CN108805947A - PET data processing method and equipment, PET imaging systems - Google Patents
PET data processing method and equipment, PET imaging systems Download PDFInfo
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Abstract
The disclosure relates in one aspect to a kind of PET data processing method, including obtains the PET data of subject's body part；The PET data is rebuild to obtain the PET image of body part, and obtains decaying image corresponding with the PET image in the reconstruction process of the PET data；Processing is split to the decaying image and obtains segmentation result；Specific organization is determined according to the segmentation result；Calculate the weight of the feature organization；And based on the calculated specific organization weight and the PET image determine SUL values.Present disclosure also relates to corresponding equipment.
Description
Technical field
The present disclosure relates generally to the calculating of standard uptake value (SUV), more particularly to calculate SUL based on PET data information
(standard uptake value of lean body mass) value.
Background technology
SUV is most widely used semiquantitative index in PET imagings, it is that the radioactivity derived from PET image is dense
The ratio between degree and injected radioactive concentration.The calculation formula of SUV generally can be as follows：
Wherein, SUV (t) can indicate the SUV values of moment t；C (t) be image in it is corrected after PET image image pixel intensities
Value；Dose represents injection dosage；Weight represents weight.
The calculation formula of this index has used the total weight for not considering fat ratio as input.However, same physiology shape
Under state, uses SUV calculation formula to make PET and adiposis patient is quantitatively made to there is the higher of entirety compared with the SUV of normal patient.Therefore,
The general calculation formula is not very applicable in adiposis patient.It is quantitative not accurate enough to solve adiposis patient SUV, keeps same physiology shape
The group of state crowd quantifies the major issue that consistency is prior art PET imagings.
Invention content
The disclosure relates in one aspect to a kind of PET data processing method, which is characterized in that including：Obtain subject's body
The PET data at position；The PET data is rebuild to obtain the PET image of body part, and in the reconstruction of the PET data
Decaying image corresponding with the PET image is obtained in journey；Processing is split to the decaying image and obtains segmentation result；Root
Specific organization is determined according to the segmentation result；Calculate the weight of the feature organization；And based on the calculated spy
The weight and the PET image for determining tissue determine SUL values.
The nonlimiting examples according to another exemplary, this method further include being determined according to the result of the segmentation
Before the weight of specific organization, the segmentation result is modified at least one of in the following way：It declines described in acquisition
Subtract the Atlas templates of image, and the pixel in the segmentation result is divided using the Atlas templates of the decaying image
Class；Alternatively, carrying out denoising to the pixel in the segmentation result.
The nonlimiting examples according to another exemplary are split processing to the decaying image and obtain segmentation result
Including：Pixel value in the decaying image is counted to determine the boundary of Different Organs.
The nonlimiting examples according to another exemplary, subject's body part further includes fat, the segmentation
As a result include the boundary on the boundary and non-fat region of fat region, the specific organization corresponds to fat region.
According to further exemplary embodiment, the SUL values are the corresponding SUV values of destination organization, based on calculated
The weight of the specific organization and the PET image include to determine SUL values：Determine the quality of subject's body part；
The weight of destination organization is determined according to the weight of the quality of subject's body part and the specific organization；Based on described
The weight of PET image, the injection dosage of contrast agent and the destination organization determines SUL values.
Another aspect of the present disclosure is related to a kind of PET data processing equipment, which is characterized in that including：It is examined for obtaining
The device of the PET data of person's body part；For rebuilding the PET data to obtain the PET image of body part, and described
The device of decaying image corresponding with the PET image is obtained in the reconstruction process of PET data；For to the decaying image into
Row dividing processing obtains the device of segmentation result；Device for determining specific organization according to the segmentation result；Based on
Calculate the device of the weight of the feature organization；And for based on the calculated specific organization weight and the PET
Image determines the device of SUL values.
The nonlimiting examples according to another exemplary obtain segmentation for being split processing to the decaying image
As a result device includes the device for being counted the boundary to determine Different Organs to the pixel value in the decaying image.
According to another exemplary, nonlimiting examples, the SUL values are the corresponding SUV values of destination organization, are used for base
Include to determine the device of SUL values in the weight of the calculated specific organization and the PET image：For determine it is described by
The device of the quality of inspection person's body part；For the weight according to the quality and the specific organization of subject's body part
Determine the device of the weight of destination organization；For based on the PET image, contrast agent injection dosage and the destination organization
Weight determines the device of SUL values.
The another further aspect of the disclosure is related to a kind of PET imaging systems, including：One or more processors；Memory；With one
A or multiple programs, wherein one or more of programs be stored in the memory and be configured as by one or
Multiple processors execute, and one or more of programs include the instruction for being operated below：Obtain subject's body
The PET data of position；The PET data is rebuild to obtain the PET image of body part, and in the reconstruction process of the PET data
It is middle to obtain decaying image corresponding with the PET image；Processing is split to the decaying image and obtains segmentation result；According to
The segmentation result determines specific organization；Calculate the weight of the feature organization；And based on the calculated specific group
The weight and the PET image knitted determines SUL values.
The disclosure yet another aspect relates to a kind of computer readable storage medium of the one or more programs of storage, described one
A or multiple programs include instruction, and described instruction realizes the either method in method as described above upon being performed.
Description of the drawings
Fig. 1 shows the method according to an exemplary embodiment of the invention.
Fig. 2 shows the equipment according to an exemplary embodiment of the invention.
Fig. 3 shows the PET imaging systems according to an exemplary embodiment of the invention.
Specific implementation mode
The SUV calculation formula such as the prior art of formula (1) etc are used inevitably to make adiposis patient and same life
The Group Consistency of reason state deviates larger.This is because contrast agent is generally gathered in non-fat tissue.Therefore, if injection
Same dose, for two patients of identical lean body mass (that is, total weight-fat weight), identical non-fat tissue
The activity C (t) of (such as liver) is also similar.However, adiposis patient weight bigger, this will eventually lead to adiposis patient liver
SUV values it is higher.
Therefore some scholars think weight being changed to " muscle weight " or " body surface area " more particularly suitable.Because a large amount of
Fat does not absorb PET contrast agent substantially, so being incorporated in the calculation formula of SUV and unreasonable.There is document table
Bright, use " muscle weight " to calculate the SUV values obtained has smaller group's variance in group experiment, thus quantitative to group
It studies more valuable.
In order to calculate " muscle weight ", academia proposes some common methods.It is a kind of feasible in PET/CT scannings
Scheme be that the pixel values of the CT images used distinguishes muscle, fat, bone, thereby calculate the gross weight of fat and will
It is deducted from total weight.However, the case where CT image sections are usually present missing in PET/CT scannings, this kind of method calculates
There are deviations for obtained muscle weight and actual value.Another kind feasible scheme in PET/MR is sweeping by Dixon sequences
Retouching the separation of progress water fat, (technology is proposed by Dixon, mainly using chemical shift effect in regular spin echo sequence basis
On, by adjusting the different echo times, the arbitrary angle of water and fatty two magnetization vectors is accurately obtained in theory.Point
Not Cai Ji water and fatty angle be 0 ° image and angle be π image, then by calculating from two width magnetic resonance (MR) images
Obtain water and fat image), and then body fatty ratio everywhere is calculated, and thus estimate the content of body fat.However, base
Fat ratio illustration can not be accurately obtained in the fatty method of estimation of Dixon sequence images, is existed to the estimated accuracy of fat weight
Problem.
Present invention seek to address that PET/CT scanning in CT excalations or PETMR scanning in Dixon sequence images without
When method accurately obtains fat ratio illustration, to the estimation problem of fat weight.Certainly, the invention is not limited thereto, but also can be
PETCT can calculate fat weight using CT images in scanning and/or can be by Dixon retrieval fat ratios in PET/MR
In the case of example, fatty estimation means as an alternative or supplement use.Specifically, one of the basic ideas of the present invention can
Including the use of such as TOF-PET data itself institute information, the decaying image of PET imagings is rebuild, and by reconstructing
Decaying image Fat Distribution/accounting is estimated.If those of ordinary skill in the art are illustrated, although being with PET below
For the embodiment of the present invention is described, but the solution of the present invention is equally applicable to SPECT, PET-MR or PET-CT
Deng.
According to an exemplary and non-limiting embodiment, a kind of method of the invention includes acquisition PET data, and
PET image is rebuild using PET data and decaying image is obtained during PET image reconstruction.Acquisition PET data may include
Such as the PET data of patient is acquired by equipment, PET data is obtained from database or receives PET data etc. from other sources.
According to optional aspect, before carrying out based on the segmentation of threshold value according to decaying image, can use combine and estimate
Calculating method is iterated reconstruction to PET image and decaying image, to obtain more accurate PET image and decaying image, in turn
Obtain more accurately segmentation.
According to an exemplary and non-limiting embodiment, using Combined estimator algorithm to PET image and decaying image
It is iterated the flow rebuild and may include following specific Combined estimator.
First, using ordered subset expectation maximization value method (OSEM), fixed attenuation sinogram carries out PET image more
Newly.
Wherein fj (n,m+1)Indicate the PET activity (radiation) obtained after m secondary subset iteration in nth iteration in reconstruction process
Image, SmIndicate than the m-th data subset in data space, HijtAnd HiktIndicate that sytem matrix, i are the serial number of line of response, k and j
Indicate that kth or j-th of voxel in radiation image, t indicate the number of time flight case, εi(t) it represents to t-th of time case i-th
The standardization coefficient of table data, s in line of responsei(t) and ri(t) it indicates respectively in t-th of time case, i-th line of response
Scattering meets the quantity of event and random coincidence event；It indicates in nth iteration used in m secondary subset iteration
The attenuated sinusoidal value of i-th of element in attenuation sinogram.
It should be noted thatInitial value can be determined according to prior information, i.e., a variety of bodies are stored in prior data bank
The pad value of element, system are that corresponding voxel distributes initial attenuation value according to the initial live angle value of PET live images；Alternatively, obtaining
The anatomical structure image at the same position of subject, such as corresponding CT images or MR images are selected, by reference to CT images
CT values are that corresponding voxel distributes pad value or attenuation coefficient；For another example by reference to MR images, the boundary of histoorgan is determined
And classification, corresponding attenuation coefficient is distributed for corresponding histoorgan, and then obtain corresponding pad value.Illustratively, Wherein：lijIndicate the system square that the line integral model of attenuation sinogram is mapped to from decaying image
Battle array,Indicate the attenuation coefficient before sub- iteration of the voxel j by m-th of subset in n times iteration.
Then, contribution of the updated PET image on data field is calculated
Wherein,Representative obtains i-th of voxel in PET radiation images after m subiterations in n times iteration and exists
Desired value in nonTOF sinograms.
Next, being updated to each voxel for image of decaying.
Wherein,Indicate after the sub- iteration by m-th of subset in n times iteration fromObtained from update
Attenuation coefficient (and non-image), lijIt is the line integral sytem matrix for being mapped to attenuation coefficient from decaying image, indicates in sinogram
I-th line of response passes through the length of voxel j, yiIndicate the number of collected annihilation photon pair in i-th of line of response, siAnd ri
Indicate that the scattering in i-th line of response meets the quantity of event and random coincidence event respectively,Representative changes by n times
Dai Zhong m+1 subiterations obtain desired value of i-th of voxel in nonTOF sinograms in PET radiation images.
In above-mentioned iterative reconstruction process, keeps PET decaying images constant first in every second son iterative process and make
PET radiation images are updated with formula (2), then keeps PET radiation images constant and formula (4) is used to update decaying image, are once being changed
All order subsets are traversed during generation carries out next iteration again later, it is reciprocal with this, until meeting preset iteration stopping
When condition, stop iteration, obtains the PET radiation images and decaying image.Otherwise, then using the value that current iteration obtains as just
Initial value continues above-mentioned iterative process.
Although being adopted above to the description of embodiment for using Combined estimator algorithm to rebuild PET image and decaying image
With ordered subset expectation maximization value method (OSEM), but other algorithms that PET image and/or decaying image are rebuild
Also it is available, such as MLAA algorithms etc..And as previously mentioned, the reconstruction is optional step, and in some embodiments
It can be omitted.
According to exemplary and non-limiting embodiment, an aspect of of the present present invention includes carrying out being based on threshold according to decaying image
The segmentation of value.Decay in image, voxel value can represent attenuation degree when gamma rays penetrates unit length.Different tissues decaying system
Number differs greatly.For example, the attenuation coefficient of bone is generally in 0.012/mm or more, tissue and muscle parts attenuation coefficient exist
0.0096/mm or so, and the attenuation coefficient of fat is relatively low, about in 0.008/mm or so.By carrying out being based on declining to decaying image
The volume and accounting of bone, tissue, fat can substantially be obtained by subtracting the Threshold segmentation of coefficient, and/or obtain its topographic morphologies.
There are many kinds of the modes of image segmentation, the present invention one it is exemplary and in non-limiting example, base can be used
In the dividing method of histogram.But those of ordinary skill in the art can be appreciated that, the present invention is not limited thereto, and can be applied to it
Its dividing method.For example, the present invention may also comprise the picture using other prior arts or exploitation in future in addition to histogram
Plain primary system calculating method.
It may include that either organ histogram method assumes same organs or same to n (kind) different tissues in image
Group, which is woven in, same or similar pixel value in decay pattern, and can then have between different organs and/or tissue different
Pixel value.It is non-limiting as example, according to histogram method, it is assumed that histogram functions h (v) can be that value is in decay pattern
The number of the pixel of v.Therefore, this n in decay pattern different tissues or organ correspond to the maximum of n h (v).It is logical
Cross differentiation h (v) maximum methods, it can be determined that the most probable value of Different Organs in decay pattern.By differentiating h (v) minimum
Method then may determine that the most probable separation and cut zone of Different Organs in decay pattern.
According to an exemplary and non-limiting embodiment, the definition of histogram is represented by:
H (v)=∫Allδ(g(x,y,z)-v)dxdydz (5)
Wherein, h (v) can indicate the number for the pixel that value is v in decay pattern；X indicates the abscissa of pixel；Y tables
Show the ordinate of pixel；Z indicates the ordinate of pixel；Coordinate is that the value of the pixel of (x, y, z) is denoted as g in decay pattern
(x,y,z).δ (v) indicates binaryzation function, as v ∈ [- v0,v0] when, δ=1；Otherwise it is 0, wherein v0It is an adjustable ginseng
Number.
According to an exemplary and non-limiting embodiment, the maximum and/or minimum of h (v) can be by h (v)
Derivation obtains.For example, according to an example, h (v) can have that there are three maximum h (va)、h(vb) and h (vc) and it is two minimum
Value h (vd) and h (ve), wherein such as va<vd<vb<ve<vc。
According to the maximum and minimum of h (v), the decaying pixel point corresponding to such as some organ can be obtained
Cloth v ∈ [v1,v2], it is R (x, y, z) to obtain the region R corresponding to this organ | g (x, y, z) ∈ [v1,v2], it is expressed as working as g
(x,y,z)∈[v1,v2] when, otherwise R (x, y, z)=1 is 0.Therefore, the region of R (x, y, z)=1 is to indicate organ thus
Segmentation result.
For example, according to precedent, it is assumed that organ A corresponds to maximum h (va), organ B corresponds to maximum h (vb), organ C
Corresponding to maximum h (vc), the separation between organ A and organ B corresponds to minimum h (vd), and between organ B and organ C
Separation correspond to minimum h (ve).Correspondingly, in order to be split to organ B (for example, fat), organ B can be chosen
Corresponding decaying pixel is distributed [vB1,vB2].The selection of the value range can be according to various algorithms.For example, according to one
A non-limiting example, range [vB1,vB2] can be chosen according to ± n times standard deviation of average value.Non-limiting shown according to another
Example, range [vB1,vB2] can be according to vb±v0It chooses, wherein v0It is an adjustable parameter.
According to the range [v of selectionB1,vB2], it can get the region R corresponding to this organ BbFor Rb(x,y,z)|g(x,y,z)
∈[vB1,vB2]。
It can after carrying out based on the segmentation of threshold value according to decaying image according to exemplary and non-limiting embodiment
To be optionally modified segmentation result to obtain such as fat region.
Since iterative algorithm obtains decaying image, there are noises, the fat topology as acquired in aforementioned any embodiment
Form may be not fully accurate.In some cases, it on the one hand has free non-fat voxel and is mistaken for fat, on the other hand
It has fatty voxel and is mistaken for non-fat tissue.Therefore it can carry out the fat of the acquisition of amendment step 2 using certain prior information
Fat topographic morphologies.Some optional prior informations include but is not limited to：
I) using such as decay pattern as Atlas (collection of illustrative plates) templates further repair fats portion acquired after segmentation
Just.
For example, according to an exemplary and non-limiting embodiment, it may include multiple dictionary elements in Atlas databases
(D1, D2 ... Dn), enumerates different height, weight, gender, disease condition.Each dictionary element Di may include such as two
Group pairing image：PET decaying image IMG (i), pixel classifications distributed image
In practical applications, the decaying image that iteration obtains is passed through for Current Scan patient, it can be first by matching body
The information such as high weight select dictionary element i, then are registrated to the decaying image IMG (i) in dictionary element by image registration and work as
Preceding patient image.Finally by same registration parameter by the pixel classifications distributed image of this dictionary elementDeformation is carried out, is obtained
The initial pictures of Current Scan patient are taken to classify.The method of image registration has very much, such as common optical flow
(optical flow field) method.
II image procossing) is carried out to the fats portion that step 2 obtains, removes the classification erroneous judgement brought into due to noise.
Image processing algorithm helps to reduce the classification error of each voxel of image.In this application, a kind of feasible image
Processing method is to be compared all voxels in current voxel and surrounding certain radius.If differed greatly, illustrate this body
The value of element probably due to influence of noise and in abnormal, it is therefore desirable to be filtered by a such as median filter, to
The phenomenon for sorting out mistake is avoided as far as possible.
Although using Atlas templates, image to the description for correcting the embodiment that segmentation result obtains fat region above
Processing Algorithm, or any combination thereof, but other algorithms being modified to segmentation result are also available.And such as preceding institute
It states, which is optional step, and can be omitted in some embodiments.
According to an exemplary and non-limiting embodiment, according to decaying image carry out the segmentation based on threshold value it
Afterwards, it and optionally after being modified to segmentation result, can be calculated " muscle weight " based on acquired fat region
lean_weight。
For example, according to an exemplary and non-limiting embodiment, lean_weight=weight-fat_weight,
That is " muscle weight "=weight-fat weight.Therefore only need to calculate fat weight can obtain.According to another it is exemplary rather than
Limited embodiment can be based on acquired revised fat after by aforementioned the step of being modified to segmentation result
Fat topology obtains fat volume, multiplied by fat attenuation can obtain fat weight.It is pointed out that body fat density
Generally at 0.9 gram/cc.
After obtaining muscle weight, SUL values (SUV lean, standard weight intake) can be calculated.The calculating of SUL values will very
Directly.For example, can SUV only need to be multiplied by a factor, it is as follows
Wherein,After C is corrected (correction for attenuation and/or scatter correction) in PET image
Pixel intensity value；Dose represents the injection dosage of contrast agent；Weight represents the weight of subject target area.
Dixon sequence images can not accurately obtain fat during CT excalations or PETMR are scanned in PET/CT scannings
When ratio chart as an alternative solution, and/or in PET/CT scannings using CT images fat weight can be calculated and/or in PET/
In MR can by Dixon retrieval fat ratios in the case of be used as additional project, aforementioned reality according to the present invention can be used
The various fatty estimation means of example are applied to estimate fat weight, it is quantitative not accurate enough to solve adiposis patient SUV, and keep
The group of same physiological status crowd quantifies the major issues such as consistency.If those of ordinary skill in the art are illustrated, although this
Invention is described the embodiment of the present invention by taking PET as an example, but the solution of the present invention is equally applicable to SPECT etc..
Fig. 1 shows the SUL value calculating methods 100 based on PET data information according to an exemplary embodiment of the invention,
The program instruction that this method is related to is storable in computer readable storage medium, the instruction of the computer-readable recording medium storage
It can be executed by PET system or other equipment.Method 100 may include such as acquisition PET data (1020).This method 100 is also wrapped
It includes and acquired PET data is utilized to rebuild PET image, and obtain decaying image (1040) during PET image reconstruction.It can
Optionally, method 100 may include being iterated reconstruction (step to PET image and decaying image using Combined estimator algorithm
1060).Such as those of ordinary skill in the art it is found that PET data, PET image and/or decaying image are not limited to only by aforesaid way
To obtain.For example, PET data, PET image and/or decaying image can be obtained from database or be received from other sources.
Method 100 may also include for example carries out the segmentation (step 1080) based on threshold value according to decaying image.Optionally,
For example, this method may also include, (step 1100) is modified to segmentation result.
Method 100 can further comprise for example according to segmentation as a result, to calculate " muscle weight " lean_weight (steps
It is rapid 1120)；And after obtaining muscle weight, SUL value (steps 1140) are calculated.
Fig. 2 shows the SUL values computing devices 200 based on PET data information according to an exemplary embodiment of the invention.
Equipment 200 may include such as processor 2010, memory 2020 and input/output interface 2030.Processor 2020 can store
The (not shown) such as software 2025 and data.The computing device 2000 may also include the device (frame for example for acquiring PET data
2040), for utilizing acquired PET data to rebuild PET image, and decaying image is obtained during PET image reconstruction
Device (frame 2060)；(can be optionally) to PET image and decaying image using Combined estimator algorithm for being iterated reconstruction
Device (frame 2080)；Device (frame 2100) for carrying out the segmentation based on threshold value according to decaying image；(can optionally) for pair
The device (frame 2120) that segmentation result is modified；For according to segmentation as a result, to calculate " muscle weight " lean_weight
Device (frame 2140)；And for after obtaining muscle weight, calculating the device (frame 2160) of SUL values.
Although in fig. 2, above-mentioned apparatus (for example, 2040-2160 etc.) is illustrated as through bus 2200 and other component couplings
It closes, but the present invention is not limited to this.For example, according to an exemplary embodiment, above-mentioned apparatus and its function can be by storing
In memory 2020 and the computer executable instructions that can be executed by processor 2010 are realized.According to another exemplary reality
Example is applied, above-mentioned apparatus and its function can be realized by being designed to carry out the hardware circuit of above method step.According to another example
Property embodiment, the device for acquiring PET data may include or be integrated in input/output interface.According to another exemplary
Embodiment, the device for acquiring PET data may include for example for by equipment acquire patient PET data device and/or
For obtaining PET data from database (not shown) or receiving the device etc. of PET data from other source (not shown).
Provide PET imaging system schematic diagrames used in one embodiment of the invention as Fig. 3 is exemplary, the PET being directed at
As system 300 with control unit 310 is maincenter, have rack 320, signal processing part 330 while count section 340, storage part 350,
Processor 360, display unit 370 and operation portion 380.Wherein, the central shaft in rack 320 circumferentially is arranged with multiple detectors
There are the multiple detectors being arranged on the axial circumference in center, subject P can be at by multiple detectors for ring, detector rings
Imaging in the scan vision (Field Of View, FOV) surrounded.Its specific imaging process is：Before PET scan, to subject
The medicament of injection radioactive isotope mark in P bodies；What detector detection was released inside subject P penetrates at pair annihilation gamma
Line generates pulse type electric signal corresponding with the light quantity at pair annihilation gamma ray detected；The pulse type electric signal is supplied
To signal processing part 330, signal processing part 330 generates single event data (Single Event Data) according to electric signal, practical
Middle signal processing part 330 is more than threshold value this case by detecting the intensity of electric signal, to electro-detection annihilation gamma ray；Single thing
Number of packages evidence is supplied to while count section 340, while 340 pairs of count section single event data related with multiple single events are implemented together
When counting handle.Specifically, at the same count section 340 from repeat supply single event data in repeat determine be contained in in advance
The related event data of two single events in the time range first set, time range are set to the left sides such as 6ns~18ns
It is right.The pairs of single event is presumed to origin in from the same pairs of annihilation gamma ray generated at pair annihilation point, wherein in pairs
Single event be briefly referred to as meeting event.Connection detects that the line of the pairs of detector of the pairs of annihilation gamma ray is claimed
For line of response (Line Of Response, LOR).In this way, count section 340 meets event and structure for every LOR countings simultaneously
It is stored to storage part 350 at the related event data of pairs of event (hereinafter referred to as meeting event data) of LOR.Processing
Device 360 meets that event is related to meet event data according to multiple, rebuilds radioisotopic dense in performance subject
The image data of the spatial distribution of degree.
Further, processor can also realize following operation：Obtain the PET data of subject's body part；Rebuild PET numbers
According to the PET image for obtaining the target site, and decay pattern corresponding with PET image is obtained in the reconstruction process of PET data
Picture；Processing is split to decaying image and obtains segmentation result；The weight of specific organization is determined according to segmentation result；And it is based on
The calculated specific organization weight and PET image determine SUL values.Detailed step refers to earlier figures 1 or Fig. 2's
Description, is not repeating again.
It will be recognized by one of ordinary skill in the art that the advantageous effect of the disclosure is real Lai whole not by any single embodiment
It is existing.Various combinations, modification and replacement are that those of ordinary skill in the art are illustrated on the basis of the disclosure.
In addition, term "or" is intended to indicate that inclusive "or" and nonexcludability "or".That is, unless otherwise specified or from upper and lower
Text can be clearly seen, otherwise phrase " X " use " A " or " B " be intended to indicate that it is any naturally can and arrangement.That is, phrase " X " is adopted
Met by any example in following instance with " A " or " B "：X uses A；X uses B；Or X uses both A and B.Belong to
" connection " can indicate identical meanings with " coupling ", indicate the electrical connection of two devices." inverter " can be indicated all with " converter "
The circuit or electric component being made of inverter bridge." the first bridge arm output current ", " inverter can be used in " resonant cavity input current "
Output current " indicates.In addition, article " one " and " certain " used in the application and the appended claims generally should be appreciated that
At expression " one or more ", unless stated otherwise or can be apparent from from the context refer to singulative.
Various aspects or feature by by may include several equipment, component, module, and the like system in the form of be in
It is existing.It should be understood that and understand, various systems may include optional equipment, component, module etc., and/or can not include in conjunction with attached drawing
Armamentarium, component, module for being discussed etc..The combination of these methods can also be used.
It can be with general in conjunction with various illustrative logicals, logical block, module and the circuit that presently disclosed embodiment describes
Processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or it is other can
Programmed logic device, discrete door or transistor logic, discrete hardware component or its be designed to carry out function described herein
Any combinations realize or execute.General processor can be microprocessor, but in alternative, and processor can be appointed
What conventional processor, controller, microcontroller or state machine.Processor is also implemented as the combination of computing device, example
As DSP and the combination of microprocessor, multi-microprocessor, the one or more microprocessors cooperateed with DSP core or it is any its
Its such configuration.In addition, at least one processor may include may act on execute one or more steps described above and/or
One or more modules of action.For example, the embodiment above in association with the description of each method can be by processor and being coupled to
The memory of processor realizes, wherein the processor can be configured to execute any step of aforementioned any method or its is any
Combination.
In addition, in conjunction with the method that aspect disclosed herein describes or the step of algorithm and/or action can be directly hard
Implement in part, in the software module executed by processor or in combination of the two.For example, above in association with each method
The embodiment of description can realize by being stored with the computer-readable medium of computer program code, wherein the computer journey
Sequence code executes any step of aforementioned any method when being executed by processor/computer.
The element of the various aspects described in the whole text in the disclosure is that those of ordinary skill in the art are currently or hereafter known
Equivalent scheme in all structures and functionally is clearly included in this by citation, and is intended to be intended to be encompassed by the claims.
In addition, any content disclosed herein is all not intended to contribute to the public --- it is no matter such open whether in claim
It is explicitly recited in book.
Claims (10)
1. a kind of PET data processing method, which is characterized in that including：
Obtain the PET data of subject's body part；
The PET data is rebuild to obtain the PET image of body part, and obtain in the reconstruction process of the PET data with
The corresponding decaying image of the PET image；
Processing is split to the decaying image and obtains segmentation result；
Specific organization is determined according to the segmentation result；
Calculate the weight of the feature organization；And
Based on the calculated specific organization weight and the PET image determine SUL values.
2. the method as described in claim 1, which is characterized in that further include determining specific organization according to the segmentation result
Weight before, the segmentation result is modified at least one of in the following way：
The Atlas templates of the decaying image are obtained, and using the Atlas templates of the decaying image in the segmentation result
Pixel classify；
Alternatively, carrying out denoising to the pixel in the segmentation result.
3. the method as described in claim 1, which is characterized in that be split processing to the decaying image and obtain segmentation result
Including：Pixel value in the decaying image is counted to determine the boundary of Different Organs.
4. the method as described in claim 1, which is characterized in that subject's body part further includes fat, the segmentation
As a result include the boundary on the boundary and non-fat region of fat region, the specific organization corresponds to fat region.
5. method as claimed in claim 4, which is characterized in that the SUL values are the corresponding SUV values of destination organization, based on meter
Calculate the specific organization weight and the PET image include to determine SUL values：
Determine the quality of subject's body part；
The weight of destination organization is determined according to the weight of the quality of subject's body part and the specific organization；
SUL values are determined based on the weight of the PET image, the injection dosage of contrast agent and the destination organization.
6. a kind of PET data processing equipment, which is characterized in that including：
Device for the PET data for obtaining subject's body part；
For rebuilding the PET data to obtain the PET image of body part, and obtained in the reconstruction process of the PET data
Take the device of decaying image corresponding with the PET image；
For being split the device that processing obtains segmentation result to the decaying image；
Device for determining specific organization according to the segmentation result；
Device for the weight for calculating the feature organization；And
For based on the calculated specific organization weight and the PET image determine the device of SUL values.
7. equipment as claimed in claim 6, which is characterized in that obtain segmentation for being split processing to the decaying image
As a result device includes：Dress for being counted the boundary to determine Different Organs to the pixel value in the decaying image
It sets.
8. equipment as claimed in claim 6, which is characterized in that the SUL values are the corresponding SUV values of destination organization, are used for base
Include to determine the device of SUL values in the weight of the calculated specific organization and the PET image：
Device for the quality for determining subject's body part；
Weight for determining according to the quality of subject's body part and the weight of the specific organization destination organization
Device；
Weight for injection dosage and the destination organization based on the PET image, contrast agent determines the device of SUL values.
9. a kind of PET imaging systems, including：
One or more processors；
Memory；With
One or more programs, wherein one or more of programs are stored in the memory and are configured as by described
One or more processors execute, and one or more of programs include the instruction for being operated below：
Obtain the PET data of subject's body part；
The PET data is rebuild to obtain the PET image of body part, and obtain in the reconstruction process of the PET data with
The corresponding decaying image of the PET image；
Processing is split to the decaying image and obtains segmentation result；
Specific organization is determined according to the segmentation result；
Calculate the weight of the feature organization；And
Based on the calculated specific organization weight and the PET image determine SUL values.
10. a kind of computer readable storage medium of the one or more programs of storage, one or more of programs include instruction,
Described instruction realizes the either method in the method as described in claim 1 to 5 upon being performed.
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