycle that is right after phase the last week on the time according to described image-generating unit.
3. it is characterized in that in accordance with the method for claim 1: described segmentation algorithm is selected a relevant segmentation can compare signal intensity in described image data set (5B).
4. in accordance with the method for claim 1, it is characterized in that: the sectional geometry of being described by described segment data group is analyzed, so that calculate especially in time or spatial change in volume and/or absolute volume size (D, D (tA)), and by described image-generating unit (7,7A) be shown as figure (C, C`) or the table.
5. in accordance with the method for claim 1, it is characterized in that: during carrying out described segmentation algorithm, will be all the part calculated at last of operational segment data group (5S) or this segment data group (5S) visual together with described image data set.
6. in accordance with the method for claim 1, it is characterized in that: described image data set (5B) is the three-dimensional data group, especially the three-dimensional data group that produces by the angiographic measurement of CT or MR equipment (1).
7. in accordance with the method for claim 1, it is characterized in that: select a blood vessel as segmentation by described segmentation algorithm, and described segment data group (5S) has especially been described this angiocentric variation and/or its especially relevant with direction radius (R).
8. it is characterized in that in accordance with the method for claim 1: the maximum and/or the minima of the described radius (R) relevant of labelling in described demonstration with direction.
9. in accordance with the method for claim 1, it is characterized in that: finish a plurality of measurements, processing and imaging cycle, these produce the 2D image data set (5B) of following mutually on a plurality of that displacement spatially arranged and/or times in cycles.
10. in accordance with the method for claim 1, it is characterized in that: the segment data group (5S) that belongs to described 2D image data set (5B) characterizes specific type of tissue (21,41) spatial variations characteristic, and utilize to implement measurement, processing and imaging cycle by described processing unit piecewise and be combined into a three-dimensional and/or reproduce the 3D-segment data group of this tissue (21,41) relevantly with the time.
11. in accordance with the method for claim 1, it is characterized in that: described specific type of tissue (21,41) is interior cardiac muscle and/or outer cardiac muscle (21).
12. it is characterized in that in accordance with the method for claim 1: described 2D image data set (5B) is combined into a 3D rendering data set that shows with described 3D segment data group.
13. it is characterized in that in accordance with the method for claim 1: image data set (5B) that will accompany before and after will going up the time and/or the segment data group (5S) that belongs to this image data set (5B) are visual with the film display mode.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE10312193A DE10312193A1 (en) | 2003-03-19 | 2003-03-19 | Operation of a medical diagnostic imaging unit, especially a computer tomography or magnetic resonance imaging instrument, whereby image data and segment data sets are processed and presented simultaneously |
| DE10312193.5 | 2003-03-19 |
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| Publication Number | Publication Date |
|---|---|
| CN1531904A true CN1531904A (en) | 2004-09-29 |
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| CNA2004100300657A Pending CN1531904A (en) | 2003-03-19 | 2004-03-18 | Method of operating imaging medical detection device |
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| JP (1) | JP2004283583A (en) |
| CN (1) | CN1531904A (en) |
| DE (1) | DE10312193A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107072531A (en) * | 2014-05-06 | 2017-08-18 | 塞克利心血管成像股份有限公司 | Method and system for the dynamic (dynamical) analysis of myocardial wall |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102006002259A1 (en) * | 2006-01-17 | 2007-07-19 | Siemens Ag | Heart blood vessel examining method for cardiac infarction patient, involves generating signals based on sequence of determined blood vessel diameters, where change of blood vessel diameters is observed by signals |
| EP1913868A1 (en) * | 2006-10-19 | 2008-04-23 | Esaote S.p.A. | System for determining diagnostic indications |
| EP1913869A3 (en) | 2006-10-19 | 2008-12-10 | Esaote S.p.A. | Diagnostic imaging method and apparatus for the anatomical region of the pelvic floor |
| DE102007024154A1 (en) | 2007-05-24 | 2008-11-27 | Siemens Ag | Method for automatic selection of a display mode for an image data record of an organ to be examined |
| US8103070B2 (en) * | 2007-11-22 | 2012-01-24 | Toshiba Medical Visualization Systems Europe, Limited | Volume rendering apparatus and method |
| JP2009261651A (en) * | 2008-04-25 | 2009-11-12 | Johns Hopkins Univ | Image processing apparatus and program |
| DE102010009701A1 (en) * | 2010-03-01 | 2011-09-01 | Siemens Aktiengesellschaft | Method for automatically identifying narrow points of coronary blood vessel in heart of patient, involves identifying narrow points in hollow vessel based on automated evaluation of profile course curve of hollow vessel |
| US9974442B2 (en) | 2013-06-24 | 2018-05-22 | Toshiba Medical Systems Corporation | Method of, and apparatus for, processing volumetric image data |
| EP3503026A1 (en) * | 2017-12-20 | 2019-06-26 | Koninklijke Philips N.V. | Device, system and method for interacting with vessel images |
Family Cites Families (2)
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| EP0668570B1 (en) * | 1994-02-16 | 2001-09-26 | Koninklijke Philips Electronics N.V. | Image processing method for locally determining the center and half-length of contrasting objects on a background and apparatus to carry out the method |
| US6487432B2 (en) * | 2000-12-04 | 2002-11-26 | Ge Medical Systems Global Technologies Company Llc | Method and system for selecting and displaying medical image data |
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- 2004-03-18 CN CNA2004100300657A patent/CN1531904A/en active Pending
- 2004-03-18 JP JP2004078482A patent/JP2004283583A/en not_active Withdrawn
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107072531A (en) * | 2014-05-06 | 2017-08-18 | 塞克利心血管成像股份有限公司 | Method and system for the dynamic (dynamical) analysis of myocardial wall |
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| Publication number | Publication date |
|---|---|
| JP2004283583A (en) | 2004-10-14 |
| DE10312193A1 (en) | 2004-09-09 |
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