CN108846810A - A kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed - Google Patents
A kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed Download PDFInfo
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- 238000002599 functional magnetic resonance imaging Methods 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000005457 optimization Methods 0.000 title claims abstract description 24
- 238000012417 linear regression Methods 0.000 claims abstract description 29
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 238000001914 filtration Methods 0.000 claims abstract description 17
- 210000004885 white matter Anatomy 0.000 claims abstract description 8
- 210000001175 cerebrospinal fluid Anatomy 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 claims description 9
- 238000010606 normalization Methods 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 5
- 230000005764 inhibitory process Effects 0.000 claims description 5
- 238000013519 translation Methods 0.000 claims description 3
- 230000002401 inhibitory effect Effects 0.000 abstract description 7
- 238000011160 research Methods 0.000 abstract description 5
- 230000003925 brain function Effects 0.000 abstract description 4
- 238000007781 pre-processing Methods 0.000 abstract description 3
- 230000001629 suppression Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 10
- 230000001186 cumulative effect Effects 0.000 description 9
- 238000006073 displacement reaction Methods 0.000 description 8
- 238000005315 distribution function Methods 0.000 description 8
- 238000012880 independent component analysis Methods 0.000 description 5
- 210000004556 brain Anatomy 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000005481 NMR spectroscopy Methods 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 230000037433 frameshift Effects 0.000 description 1
- 230000000004 hemodynamic effect Effects 0.000 description 1
- 238000002610 neuroimaging Methods 0.000 description 1
- 230000000926 neurological effect Effects 0.000 description 1
- 210000002569 neuron Anatomy 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 238000005201 scrubbing Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 235000019640 taste Nutrition 0.000 description 1
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
A kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed, belongs to functional magnetic resonance imaging preprocessing technical field.Recent research indicate that head moving noise is especially prominent to the interference of functional magnetic resonance imaging.Therefore, effectively inhibiting image noise (such as the dynamic interference of head) is the matter of utmost importance urgently to be resolved of the brain function research based on Functional magnetic resonance imaging.In order to overcome a moving noise, this method determines that bandpass filtering carries out having better head moving noise inhibitory effect before linear regression analysis removes covariant.Simultaneously, during linear regression analysis removes covariant, this pretreatment optimization method, which selects 14 to create disturbances to variable (moving parameter and their first derivative, white matter average signal and cerebrospinal fluid average signal including 6 heads), can further suppress a moving noise.Compared with existing state-of-the-art method, the method has reached outstanding noise suppression effect.
Description
Technical field
The invention belongs to functional magnetic resonance imaging preprocessing technical fields, are related to a kind of pretreatment optimization of functional magnetic resonance imaging
Method, in particular to a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed.
Background technique
Since the 1990s, functional mri is former as a kind of emerging neuroimaging imaging technique
Reason is to detect electrical activity of neurons by non-invasive manner to cause hemodynamic change signal.Currently, function magnetic is total
Vibration imaging has become the indispensable tool of brain function research.However, functional magnetic resonance imaging is made an uproar by many separate sources
The influence of sound causes the signal-to-noise ratio of image data very low.Recent research indicate that interference of the head moving noise to functional magnetic resonance imaging
It is especially prominent.Therefore, effectively inhibiting image noise (such as the dynamic interference of head) is that the brain function based on Functional magnetic resonance imaging is ground
Study carefully matter of utmost importance urgently to be resolved.
Currently, the head moving noise of tranquillization state functional magnetic resonance imaging inhibits problem to receive very big concern.Researcher takes
Many inhibition strategies for being used for tranquillization state functional magnetic resonance imaging head moving noise, such as independent component analysis (Independent
Component Analysis, ICA), wavelet analysis, the data-drivens strategy such as erasing (Scrubbing).Wherein, by Pruim etc.
The head moving noise strategy based on independent component analysis that people introduces, i.e. ICA-based Automatic Removal of
Motion Removal of Motion Artifacts (ICA-AROMA) is showed very outstanding.But even across ICA-
After AROMA strategy carries out noise suppressed to tranquillization state functional magnetic resonance imaging, moves and make an uproar there are still biggish head in image data
Sound.The existing tranquillization state functional magnetic resonance imaging head moving noise based on data-driven inhibits tactful shortcoming to be mainly manifested in
Two aspects.First, the linear regression removal problem of the dynamic covariant of enemy considers insufficient.Second, to filtering and linear regression
Sequencing problem between analysis removal covariant is paid little attention to.
Therefore, it on the outstanding noise suppressed policy grounds of ICA-AROMA, needs to further suppress remaining big in image
Amount head moving noise such as considers that head moves the linear regression removal problem of covariant and linear regression analysis removes the suitable of covariant
Sequence problem, effectively to inhibit image noise, to meet the demand of the brain function research based on Functional magnetic resonance imaging.
Summary of the invention
It is an object of the invention to propose a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed,
This method removes covariant on the outstanding ICA-AROMA policy grounds of noise suppressed performance, through optimization linear regression analysis
The type of sequence and linear regression analysis removal covariant between two steps of bandpass filtering, further effectively inhibits
The head moving noise of tranquillization state functional magnetic resonance imaging, to reach better noise suppression effect.
To achieve the goals above, the technical solution adopted by the present invention inhibits two by core image processing and image noise
Part forms, and core image processing carries out before image noise inhibition.The whole flow process of the technical solution such as Fig. 1 institute
Show, is described in detail below.
Core image processing successively comprises the following steps：(1) it goes tiltedly to handle；(2) data at several time points before removing；
(3) the dynamic correction of head；(4) overall situation 4D mean intensity is normalized；(5) Spatial normalization.The space criteria, which turns to, puts down global 4D
Tranquillization state functional magnetic resonance imaging Registration of Measuring Data after equal intensity normalization is to Montreal Neurological Institute
(MNI) normed space.
Image noise inhibition successively comprises the following steps：(1) Gaussian spatial is smooth；(2) head moving noise removes；(3) band logical
Filtering；(4) linear regression analysis removes covariant.The head moving noise removal ICA-AROMA plan outstanding using denoising performance
Slightly.It on the basis of inhibiting preprocess method based on ICA-AROMA strategy head moving noise, is optimized linear in Pruim et al. introduction
Regression analysis removes the sequence between two steps of covariant and bandpass filtering.Meanwhile covariant is removed in linear regression analysis
Increased in step 12 heads move it is relevant create disturbances to variable, i.e. 2 tastes in addition to white matter average signal and cerebrospinal fluid average signal
Disturb outside variable, further comprise 6 heads move parameter (3 translation parameters and 3 rotation parameters that are generated when the dynamic correction of head) and it
First derivative create disturbances to variable for totally 12.Further, since whether overall signal returns removal, there are inconsistent viewpoints, by it
As optional covariant.
In order to evaluate the validity of technical solution proposed by the invention, steps are as follows for the evaluation of programme taken.
(1) frame calculated between adjacent time point is displaced (Framewise Displacement, FD).Frame is displaced FD
Definition between adjacent time point 6 heads move the sum of parameter (x, y, z, α, beta, gamma) derivative absolute value, wherein D=x, y,
Z } be three orthogonal planes displacement (mm), R={ α, beta, gamma } be three orthogonal planes rotation angle (degree).Work as calculation block
Frame be displaced FD when, by calculate radius be 50mm spherome surface arc length be displaced, by rotation parameter α, β and γ be converted to away from
From.Frame is displaced FD specific formula for calculationOn
State the number that N in formula is time point, time point t={ 1 ..., N-1 }.In addition, the frame at time point t=0 is displaced FD
Value is set as 0, so that the length of frame displacement FD sequence is equal to N.
(2) related coefficient between Computational frame displacement FD and function signal.It is being calculated containing N number of frame shift value
FD sequence after, it is done into correlation analysis with the function signal Jing Guo noise suppressed, the phase of a full brain voxel is calculated
Coefficient values.
(3) cumulative distribution function of related coefficient absolute value is calculated.Full brain voxel phase relation to being calculated in step (2)
Number, calculates its cumulative distribution function after taking absolute value.Meanwhile cumulative distribution function curve graph is drawn, and the abscissa in figure | r |
The absolute value of frame displacement FD and function signal related coefficient is represented, ordinate F (| r |) represents related coefficient absolute value and is less than
Be equal to | r | value probability of occurrence accumulation and.Then, by observe different pretreatments method cumulative distribution function curve it
Between difference (the head moving noise inhibitory effect of function curve preprocess method corresponding to the longitudinal axis is better), to the present invention
The pretreatment optimization method of the tranquillization state functional magnetic resonance imaging noise suppressed of proposition is evaluated.
Since based on existing state-of-the-art method, it is as follows that the present invention proposes that the superiority of method embodies.
1, no matter linear regression analysis removal covariant and bandpass filtering which step preferentially carry out, and are grown using 14
It disturbs variable and carries out linear regression analysis removal covariant with better head moving noise inhibitory effect (Fig. 2 and Fig. 3).Namely
Say, removed in linear regression analysis 14 covariants (6 heads move parameter and their first derivative, white matter average signal and
Cerebrospinal fluid average signal) than removal 2 covariants (white matter average signal and cerebrospinal fluid average signal) can preferably inhibit head
Moving noise
2, on the basis of the type of above-mentioned linear regression analysis removal covariant selects conclusion, and then optimize linear regression point
Sequence between analysis removal covariant (14 covariants) and two steps of bandpass filtering.Two cumulative distributions as shown in Figure 4
Function curve shows that the preferential corresponding cumulative distribution function curve of bandpass filtering that carries out is some close to the longitudinal axis, therefore band logical
Filtering carries out preferably inhibiting a moving noise before linear regression analysis removes covariant.
3, about whether linear regression analysis removal is carried out to overall signal the problem of.In tranquillization state functional magnetic resonance imaging
Whether linear regression removal overall signal needs to determine according to specifically studying a question in the preprocessing process of noise suppressed.
Therefore, the optional covariant that the present invention removes overall signal as linear regression analysis.
Detailed description of the invention
Fig. 1 is the process of the pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed proposed by the present invention
Figure.
Fig. 2 and Fig. 3 is the cumulative distribution function curve of frame displacement FD and function signal related coefficient absolute value.Fig. 2 and
(6 heads move parameter and their single order to two curves in Fig. 3 with 14 covariants are removed by linear regression analysis respectively
Derivative, white matter average signal and cerebrospinal fluid average signal create disturbances to variable for totally 14) and 2 covariants (white matter average signal and brains
Spinal fluid average signal creates disturbances to variable for totally 2) tranquillization state functional magnetic resonance imaging data it is corresponding.Fig. 2 is that bandpass filtering is online
Property regression analysis removal covariant before the case where carrying out, Fig. 3 is bandpass filtering after linear regression analysis removes covariant
Progress the case where.
Fig. 4 is the cumulative distribution function curve of frame displacement FD and function signal related coefficient absolute value.Two in figure
Curve respectively with Jing Guo different disposal sequence bandpass filtering and linear regression analysis remove 14 covariants tranquillization state function
Nuclear magnetic resonance image data are corresponding.
Specific embodiment
The invention proposes a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed, this method by
Core image processing and image noise inhibit two parts to form, as shown in Figure 1.Specific embodiment is described as follows.
After acquisition obtains tranquillization state functional magnetic resonance imaging data, noise suppressed is successively carried out first and pre-processes optimization side
Five steps of the core image processing of method, detailed embodiment are as follows.
(1) it goes tiltedly to handle.Tranquillization state functional magnetic resonance imaging is gone tiltedly to correct.
(2) several time point data removals before.The data at preceding 10 time points are removed, to ensure that image data is magnetostatic
Authentic data collected under the stable condition of field.
(3) the dynamic correction of head.Different time point data is aligned using the rigid transformation of 6 parameters.
(4) normalization overall situation 4D mean intensity is 10000.
(5) Spatial normalization.MNI normed space is registrated to by image data is normalized by nonlinear transformation.
After core image processing, four that the image noise of noise suppressed pretreatment optimization method inhibits successively are carried out
Step, detailed embodiment are as follows.
(1) Gaussian spatial is smooth.The smooth scale of Gaussian spatial is 2 voxel length full width at half maximum.
(2) head moving noise removes.Using the outstanding ICA-AROMA strategy of noise suppressed performance.
(3) bandpass filtering.Bandpass filtering frequency range is 0.009-0.08Hz.
(4) linear regression analysis removes covariant.It the use of the covariant that linear regression analysis removes include that 6 heads move parameter
(3 translation parameters and 3 rotation parameters) and their first derivative, white matter average signal and cerebrospinal fluid average signal totally 14
It is a to create disturbances to variable.In addition, overall signal is as optional covariant.
Present invention optimizes the linear regression analysis removal covariants and band in the pretreatment of tranquillization state functional magnetic resonance imaging
The type of sequence and linear regression analysis removal covariant between two steps of pass filter.By observing in Fig. 2,3 and 4
Frame displacement FD and function signal related coefficient absolute value cumulative distribution function curve it is found that optimization after pretreatment side
Method obviously further suppresses the head moving noise in tranquillization state functional magnetic resonance imaging.
Claims (10)
1. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed, which is characterized in that by core image
Processing and image noise inhibit two parts to form.
2. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 1,
It is characterized in that, core image processing carries out before image noise inhibition.
3. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 1,
It is characterized in that, core image processing successively comprises the following steps：(1) it goes tiltedly to handle；(2) data at preceding 10 time points are removed；
(3) the dynamic correction of head；(4) normalization overall situation 4D mean intensity is 10000；(5) Spatial normalization.
4. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 1,
It is characterized in that, image noise inhibition successively comprises the following steps：(1) Gaussian spatial is smooth；(2) head moving noise removes；(3) band logical
Filtering；(4) linear regression analysis removes covariant.
5. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 4,
Be characterized in that, the image noise inhibit the step of (3) and (4) between, bandpass filtering linear regression analysis removal covariant
It carries out before.
6. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 4,
Be characterized in that, the image noise inhibit the step of (1) in, the smooth scale of Gaussian spatial be 2 voxel length full width at half maximum.
7. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 4,
It is characterized in that, the image noise inhibits in step (2), the head moving noise removal ICA-AROMA strategy outstanding using performance.
8. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 4,
It is characterized in that, the image noise inhibits in step (3), and bandpass filtering frequency range is 0.009-0.08Hz.
9. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 4,
Be characterized in that, the image noise inhibit the step of (4) in, using linear regression analysis remove covariant include 6 heads move
Parameter and their first derivative, white matter average signal and cerebrospinal fluid average signal create disturbances to variable for totally 14.
10. a kind of pretreatment optimization method of tranquillization state functional magnetic resonance imaging noise suppressed according to claim 9,
It is characterized in that, it is 3 translation parameters and 3 rotation parameters obtained by the dynamic correction of head that 6 head, which moves parameter,.
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| CN111227834A (en) * | 2020-01-15 | 2020-06-05 | 上海市第四人民医院 | Automatic rapid visualization method for resting brain function connection |
| CN113100780A (en) * | 2021-03-04 | 2021-07-13 | 北京大学 | Automatic processing method for synchronous brain electricity-function magnetic resonance data |
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