CN104352244B - A kind of data processing method and device - Google Patents

Abstract

The embodiment of the invention discloses a kind of data processing method and device, including the boundary analyzing string figure, do not comprise described in acquisition and true coincidence data area meets data immediately, determine scatter distributions data and random coincidence data by the described data that immediately meet；The described data that immediately meet are processed, particularly as follows: utilize the second correction factor after described adjustment immediately meeting of true coincidence data data to be determined random coincidence data comprising, visible, obtain and described random coincidence data by immediately meeting data, and be described random coincidence data setting the second correction factor, by adjusting the first error amount described in described second correction factor and comparison and described second error amount, obtain the second correction factor after described adjustment, the second correction factor after described adjustment is utilized data to be determined, described random coincidence data are more accurate from immediately meeting.

Description

A kind of data processing method and device

Technical field

The present invention relates to data processing field, particularly relate to a kind of data processing method and device.

Background technology

Positron annihilation radiation that medical imaging apparatus produces according to the radionuclide being injected in vivo in decay process and meet detection principle and can obtain internal fault image, such as typical PET-Positron emission computed tomography imaging (PositronEmissionComputedTomography, PET) device.

When positron annihilation, two γ photons of almost back-to-back operation can be generated.Each γ photon is detected by the detector of PET and is flagged as a single event.Produced mass data when occurring according to this single event, it can be determined that go out whether this single event is produced by positron annihilation.When judging that a single event is to be produced by positron annihilation, the data of this single event for judging are defined as immediately meeting data.Make described to meet in data except comprising true coincidence data even if existing judgement meets the mode of data immediately, further comprises substantial amounts of random coincidence data and scattering meets data, wherein, if two the γ photons produced by a positron annihilation, and in traveling process, do not produce Compton scattering, the data formed on the detector, are called true coincidence data.If several positroies are buried in oblivion at synchronization or in the very close moment, almost produce in the γ photon of some pairs simultaneously, it is likely to have two γ photons produced when not being same positron annihilation to be judged to meet by detector, such accident meets event and is called random coincidence, meet the data that the γ photon of random coincidence is formed on the detector, be called random coincidence data.If there is Compton scattering in flight course in one or two photons in a pair γ photon, change the flight path of self and reduce self-energy, due to detector energy limited resolution, part energy changes little event and can be mistaken as true coincidence event and record.Meet the data that the γ photon of this situation is formed on the detector, be called scattering and meet data.In order to remove these invalid datas, it is necessary to it is calculated accurately.

Described adjustment relies primarily on the accurate calculating to described random coincidence data, if the judgement of random coincidence data exists error, then correction result will be brought impact, but, currently without the method calculating random coincidence data accurately.

Summary of the invention

In order to solve above-mentioned technical problem, the invention provides a kind of data processing method and device, improve and determine that scattering meets the order of accuarcy of data.

The embodiment of the invention discloses following technical scheme:

A kind of data processing method, described method includes:

Analyze the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan；

Do not comprise described in acquisition and true coincidence data area meets data immediately, determine scatter distributions data and random coincidence data by the described data that immediately meet；

The described data that immediately meet are processed, particularly as follows:

Step 1: for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data；

Step 2: only adjust described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum；

Step 3: carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains is the second error amount；

Step 4: the relatively difference between described first error amount and described second error amount, if described difference is in preset range, then utilizes the second correction factor after described adjustment immediately meeting of true coincidence data to determine random coincidence data in data comprising；

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, re-execute described step 1.

Preferably, between described step 1 and described step 3, also include step 2a:

Step 2a: only adjust described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described mathematic interpolation obtains minimum；

Described step 3 is particularly as follows: carrying out, according to the first correction factor after described adjustment and the second correction factor after described adjustment, the result that described mathematic interpolation obtains is the second error amount；

Described step 4 is particularly as follows: relatively difference between described first error amount and described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, re-execute described step 1.

Preferably, if described difference is in preset range, also include:

The second correction factor after described adjustment is carried out the first verification, and utilizes the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification；

If described first verification and described second verification are all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.

Preferably, described step 1, particularly as follows:

err₁=Σ_i|P_iN_i-ω₁R_iN_i-λ₁S′_i|；

Wherein, err₁For described first error amount, λ₁For described first correction factor, ω₁For described second correction factor, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

Preferably, described step 2a particularly as follows:

$\left[{\mathrm{\λ}}_2\right]=\underset{\mathrm{\λ}}{\arg \min }\underset{i}{\mathrm{\Σ}}|P_i{N}_i-{\mathrm{\ω}}_1{R}_i{N}_i-{\mathrm{\λS}}_i^{\′}|;$

Wherein, λ₂For the first correction factor after described adjustment.

Preferably, described step 2 particularly as follows:

$\left[{\mathrm{\ω}}_2\right]=\underset{\mathrm{\ω}}{\arg \min }\underset{i}{\mathrm{\Σ}}|P_i{N}_i-{\mathrm{\ωR}}_i{N}_i-{\mathrm{\λ}}_1{S}_i^{\′}|;$

Wherein, ω₂For the second correction factor after described adjustment.

Preferably, described step 3 particularly as follows:

err₂=Σ_i|P_iN_i-ω₂R_iN_i-λ₂S′_i|；

Wherein, err₂For described second error amount.

Preferably,

Described first verification particularly as follows:

Judge whether the second correction factor after described adjustment meets the first preset range；

Described second verification particularly as follows:

${\mathrm{err}}_{\mathrm{total}}=\frac{{\mathrm{\Σ}}_i({\mathrm{\ω}}_2{R}_i{N}_i+{\mathrm{\λ}}_2{S}_i^{\′})}{{\mathrm{\Σ}}_i{P}_i{N}_i};$

err_totalWhether meet the second preset range.

A kind of data processing equipment, including:

Determine unit, for analyzing the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan；

Acquiring unit, immediately meets data for not comprising described in obtaining in true coincidence data area, determines scatter distributions data and random coincidence data by the described data that immediately meet；

Processing unit, for the described data that immediately meet are processed, specifically includes:

First computation subunit, for for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data；

First adjusts subelement, for only adjusting described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum；

Second computation subunit, is the second error amount for carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains；

Relatively subelement, for comparing the difference between described first error amount and described second error amount, if described difference is in preset range, then the second correction factor after described adjustment is utilized immediately meeting of true coincidence data data to be determined random coincidence data comprising；

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, again trigger described first computation subunit.

Preferably, after triggering described first computation subunit, before triggering described second computation subunit, the second adjustment subelement is also included:

Described second adjusts subelement, for only adjusting described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described mathematic interpolation obtains minimum；

Described second computation subunit, be additionally operable to the first correction factor after according to described adjustment and the second correction factor after described adjustment to carry out the result that described mathematic interpolation obtains be the second error amount；

Described compare subelement, it is additionally operable to the first error amount described in comparison and the difference between described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, again trigger described first computation subunit.

Preferably, if the described comparative result comparing subelement is that described difference is in preset range, syndrome unit is also included:

Described syndrome unit, for the second correction factor after described adjustment carries out the first verification, and utilize the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification；

Described compare subelement, if being additionally operable to described first verification and described second verification being all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.

Be can be seen that by technique scheme, obtain and described random coincidence data by immediately meeting data, and be described random coincidence data setting the second correction factor, by adjusting the first error amount described in described second correction factor and comparison and described second error amount, obtain the second correction factor after described adjustment, utilize the second correction factor after described adjustment data to be determined, described random coincidence data are more accurate from immediately meeting.

Accompanying drawing explanation

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, the accompanying drawing used required in embodiment or description of the prior art will be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the premise not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.

The method flow diagram of a kind of data processing method that Fig. 1 provides for the embodiment of the present invention；

The schematic diagram of a kind of string figure that Fig. 2 provides for the embodiment of the present invention；

The structure chart of a kind of data processing equipment that Fig. 3 provides for the embodiment of the present invention；

The structure chart of a kind of data processing equipment that Fig. 4 provides for the embodiment of the present invention；

The structure chart of a kind of data processing equipment that Fig. 5 provides for the embodiment of the present invention.

Detailed description of the invention

Owing to prior art lacking from immediately meeting the means accurately determining random coincidence data data, cause utilize described immediately meet data carry out data process time, and when improving the described ratio immediately meeting true coincidence data in data, effect is all undesirable.Also just directly results in medical imaging apparatus precision can not improve further.A kind of data processing method and device is the invention provides for this, obtain and described random coincidence data by immediately meeting data, and be described random coincidence data setting the second correction factor, by adjusting the first error amount described in described second correction factor and comparison and described second error amount, obtain the second correction factor after described adjustment, utilize the second correction factor after described adjustment data to be determined, described random coincidence data are more accurate from immediately meeting.

For making the purpose of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is explicitly described, it is clear that, described embodiment is a part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, the every other embodiment that those of ordinary skill in the art obtain under not making creative work premise, broadly fall into the scope of protection of the invention.

Embodiment one

Fig. 1 is the method flow diagram of a kind of data processing method of the present invention, and described method includes:

S101: analyze the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan.

Need exist for illustrate be, described string figure is the projection commonly used in medical science contrast imaging, the kind more than one of described string figure, it it is all generally the scanned body (such as human body) projection by generating after medical imaging devices projection scanning, the schematic diagram of a kind of string figure that Fig. 2 provides for the embodiment of the present invention, as shown in Figure 2 be exactly the one in described string figure.Wherein, b and c is the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, or it may be said that, the region between region and cd between ab is that medical imaging devices does not also scan projection obtained during scanned body, and the region between bc is that medical imaging devices scans projection obtained during scanned body.Region between bc has true coincidence data, and in general, the region between ab and between cd does not have true coincidence data.

S102: do not comprise described in acquisition and immediately meet data in true coincidence data area, determine scatter distributions data and random coincidence data by the described data that immediately meet.

Owing to the region between ab and between cd being not there are true coincidence data, therefore data contain substantially no true coincidence data immediately meeting in this subregion, and only comprise random coincidence data and scattering meets data.Therefore owing to there is no the interference of true coincidence data, described immediately meet data by what process in this subregion, it is possible to determine that scattering meets data more accurately.And can by the described result immediately meeting data not comprised in true coincidence data area, it is incorporated in the process immediately meeting data comprising in true coincidence data area, improves further and true coincidence data area meets the accuracy determining in data that scattering meets data immediately from comprising.

Described scatter distributions data meet data and described scattering meets data and calculates and obtain immediately mainly by described, and the method for acquisition can have multiple, and this is not illustrated by the present invention one by one.

S103: the described data that immediately meet are processed, particularly as follows:

Step 1: for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data.

Owing to immediately meeting the described scatter distributions data obtained in data and described random coincidence data are inaccurate by prior art according to described, therefore the present invention is that respectively the first correction factor described in described scatter distributions data and described random coincidence data setting and described second correction factor carry out the correction in error for this.Do not comprise described true coincidence data owing to immediately meeting data shown in the process in S103, only comprise described scatter distributions data and described random coincidence data.Second correction factor is adjusted by the result obtained by described mathematic interpolation.Concrete:

err₁=Σ_i|P_iN_i-ω₁R_iN_i-λ₁S′_i|；

Wherein, err₁For described first error amount, λ₁For described first correction factor, ω₁For described second correction factor, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

Step 2: only adjust described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum.

It is to say, described first correction factor is not adjusted, and only adjust described second correction factor, it is determined that go out the second correction factor after the adjustment when the result of described Error Calculation is minimum.Particularly as follows:

$\left[{\mathrm{\ω}}_2\right]=\underset{\mathrm{\ω}}{\arg \min }\underset{i}{\mathrm{\Σ}}|P_i{N}_i-{\mathrm{\ωR}}_i{N}_i-{\mathrm{\λ}}_1{S}_i^{\′}|;$

Wherein, ω₂For the second correction factor after described adjustment.

Step 3: carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains is the second error amount.

Particularly as follows:

err₂=Σ_i|P_iN_i-ω₂R_iN_i-λ₁S′_i|；

Wherein, err₂For described second error amount.

Step 4: the relatively difference between described first error amount and described second error amount, if described difference is in preset range, then utilizes the second correction factor after described adjustment immediately meeting of true coincidence data to determine in data and meet data immediately comprising.

That is err is compared₁Deduct err₂Whether obtained difference meets preset range.In order to improve judgement precision further, it is also possible to by the described difference that obtains again divided by err₁, it is judged that whether result of calculation is in predetermined scope, and described predetermined scope can value be between 0 to 0.0005.

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, re-execute described step 1.

Illustrate, if described difference is in outside preset range, by ω₂As ω₁, by ω₂Value as ω₁Value, re-start step 1.

Can not determine accurately owing to described scattering meets in data prior art, therefore the embodiment of the present invention can also be passed through both to have adjusted described first correction factor, also the mode of described second correction factor is adjusted, improve and determine that described scattering meets the accuracy of data, the accuracy determining described random coincidence data can also be improved further simultaneously.For this, on the basis of embodiment corresponding for such as Fig. 1, the embodiment of the present invention additionally provides a kind of method that data process, and between described step 1 and described step 3, also includes step 2a:

Step 2a: only adjust described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described Error Calculation obtains minimum.

It is to say, described first correction factor is not adjusted, and only adjust described second correction factor, it is determined that go out the second correction factor after the adjustment when described first error amount is minimum.Particularly as follows:

$\left[{\mathrm{\λ}}_2\right]=\underset{\mathrm{\λ}}{\arg \min }\underset{i}{\mathrm{\Σ}}|P_i{N}_i-{\mathrm{\ω}}_1{R}_i{N}_i-{\mathrm{\λS}}_i^{\′}|;$

Wherein, λ₂For the first correction factor after described adjustment.

Execution sequence between described step 2 and described step 2a is not defined by the present invention, both can be described step 2 and described step 2a performs simultaneously, it is also possible to be successively perform.

Accordingly, described step 3 also has further relevant treatment for described step 2a.

Described step 3 is particularly as follows: carrying out, according to the first correction factor after described adjustment and the second correction factor after described adjustment, the result that described mathematic interpolation obtains is the second error amount.

Particularly as follows:

err₂=Σ_i|P_iN_i-ω₂R_iN_i-λ₂S′_i|；

Accordingly, described step 4 also has further relevant treatment for described step 2a.

Described step 4 is particularly as follows: relatively difference between described first error amount and described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, re-execute described step 1.

Relatively the difference between described first error amount and described second error amount, if described difference is in preset range, is namely equivalent to the first correction factor after defining described adjustment and the second Dynamic gene after described adjustment.In order to the result determined further is verified, the embodiment of the present invention additionally provides a kind of verification mode, at least includes twice verification, specifically includes:

The second correction factor after described adjustment is carried out the first verification, and utilizes the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification.

Needing exist for illustrating, whether the second correction factor that described first verification is mainly after verifying described adjustment is in rational scope, when the second correction factor after described adjustment is in the first preset range, it is determined that described first verifies successfully.Wherein, illustrating, described first preset range can set that to be 1 ± 0.25, namely between 0.75 to 1.25.

Whether normally described second verification is mainly used in verification whole body counting value, illustrates, concrete verification mode may is that

${\mathrm{err}}_{\mathrm{total}}=\frac{{\mathrm{\Σ}}_i({\mathrm{\ω}}_2{R}_i{N}_i+{\mathrm{\λ}}_2{S}_i^{\′})}{{\mathrm{\Σ}}_i{P}_i{N}_i};$

err_totalWhether meet the second preset range.

Illustrating, described second preset range can set that to be 1 ± 0.25.

If described first verification and described second verification are all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.

If described first verification and described second verification at least one is unsuccessful, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjusting as described second correction factor, re-execute described step 1.Or, under some application scenarios, it is possible that by the situation of described first verification and described second verification, cannot cause repeating adjusting and the system that is verified as bring bigger burden, and this situation is generally probably what the fault of medical imaging apparatus own caused always always.Therefore, when described first verification and described second at least one unsuccessful number of times of verification reach certain number of times, system can send alarm, and suggestion device breaks down, and carries out manual intervention.

As can be seen from the above-described embodiment, obtain and described random coincidence data by immediately meeting data, and be described random coincidence data setting the second correction factor, for described scatter distributions data setting the first correction factor, by adjusting the first error amount described in described second correction factor, the first correction factor and comparison and described second error amount, the first correction factor after obtaining the second correction factor after described adjustment and adjusting, utilizes the second correction factor after described adjustment to determine data that described random coincidence data are more accurate from immediately meeting.And the precision adjusting described first correction factor by adjusting the process of described second correction factor to improve, further improve the first correction factor after utilizing described adjustment from immediately meeting the degree of accuracy determining described random coincidence data data.

Embodiment two

The present embodiment is the device embodiment of corresponding embodiment one, the structure chart of a kind of data processing equipment that Fig. 3 provides for the embodiment of the present invention, and described data processing equipment 300 includes:

Determine unit 301, for analyzing the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan.

Acquiring unit 302, immediately meets data for not comprising described in obtaining in true coincidence data area, determines scatter distributions data and random coincidence data by the described data that immediately meet.

Processing unit 303, for the described data that immediately meet are processed, specifically includes:

First computation subunit 3031, for for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data.

First adjusts subelement 3032, for only adjusting described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum.

Second computation subunit 3033, is the second error amount for carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains.

Relatively subelement 3034, for comparing the difference between described first error amount and described second error amount, if described difference is in preset range, then the second correction factor after described adjustment is utilized immediately meeting of true coincidence data data to be determined random coincidence data comprising；

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, again trigger described first computation subunit 3031.

Optionally, embodiment corresponding to Fig. 3 basis on, triggering after described first computation subunit 3031, before triggering described second computation subunit 3033, also include the second adjustment subelement 3035, as shown in Figure 4, the structure chart of a kind of data processing equipment that Fig. 4 provides for the embodiment of the present invention:

Described second adjusts subelement 3035, for only adjusting described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described mathematic interpolation obtains minimum.

Described second computation subunit 3033, be additionally operable to the first correction factor after according to described adjustment and the second correction factor after described adjustment to carry out the result that described mathematic interpolation obtains be the second error amount.

Described compare subelement 3034, it is additionally operable to the first error amount described in comparison and the difference between described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, again trigger described first computation subunit 3031.

Optionally, on the basis of embodiment corresponding to Fig. 4, if the described comparative result comparing subelement 3034 is that described difference is in preset range, also include syndrome unit 3036, as it is shown in figure 5, the structure chart of a kind of data processing equipment that Fig. 5 provides for the embodiment of the present invention:

Described syndrome unit 3036, for the second correction factor after described adjustment carries out the first verification, and utilize the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification；

Described compare subelement 3034, if being additionally operable to described first verification and described second verification being all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If it is unsuccessful that described first verification and described second verifies at least one, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, again trigger described first computation subunit 3031.

As can be seen from the above-described embodiment, obtain and described random coincidence data by immediately meeting data, and be described random coincidence data setting the second correction factor, for described scatter distributions data setting the first correction factor, by adjusting the first error amount described in described second correction factor, the first correction factor and comparison and described second error amount, the first correction factor after obtaining the second correction factor after described adjustment and adjusting, utilizes the second correction factor after described adjustment to determine data that described random coincidence data are more accurate from immediately meeting.And the precision adjusting described first correction factor by adjusting the process of described second correction factor to improve, further improve the first correction factor after utilizing described adjustment from immediately meeting the degree of accuracy determining described random coincidence data data.

In the first correction factor of mentioning in the embodiment of the present invention, the first error amount, the first verification, the first computation subunit and the first " first " adjusting subelement be used only to do name mark, do not represent first sequentially.This rule is equally applicable to " second ".

As seen through the above description of the embodiments, those skilled in the art is it can be understood that can add the mode of general hardware platform by software to all or part of step in above-described embodiment method and realize.Based on such understanding, the part that prior art is contributed by technical scheme substantially in other words can embody with the form of software product, this computer software product can be stored in storage medium, such as ROM/RAM, magnetic disc, CD etc., including some instructions with so that a computer equipment (can be personal computer, server, or the network communication equipment such as such as WMG) perform the method described in some part of each embodiment of the present invention or embodiment.

It should be noted that each embodiment in this specification all adopts the mode gone forward one by one to describe, between each embodiment identical similar part mutually referring to, what each embodiment stressed is the difference with other embodiments.Especially for equipment and system embodiment, owing to it is substantially similar to embodiment of the method, so describing fairly simple, relevant part illustrates referring to the part of embodiment of the method.Equipment described above and system embodiment are merely schematic, the unit wherein illustrated as separating component can be or may not be physically separate, the parts shown as unit can be or may not be physical location, namely may be located at a place, or can also be distributed on multiple NE.Some or all of module therein can be selected according to the actual needs to realize the purpose of the present embodiment scheme.Those of ordinary skill in the art, when not paying creative work, are namely appreciated that and implement.

The above is only the preferred embodiment of the present invention, is not intended to limit protection scope of the present invention.It should be pointed out that, for those skilled in the art, under the premise without departing from the principles of the invention, it is also possible to make some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention.

Claims (11)

1. a data processing method, it is characterised in that described method includes:

Analyze the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan；

Do not comprise described in acquisition and true coincidence data area meets data immediately, determine scatter distributions data and random coincidence data by the described data that immediately meet；

The described data that immediately meet are processed, particularly as follows:

Step 1: for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data；

Step 2: only adjust described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum；

Step 3: carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains is the second error amount；

Step 4: the relatively difference between described first error amount and described second error amount, if described difference is in preset range, then utilizes the second correction factor after described adjustment immediately meeting of true coincidence data to determine random coincidence data in data comprising；

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, re-execute described step 1.

2. method according to claim 1, it is characterised in that between described step 1 and described step 3, also includes step 2a:

Step 2a: only adjust described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described mathematic interpolation obtains minimum；

Described step 3 is replaced by: carrying out, according to the first correction factor after described adjustment and the second correction factor after described adjustment, the result that described mathematic interpolation obtains is the second error amount；

Described step 4 is replaced by: the relatively difference between described first error amount and described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, re-execute described step 1.

3. method according to claim 2, it is characterised in that if described difference is in preset range, also include:

The second correction factor after described adjustment is carried out the first verification, and utilizes the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification；

If described first verification and described second verification are all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.

4. the method according to any one of claims 1 to 3, it is characterised in that described step 1, particularly as follows:

err₁=∑_i|P_iN_i-ω₁R_iN_i-λ₁S′_i|；

Wherein, err₁For described first error amount, λ₁For described first correction factor, ω₁For described second correction factor, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

5. method according to claim 2, it is characterised in that described step 2a particularly as follows:

$\[{\mathrm{\λ}}_2\]=\underset{\mathrm{\λ}}{\mathrm{argmin}}\underset{i}{\mathrm{\Σ}}\left|P_i{N}_i-{\mathrm{\ω}}_1{R}_i{N}_i-{\mathrm{\λS}}_i^{\′}\right|;$

Wherein, λ₂For the first correction factor after described adjustment, λ₁For described first correction factor, ω₁For described second correction factor, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

6. the method according to any one of claims 1 to 3, it is characterised in that described step 2 particularly as follows:

$\[{\mathrm{\ω}}_2\]=\underset{\mathrm{\ω}}{\mathrm{argmin}}\underset{i}{\mathrm{\Σ}}\left|P_i{N}_i-{\mathrm{\ωR}}_i{N}_i-{\mathrm{\λ}}_1{S}_i^{\′}\right|;$

Wherein, ω₂For the second correction factor after described adjustment, λ₁For described first correction factor, ω₁For described second correction factor, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

7. according to the method in claim 2 or 3, it is characterised in that the step 3 that is replaced particularly as follows:

err₂=∑_i|P_iN_i-ω₂R_iN_i-λ₂S′_i|；

Wherein, err₂For described second error amount, ω₂For the second correction factor after described adjustment, λ₂For the first correction factor after described adjustment, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

8. method according to claim 3, it is characterised in that

Described first verification particularly as follows:

Judge whether the second correction factor after described adjustment meets the first preset range；

Described second verification particularly as follows:

${\mathrm{err}}_{total}=\frac{{\mathrm{\Σ}}_i({\mathrm{\ω}}_2{R}_i{N}_i+{\mathrm{\λ}}_2{S}_i^{\′})}{{\mathrm{\Σ}}_i{P}_i{N}_i};$

err_totalWhether meet the second preset range, ω₂For the second correction factor after described adjustment, λ₂For the first correction factor after described adjustment, P_iImmediately data, S ' is met for described_iFor described scatter distributions data, R_iFor described random coincidence data, N_iFor normalization factor, the span of i is determined by the border between the region comprising true coincidence data in described string figure and the region not comprising true coincidence data.

9. a data processing equipment, it is characterised in that including:

Determine unit, for analyzing the boundary of string figure, it is determined that going out the border between the region comprising true coincidence data in described string figure and the region not comprising described true coincidence data, described string figure is the projection obtained by transmission scan；

Acquiring unit, immediately meets data for not comprising described in obtaining in true coincidence data area, determines scatter distributions data and random coincidence data by the described data that immediately meet；

Processing unit, for the described data that immediately meet are processed, specifically includes:

First computation subunit, for for described scatter distributions data setting the first correction factor, for described random coincidence data setting the second correction factor, carrying out, according to described first correction factor and described second correction factor, the result that mathematic interpolation obtains is the first error amount, and described mathematic interpolation is that the described data that immediately meet deduct described scatter distributions data and random coincidence data；

First adjusts subelement, for only adjusting described second correction factor so that carry out, according to the second correction factor after adjusting and described first correction factor, the result that described mathematic interpolation obtains minimum；

Second computation subunit, is the second error amount for carrying out, according to the second correction factor after described adjustment and described first correction factor, the result that described mathematic interpolation obtains；

Relatively subelement, for comparing the difference between described first error amount and described second error amount, if described difference is in preset range, then the second correction factor after described adjustment is utilized immediately meeting of true coincidence data data to be determined random coincidence data comprising；

If described difference is in outside preset range, then using the second correction factor after described adjustment as described second correction factor, again trigger described first computation subunit.

10. device according to claim 9, it is characterised in that after triggering described first computation subunit, before triggering described second computation subunit, also include the second adjustment subelement:

Described second adjusts subelement, for only adjusting described first correction factor so that carry out, according to described second correction factor and the first correction factor after adjusting, the result that described mathematic interpolation obtains minimum；

Described second computation subunit, being also replaced by for carrying out, according to the first correction factor after described adjustment and the second correction factor after described adjustment, the result that described mathematic interpolation obtains is the second error amount；

Described compare subelement, also it is replaced by for comparing the difference between described first error amount and described second error amount, if described difference is in preset range, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising；

If described difference is in outside preset range, then using the first correction factor after described adjustment as described first correction factor, using the second correction factor after adjustment as described second correction factor, again trigger described first computation subunit.

11. device according to claim 10, it is characterised in that be in preset range if the comparative result of the comparison subelement being replaced is described difference, also include syndrome unit:

Described syndrome unit, for the second correction factor after described adjustment carries out the first verification, and utilize the first correction factor after described adjustment and the second correction factor after described adjustment that described data, described scatter distributions data and the described random coincidence data of immediately meeting are carried out the second verification；

Described compare subelement, if being additionally operable to described first verification and described second verification being all successful, then the first correction factor after described adjustment is utilized data to be determined random coincidence data at described the second correction factor after determining scatter distributions data in data and utilizing described adjustment that immediately meets comprising true coincidence data immediately meeting of true coincidence data in described comprising.