CN106157275A - Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen - Google Patents

Abstract

The invention discloses a kind of multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen.On the basis of original CT image reference frequency, based on isotropism thermic vibrating screen, original CT image is done multi-resolution decomposition, image detail and noise are decomposed little yardstick subspace, and image background decomposes large scale subspace on a large scale.Described original CT image is for containing noisy CT image owing to preparation amount limits.Setting a removing-noise strength coefficient, this coefficient is used for controlling multi-resolution decomposition process.With anisotropy thermic vibrating screen or punishment weighted least squares (PWLS) algorithm, to CT image denoising in each yardstick；Removing-noise strength coefficient, controls removing-noise strength in yardstick simultaneously.Residual edge after denoising is smoothed, strengthen and compensates, reduce image detail loss.To all yardstick denoisings, strengthen, compensate after CT image sue for peace according to pixel, finally synthesized CT image so that while CT image denoising, marginal information keeps good.

Description

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen

Technical field

The present invention relates to engineering in medicine technical field, be specifically related to a kind of multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen.

Background technology

X-ray that X ray CT bulb sends can produce ionization to body material, discharges the electron stream of higher-energy, strikes off chromosome double-spiral structure in nucleus, makes hereditary material morph, cause cancer.Propose for this International Commission on Radiological Protection (ICRP) and famous the lowest obtain (ALARA) radiation safety criterion, it is desirable to take rational method to reduce radiation dose release as much as possible.Under total radiation dosage limits, X ray CT image usually shows relatively very noisy, it is therefore desirable to take measures to improve CT signal noise ratio (snr) of image under keeping spatial resolution premise.

Under total radiation dosage limits, X ray CT image usually shows relatively very noisy.Traditional images territory denoising method, owing to the most finely considering signal and Noise Criterion, after process, image usually signal to noise ratio cannot be taken into account with spatial resolution index simultaneously, causes CT picture quality cannot fully meet clinical diagnosis requirement.

Summary of the invention

For prior art shortcoming, the present invention proposes a kind of multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen, including:

1. multi-resolution decomposition

The present invention utilizes image area Multiresolution Decompositions Approach based on isotropism thermic vibrating screen, considers yardstick residing for signal and noise subtly.CT picture frequency is decomposed by image area Multiresolution Decompositions Approach by amplitude size so that image detail and noise decompose little yardstick subspace, and image background decomposes large scale subspace on a large scale.

According to following isotropism thermic vibrating screen:

(1-1) $\frac{\∂}{\∂t}f(x,t)=\mathrm{d\Δf}(x,t),f(x,0)=f\left(x\right),t\≥0,$

(1-2) $f(x,t)=G(x,{\mathrm{\σ}}^2)\⊗f(x,0),\mathrm{\σ}=2\mathrm{dt},$

Arbitrfary point during wherein x represents the two dimension real space；F (x) represents original CT image itself；Isotropism thermic vibrating screen can be expressed as formula (1-1), t express time, and d represents thermal conduction constant；Formula (1-1) result is equivalent to formula (1-2)；SymbolRepresent two-dimensional convolution；G (x, σ²) it is Gaussian convolution core；

Input original CT image as shown in Figure 3, in conjunction with above-mentioned formula, according to image area multi-resolution decomposition and the denoising schematic diagram of Fig. 1, processes with original CT image.It is defined as the f (x) function about time t, sets initial time as 0, available first pending CT view data.Again by formula (1-1) thermal diffusion to first time point t₁, available second pending CT view data, calculate these two CT images in the data difference of respective pixel position, original CT image data separating can be become different scale images.This process can use equation below to represent:

f_s(x)=f (x, t_s)-f (x, t_s-1), t_s＞ t_s-1, t₀=0, s=1,2 ..., S,

Wherein s represents that scale parameter, S represent yardstick sum, t_sRepresent the corresponding diffusion time of yardstick s, t_sSetting depend on original CT image reference frequency f_r；

Scale Decomposition core algorithm can be clearly drawn: by original CT image function f (x) isotropism thermal diffusion to time point t according to this formula_sObtain f (x, t_s), then with previous time point function f (x, t_s-1) contrast, its difference f_sX () is the image function comprising part random perturbation noise and portion of tissue under yardstick s.

2. metric space denoising

After CT picture frequency is decomposed different scale subspace by amplitude size by the present invention, under each subspace, Different Strategies (such as anisotropy thermic vibrating screen or PWLS algorithm), different parameters is taked to carry out denoising targetedly.

Denoising process based on anisotropy thermic vibrating screen is as follows:

(3-1) $\frac{\∂u(x,t)}{\∂t}\▿\·(c_d(x,t)\▿u(x,t)),\left(1\right)$

(3-2) $c_d(x,t)=\left\{\begin{array}{c}1,|\▿u_{\mathrm{\σ}}(x,t)|=0\\ 1-e^{-C_q/{|\▿u_{\mathrm{\σ}}(x,t)/\mathrm{\λ}|}^q},|\▿u_{\mathrm{\σ}}(x,t)|>0\end{array}\right.$

Formula (3-1) is the general expression of anisotropy thermic vibrating screen, and (x t) is image u (x) function at time t to u；In formula (3-1), c_d(x t) is anisotropy thermal diffusion coefficient；With● represent gradient and divergence operator respectively；c_d(x, t) can be expressed as formula (3-2), and in formula (3-2), reduced parameter lambda definition is diffusion strength, and preset parameter q ＞ 1 is defined as diffusion conversion, u_σ(x t) is CT image u (x, t) convolution with standard deviation sigma as Gaussian kernel；Work as c_d(x, when t) determining, (x t) can restrain u iteratively.

In conjunction with above-mentioned formula, after Fig. 3 original CT image is carried out Scale Decomposition according to isotropism thermal diffusion；Each yardstick is carried out anisotropy thermic vibrating screen or PWLS algorithm；Carry out reasonable noise reduction when estimating its true picture trend, while effective noise reduction, reduce loss of detail.

3. residual edge smooths, strengthens and compensates

The present invention is with reference to prior art, even if taking multi-resolution decomposition and process, after denoising, image detail loses unavoidably, therefore needs to take specific policy to smooth residual edge, strengthens (such as DoG Operator Method) and compensates (feed back to denoising after image in).

As in figure 2 it is shown, original CT image is resolved into different scale images by inventive algorithm, different scale images is carried out anisotropy thermic vibrating screen denoising.After denoising, the loss of its detail edges is inevitable, and CT image border is extremely important, image before after denoising is contrasted by the present invention, use DoG to carry out enhancing and the compensation at yardstick edge, and to all yardstick denoisings, strengthen, compensates after CT image according to pixel summation, finally synthesized CT image, making while CT image denoising, marginal information keeps good.

4. accommodation

Make adjustable parameter r and the CT system imaging parameter in front 3 steps (kVp, mAs and wave filter etc.) be associated, and this association is the most nonlinear, it is predetermined to need.This is also based on die body calibration experiment and carries out the reason place of accommodation, adjusts result and is stored in CT system with look-up table.

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen, it is characterised in that set a removing-noise strength coefficient, be used for controlling multi-resolution decomposition process, arranges removing-noise strength coefficient r, controls removing-noise strength in yardstick, and removing-noise strength coefficient r setting up procedure is as follows:

D ← rd, c_d(x, t) ← rc_d(x, t).

Compared with prior art, the correction result precision of based on thermic vibrating screen the multiple dimensioned CT Image denoising algorithm of the present invention is high, and it is fast to revise the speed of service, is the original CT image of 512 × 512 for size, and erection rate is less than 2 minutes.

Accompanying drawing explanation

Fig. 1 is image area multi-resolution decomposition and denoising schematic diagram；

Fig. 2 is image area metric space edge compensation and enhancing schematic diagram；

Fig. 3 is original CT image；

Fig. 4 is multi-resolution decomposition image, (a) smallest dimension, display window [0 0.0005]；(b) secondary little yardstick, display window [0 0.0011]；(c) secondary large scale, display window [0 0.0015]；(d) out to out, display window [0.015 0.025]；

Denoising image in each yardstick of Fig. 5, (a) smallest dimension, display window [0 0.0005]；(b) secondary little yardstick, display window [0 0.0011]；(c) secondary large scale, display window [0 0.0015]；(d) out to out, display window [0.015 0.025]；

Image, (a) smallest dimension, display window [0 0.0005] is compensated in each yardstick of Fig. 6；(b) secondary little yardstick, display window [0 0.0011]；(c) secondary large scale, display window [0 0.0015]；(d) out to out, display window [0.015 0.025]；

Fig. 7 is that denoising synthesizes CT image；

Differential image between Fig. 8 original image and denoising composograph；

Detailed description of the invention

Describe the present invention below in conjunction with the drawings and specific embodiments.

The most in one embodiment, the original CT image that input CT machine gathers, original CT image containing much noise, verifies the related algorithm of the present invention significant degree to CT image denoising due to imaging dose limitation.

2. in technique scheme, described original CT image such as Fig. 3, it is possible to find containing the biggest noise in image.With original CT image reference frequency f_rOn the basis of=0.6lp/mm, based on isotropic diffusion equation, original CT image is done image area multi-resolution decomposition, can get multi-resolution decomposition image such as Fig. 4.

3. in technique scheme, described image detail and noise decompose little yardstick subspace, and image background decomposes large scale subspace on a large scale, use removing-noise strength coefficient r to control multi-resolution decomposition process simultaneously.

4. in technique scheme, described with anisotropy thermic vibrating screen or PWLS algorithm, to image denoising in each yardstick；Removing-noise strength coefficient r, controls removing-noise strength in yardstick simultaneously；See denoising image in each yardstick of Fig. 5.

5. in technique scheme, described residual edge after denoising smoothed, strengthen and compensate, reduce image detail loss；Image after available Fig. 6-compensation so that at image denoising simultaneously, marginal information keeps good.

6. in technique scheme, described to all yardstick denoisings, strengthen, compensate after image sue for peace according to pixel, finally give denoising synthesis CT image such as Fig. 7.

7. go up described detailed description of the invention technical scheme and beneficial effect have been described in detail; it it should be understood that described only presently most preferred embodiment of the invention; it is not limited to the present invention; all made in the spirit of the present invention any amendment, supplement and equivalent etc., should be included within the scope of the present invention.

Claims (8)

1. a multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen, it is characterised in that including:

(1) on the basis of original CT image reference frequency, based on isotropism thermic vibrating screen, original CT image is done multi-resolution decomposition, image detail and noise are decomposed little yardstick subspace, and image background decomposes large scale subspace on a large scale；Described original CT image is for containing noisy CT image owing to preparation amount limits；

(2) setting a removing-noise strength coefficient, this coefficient is used for controlling multi-resolution decomposition process；

(3) with anisotropy thermic vibrating screen or punishment weighted least squares (PWLS) algorithm, to CT image denoising in each yardstick；Removing-noise strength coefficient, controls removing-noise strength in yardstick simultaneously；

(4) residual edge after denoising smoothed, strengthen and compensate, reduce image detail loss；

(5) to all yardstick denoisings, strengthen, compensate after CT image sue for peace according to pixel, finally synthesized CT image so that while CT image denoising, marginal information keeps good.

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen the most according to claim 1, it is characterised in that described step (1) isotropism thermic vibrating screen is as follows:

Arbitrfary point during wherein x represents the two dimension real space；F (x) represents original CT image itself；Isotropism thermic vibrating screen can be expressed as formula (1-1), t express time, and d represents thermal conduction constant；Formula (1-1) result is equivalent to formula (1-2)；SymbolRepresent two-dimensional convolution；G (x, σ²) it is Gaussian convolution core.

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen the most according to claim 1, it is characterised in that described step (1) multi-resolution decomposition process is as follows:

(1-3) f_s(x)=f (x, t_s)-f (x, t_s-1), t_s＞ t_s-1, t₀=0, s=1,2 ..., S,

Wherein s represents that scale parameter, S represent yardstick sum, t_sRepresent the corresponding diffusion time of yardstick s, t_sSetting depend on original CT image reference frequency f_r。

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen the most according to claim 1, it is characterised in that setting a removing-noise strength coefficient, be used for controlling multi-resolution decomposition process, described step (2) processes by the following method:

(2-1) d←rd。

5. multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen as claimed in claim 1, it is characterised in that described step (3) denoising based on anisotropy thermic vibrating screen process is as follows:

Formula (3-1) is the general expression of anisotropy thermic vibrating screen, and (x t) is image u (x) function at time t to u；In formula (3-1), c_d(x t) is anisotropy thermal diffusion coefficient；WithRepresent gradient and divergence operator respectively；c_d(x, t) can be expressed as formula (3-2), and in formula (3-2), reduced parameter lambda definition is diffusion strength, and preset parameter q ＞ 1 is defined as diffusion conversion, u_σ(x t) is CT image u (x, t) convolution with standard deviation sigma as Gaussian kernel；Work as c_d(x, when t) determining, (x t) can restrain u iteratively.Similarly, based on PWLS algorithm denoising, do not repeat them here.

6. multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen as claimed in claim 1, it is characterised in that arranging removing-noise strength coefficient r, control removing-noise strength in yardstick, described step (3) removing-noise strength coefficient r setting up procedure is as follows:

(3-3) c_d(x, t) ← rc_d(x, t)

Similarly, based on PWLS algorithm denoising, regular coefficient is amplified r times.

7. multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen as claimed in claim 1, it is characterised in that described step (4) carries out strengthening and compensating by following process:

(4-1) to image subtraction before and after each yardstick denoising, residual image is obtained；Residual image is done smooth, strengthen, then feedback compensation is in image after each yardstick denoising.

Multiple dimensioned CT Image denoising algorithm based on thermic vibrating screen the most according to claim 1, it is characterised in that described step (5) is processed by following integration.

(5-1) to image after each scale processing, sue for peace according to pixel, obtain final composograph.