CN104182932A - CT (Computed Tomography) device, CT image system and CT image generation method - Google Patents
CT (Computed Tomography) device, CT image system and CT image generation method Download PDFInfo
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Abstract
The invention provides a CT (Computed Tomography) device, a CT image system and a CT image generation method. On the premise that safety is guaranteed, the CT image quality and the CT image generation efficiency are both considered. The CT device scans a scanning area through X-rays to generate a CT image of a scanned object in the scanning area, and is provided with a reference substance device and a CT image generation device, wherein the reference substance device is arranged in a specified position in the scanning area; and according to the known CT image information of the reference substance device and scanning data, which is obtained by scanning, of the scanning area, the CT image of the scanned object is generated. When the CT image of the scanned object is generated by utilizing an iterative reconstruction way, the iterative step length can be determined especially by utilizing the known CT image information of the reference substance device as well as a reconstruction image and an updating image corresponding to the reference substance device in iteration. Therefore, iteration frequencies in iterative reconstruction can be effectively reduced, and the iterative reconstruction efficiency is improved.
Description
Technical field
The present invention relates to CT device, CT picture system and CT image generating method, relate in particular to CT device, CT picture system and the CT image generating method of for improving CT Image Iterative, rebuilding efficiency.
Background technology
X ray computer fault imaging (CT) technology has been widely used in human body to check, CT image as to medical diagnosis on disease according to the history of existing 30 years, to CT image reconstruction technique study to reduce radiation dose, improve CT picture quality, reduce image artifacts be research always with clinical in hot issue.
In practical application, CT image reconstruction technique mainly comprises filtered back projection's mode and iterative approximation mode.Wherein, filtered back projection's mode is the traditional approach of CT image reconstruction, in current CT product, is widely used.In Dan filtered back projection mode, the data for projection of reconstruction image is assumed to be noiseless interference, and in fact, noise is accompanied by data for projection and exists all the time, especially all the more so in the situation that of low-dose scanning, be therefore difficult to obtain high-quality CT image.Yet along with the development of clinic diagnosis, the breadth and depth of CT clinical practice has all day by day reached unprecedented height, under this new situation background, security consideration and picture quality that industry is used CT have all had new, higher requirement.This just makes filtered back projection's mode be difficult to meet new demand.Even in low and middle-end application, filtered back projection's mode still needs new more accurate back projection method to reduce artifact, improves picture quality.
For above new demand, in high-end applications, iterative approximation mode is taken seriously and studies.Iterative approximation mode can be processed the image artifacts that electronic noise and other physical factor cause well, thereby in the situation that guaranteeing picture quality, reduces the x-ray dose while checking.In the past, cannot practical clinical because its huge calculated amount causes image taking speed slowly.In recent years, develop rapidly along with computer hardware and computational science, iterative approximation mode is applied to actual product becomes possibility, and along with the pay attention to day by day of society to medical treatment & health, X-radiation in CT diagnosis more and more receives people's concern on the impact of health, low X-radiation dosage has become the future trend of CT development.Therefore iterative approximation mode is paid close attention to more and more widely, is current study hotspot.
Iterative reconstruction process mainly comprises repeatedly projection and back projection's process of loop iteration, in this process, the iteration of taking turns by each, the image obtaining can progressively approach ideal image, can in low noise situation, guarantee good image resolution ratio and sharpness, but often need iteration many times, length consuming time, becomes a Main Bottleneck of clinical practice.
Therefore, in current CT field, in filtered back projection's mode and iterative approximation mode, all there is technical matters separately, in the urgent need to guaranteeing under the prerequisite of security, take into account CT picture quality and CT image formation efficiency.
Summary of the invention
Based on above background, the object of the invention is to, a kind of CT device, CT picture system and CT image generating method are provided, can guarantee under the prerequisite of security, take into account CT picture quality and CT image formation efficiency.
In order to achieve the above object, the present invention relates to a kind of CT device, by X ray, scanning area is scanned, generation is arranged in the CT image of the sweep object of described scanning area, it is characterized in that possessing: reference substance device, is arranged on the assigned position in described scanning area; And CT video generation device, according to the scan-data of the known CT image information of described reference substance device and the described scanning area that obtains by scanning, generate the CT image of described sweep object.
According to CT device of the present invention, for example, by the assigned position near scanning area sweep object (human body), increase the reference substance device of CT image information known (for example given material), and when generating the CT image of sweep object, utilize the CT image information that reference substance device is known, can guarantee under the prerequisite of security, take into account CT picture quality and CT image formation efficiency.
In above-mentioned CT device, can be also that described CT video generation device utilizes the known CT image information of described reference substance device, and the scan-data of the described scanning area obtaining by scanning is carried out to iterative approximation, generates thus the CT image of described sweep object.
Thus, in iterative approximation mode, with reference to the known CT image information of reference substance device, generate the CT image of sweep object, can effectively reduce the number of times of iteration in iterative approximation, improve the efficiency of iterative approximation.Due to iterative approximation mode, to have safe and picture quality high, further improved again the efficiency of iterative approximation mode, thereby greatly improved the practicality of iterative approximation mode at this.
In above-mentioned CT device, can be also, in described iterative approximation, described CT video generation device, according to the current reconstruction image in the reference substance region at reference substance device place described in the known CT image of described reference substance device and described scanning area and new images more, determines the step-length of using in this iteration.
In iterative approximation, the size of step-length arranges the speed of convergence tool of iterative approximation is had a great impact.By utilize the known CT image of reference substance device and in iteration the corresponding reconstruction image of reference substance device and more new images from adapting to, determine iteration step length, can more suitably determine step-length, thereby the process of acceleration of iterative convergence greatly, improves the efficiency of iterative approximation mode.
In above-mentioned CT device, can be also, in described iterative approximation, in the situation that the difference between the data for projection of the current reconstruction image of the scan-data of described scanning area and described scanning area is less than the first defined threshold, described CT video generation device is used the arbitrary width in specialized range in this iteration.
In above-mentioned CT device, can be also that, in described iterative approximation, in the situation that the step-length of using in last iteration is less than the second defined threshold, described CT video generation device is used the arbitrary width in specialized range in this iteration.
At this, problem for the local optimum that may occur in utilizing the process of reference substance device decision iteration step length, by jumping out local optimum with the arbitrary width in specialized range, prevent within the scope of local optimum, vibrating and restraining and slowly maybe can not restrain, thereby improve precision and the efficiency of iteration convergence.
In above-mentioned CT device, can be also, in described iterative approximation, in the situation that the current reconstruction image in described reference substance region reaches definite quality, or the quality of the reconstruction image in described reference substance region in this iteration lower than last iteration in the situation that, described CT video generation device stops iteration.
In the prior art, sometimes cannot meet stopping criterion for iteration all the time, cause occurring iterative approximation convergence and judge the problem losing efficacy.To this, the reconstruction image setting stopping criterion for iteration based on corresponding with reference substance device, can solve the aforementioned problems in the prior, and accurately and reliably carries out iterative approximation convergence and judges.
In above-mentioned CT device, can be also, in the situation that the difference between the known CT image of described reference substance device and the current reconstruction image in described reference substance region is less than the 3rd defined threshold, the current reconstruction image that described CT video generation device is judged as described reference substance region reaches definite quality, difference between the known CT image of described reference substance device and the reconstruction image in described reference substance region in this iteration, be greater than once iteration in the situation that, the quality of reconstruction image that described CT video generation device is judged as described reference substance region in this iteration lower than on once in iteration.
At this, provide the concrete stopping criterion for iteration based on reference substance device.By according to above stopping criterion for iteration, can accurately and reliably carry out iterative approximation convergence and judge.
In above-mentioned CT device, can be also, in described iterative approximation, described CT video generation device also carries out regularization filtering processing, it is the corresponding residual image of difference between the data for projection of the reconstruction image of the scan-data of described scanning area and described scanning area to be carried out to the processing of regularization filtering that this regularization filtering is processed, in described regularization filtering is processed, described CT video generation device, according to the noise of the reconstruction image in described reference substance region, determines the filter parameter using in regularization filtering.
In the prior art, while carrying out regularization filtering processing in iterative approximation, the parameter of wave filter is set according to the noise intensity of image, but because the noise intensity obtaining exists error, causes arranging the parameter of suitable wave filter.To this, by utilizing the noise of the reconstruction image corresponding with reference substance device, can solve the problems of the prior art, the parameter of wave filter in processing, is set adaptively in regularization filtering.
In above-mentioned CT device, can be also, be configured in the annular region of described sweep object to described reference substance device one or split, in described iterative approximation, described CT video generation device will be made as 0 than the pixel value in described annular region region more in the outer part in initial pictures.
When reference substance device arranges around sweep object with annular, can think in the region in outside of this annular region and not have sweep object.Therefore, by the pixel value in the region in the outside of this annular region is made as to 0, can make initial pictures closer to net result image, thus the process of accelerating convergence, the efficiency of raising iterative approximation.
In above-mentioned CT device, can be also that the annular that described reference substance device is integrated, the rectangle of one, a plurality of rectangles of split are, a certain in a plurality of circles of split, equably round described sweep object configuration.
At this, specifically list several preferred configuration of reference substance device.Thus, can grasp more easily the allocation position of reference substance device in scanning area, thereby grasp better the CT image information of reference substance device.
In addition, in order to reach object of the present invention, the invention still further relates to a kind of CT picture system, it is characterized in that, possess above-mentioned CT device and output by the CT image output device of the CT image of the described sweep object of described CT video generation device generation.
According to CT picture system of the present invention, for example, by the assigned position near scanning area sweep object (human body), increase the reference substance device of CT image information known (for example given material), and when generating the CT image of sweep object, utilize the CT image information that reference substance device is known, can guarantee under the prerequisite of security, take into account CT picture quality and CT image formation efficiency.Thus, can export at faster speed (for example demonstration) CT image that quality is higher.
In addition, in order to reach object of the present invention, the invention still further relates to a kind of CT image generating method, according to by X ray, scanning area being scanned the scan-data obtaining, generation is arranged in the CT image of the sweep object of described scanning area, it is characterized in that, utilizes the known CT image information of the reference substance device that is arranged on the assigned position place in described scanning area, described scan-data is carried out to iterative approximation, generate thus the CT image of described sweep object; In described iterative approximation, using to scan-data carry out back projection and the image that obtains as initial reconstruction image, repeatedly carry out following step (1)～(3) until meet iteration stopping condition: the difference between the data for projection of the reconstruction image of (1) scan-data based on described scanning area and described scanning area, obtains the more new images of described scanning area; (2) according to the reconstruction image in the reference substance region at reference substance device place described in the known CT image of described reference substance device and described scanning area and new images more, determine the step-length of using in this iteration; (3) according to the reconstruction image of described scanning area and new images more, utilize the described step-length determining, obtain the new reconstruction image of described scanning area; When meeting iteration stopping condition, according to the current reconstruction image of described scanning area, generate the CT image of sweep object.
According to CT image generating method of the present invention, for example, when generating the CT image of sweep object (human body) based on iterative approximation mode, utilization is arranged on the reference substance device of the CT image information known (for example given material) at the assigned position place near scanning area sweep object, utilize especially the known CT image of reference substance device and in iteration the corresponding reconstruction image of reference substance device and more new images from adaptation determine iteration step length.Thus, can effectively reduce the number of times of iteration in iterative approximation, improve the efficiency of iterative approximation.Due to iterative approximation mode, to have safe and picture quality high, further improved again the efficiency of iterative approximation mode, thereby greatly improved the practicality of iterative approximation mode at this.
According to CT device of the present invention, CT picture system and CT image generating method, can guarantee under the prerequisite of security, take into account CT picture quality and CT image formation efficiency.Wherein, the present invention be defined in mode listed above.For example, in CT image generating method of the present invention, not only can adopt the above-mentioned adaptive step determining method based on reference substance device, but also can adopt separately or appropriately combined above-mentioned arbitrary width establishing method, the iterative approximation based on reference substance device convergence decision method, the adaptive regularization filtering parameter method to set up based on reference substance device, the iteration initialization image correcting method based on reference substance device etc.And each step in CT image generating method of the present invention can also be as Implement of Function Module.
Accompanying drawing explanation
Fig. 1 is the structural drawing of CT picture system.
Fig. 2 A is the schematic diagram of an example of the allocation position of reference substance device.
Fig. 2 B is the schematic diagram of several configuration of reference substance device.
Fig. 3 is the basic step figure of iterative approximation.
Fig. 4 A is the iterative process schematic diagram in the situation that while utilizing fixed step size, step-length is larger in the past.
Fig. 4 B is the iterative process schematic diagram in the situation that while utilizing fixed step size, step-length is less in the past.
Fig. 4 C is the iterative process schematic diagram utilizing in the situation of adaptive step.
Fig. 4 D calculates the schematic diagram of adaptive step based on reference substance device.
Fig. 4 E is the comparison diagram of the experimental result in the situation of fixed step size and adaptive step.
Fig. 5 is the comparison diagram of the experimental result in the situation of adaptive step and self-adaptation+arbitrary width.
Fig. 6 is the schematic diagram that the iterative approximation convergence based on reference substance device is judged.
Fig. 7 is the schematic diagram that the adaptive regularization filtering parameter based on reference substance device arranges.
The iteration initialization image correction that Fig. 8 describes based on reference substance device is processed.
Fig. 9 means the process flow diagram of CT image generating method of the present invention.
Figure 10 means the process flow diagram of an example of CT image generating method of the present invention.
Embodiment
First, the structure of CT picture system involved in the present invention is described.Fig. 1 is the structural drawing of CT picture system.As shown in Figure 1, CT picture system mainly comprises CT device 1 and CT image output device 2.CT device 1 for example utilizes existing X-ray scanning device, by X ray, scanning area is scanned, and generates the CT image of the sweep object that is arranged in scanning area.At this, sweep object is such as being human body etc.The CT image of the sweep object that 2 outputs of CT image output device are generated by CT device 1.At this, CT image output device 2 is typically CT image display device, shows the CT image of the sweep object being generated by CT device 1 on screen.Certainly, CT image output device is not limited to CT image display device, also can by network send the CT image being generated by CT device 1 data transmission interface, print the printer of the CT image being generated by CT device 1 etc.
The characteristic structure of CT device 1 involved in the present invention mainly comprises reference substance device 11 and CT video generation device 12.Reference substance device 11 is arranged on the assigned position in scanning area, about reference substance device 11, waits until hereinafter and describes in detail.CT video generation device 12 is for example realized by general processor or special-purpose integrated circuit, according to the scan-data of the known CT image information of reference substance device 11 and the scanning area that obtains by scanning, the CT image of generation sweep object.
Below, illustrate the reference substance device 11 that the present invention proposes.The present invention has increased reference substance device 11 newly in CT picture system.Fig. 2 A is the schematic diagram of an example of the allocation position of reference substance device.As shown in Figure 2 A, in the existing X-ray scanning device of CT device 1, swing-around trajectory 201 is swing-around trajectories of x-ray source 202 and detecting device 203.As the example with reference to thing device 11, reference substance 204 is arranged on around the body scans region 205 as sweep object.Here reference substance can consist of any solid-state high-purity material, such as being formed by metal materials such as the organic materials such as the nonmetallic materials such as silicon, synthesized polymer material or iron, copper etc., and the purity of material and consistance are more high better, contributing to like this CT image value that reference substance is corresponding is a constant, reference substance that each material produces corresponding such as the CT image informations such as CT image value in advance experiment test obtain, be known.Fig. 2 B is the schematic diagram of several configuration of reference substance device.As shown in Figure 2 B, be distributed near body scans region (figure center elliptic region) reference substance 204 around and can be the annular of one, a plurality of rectangles of the rectangle of one, split, a certain in a plurality of circles of split, equably round the body scans area configurations as sweep object.At this, the shape of reference substance 204 is not limit, and distributing position is not limit, but need to know the position of reference substance 204 in scanning area, thereby obtains the pixel region (also referred to as reference substance region) corresponding to reference substance in CT image.At this, preferably reference substance is evenly distributed in around the body scans region as sweep object, will using annular as schematic view illustrating in present disclosure.
As an embodiment of the invention, CT video generation device 12 is realized by processor, mainly comprises for the general processor unit of the controls such as basic program, parameter and is exclusively used in the iterative approximation processing unit of iterative approximation.CT video generation device 12 utilizes the known CT image information of reference substance device 11, and the scan-data of the scanning area obtaining by scanning is carried out to iterative approximation, generates thus the CT image of sweep object.
Fig. 3 is the basic step figure of iterative approximation.Below simply describe, CT device 1 for example utilizes basic X-ray scanning device reality to scan (step 301) to scanning area and obtains actual scanning data S, and actual scanning data S after filtering back projection's process (step 309) obtains the initial pictures of iterative approximation
this initial pictures is carried out to projection (step 308) and obtain calculating data for projection
then to S and
carry out difference calculating (step 302) to projection residual errors Δ S, projection residual errors Δ S is carried out to back projection's (step 303) again, obtain residual image Δ I, residual image Δ I is carried out to regularization filtering (step 304) and obtain more new images Δ UI, then judge whether all pixels of Δ UI are approximately 0(step 306), if not be approximately 0, cumulative upgrade (step 307) rebuild image, cumulative renewal is after a step-length of new images Δ UI weighting (also referred to as relaxation factor) α more, to be added on the reconstruction image that last round of loop iteration obtains,
Wherein the initial reconstructed image of first run iteration is
again to rebuilding image
carry out projection and obtain calculating the iterative process that data for projection carries out next round, until the more all pixels of new images Δ UI are approximately 0 end, reconstruction image at this moment
be the final reconstruction image of whole iterative approximation.
In iterative approximation, the process of iteration can be thought the minimized process of objective function J, in order to solve I, objective function J is minimized,
Wherein A is system matrix, and I is CT image, and S is actual scanning data, and P (I) is image prior imformation item, and the regularization filtering in iterative process embodies.Minimize the objective function solving above, generally adopt gradient descent method, thereby obtain
(formula 3)
Wherein α is the step-length (relaxation factor) in cumulative renewal process.The size of this step-length (relaxation factor) arranges iterative approximation speed of convergence tool is had a great impact, and below illustrates.
Fig. 4 A is the iterative process schematic diagram in the situation that while utilizing fixed step size, step-length is larger in the past.As shown in Figure 4 A, if larger step-length (relaxation factor) α is set, when the value of objective function J approaches minimum value I
∞or while running into local minimum, renewal process can cause target function value to vibrate near minimum value or local minimum, though iteration many times very rapid convergence to minimum value I
∞.
Fig. 4 B is the iterative process schematic diagram in the situation that while utilizing fixed step size, step-length is less in the past.As shown in Figure 4 B, when less step-length (relaxation factor) α is set, each time iteration upgrade all seldom, iterative process is very slow, needs equally iteration many times just can converge to minimum value I
∞.
Therefore,, if can adjust adaptively the size of step-length (relaxation factor) α according to the quality of rebuilding image in iterative process, the process of iteration convergence will be accelerated greatly.Fig. 4 C is the iterative process schematic diagram utilizing in the situation of adaptive step.As shown in Figure 4 C, compare with the situation of Fig. 4 A and Fig. 4 B, the process of iteration convergence is accelerated greatly.
In order to adjust adaptively the size of step-length (relaxation factor) α according to the quality of rebuilding image in iterative process, in the present invention, according to reference substance device 11, calculate adaptive step-length (relaxation factor).In iterative approximation, CT video generation device 12, according to the current reconstruction image in the reference substance region at reference substance device 11 places in the known CT image of reference substance device 11 and scanning area and new images more, determines the step-length of using in this iteration.As a concrete example, as shown in Figure 4 D, for given i wheel iteration, select a step-length (relaxation factor) α, make under this step-length (relaxation factor) α, the squared difference of rebuilding reference substance region CT image value corresponding with reference substance material after cumulative renewal in image is minimum, can be with equation expression
I wherein
rfor the known CT image of reference substance device 11, represent reference substance image-region, its value is constant, the CT image value that reference substance material is corresponding,
for the reconstruction image of current reference substance image-region, Δ UI
rmore new images for current reference substance image-region.
Fig. 4 E is the comparison diagram of the experimental result in the situation of fixed step size and adaptive step.In the emulation experiment shown in Fig. 4 E, stopping criterion for iteration is set to residual error and is less than 50, can find out, uses adaptive step (relaxation factor) method can effectively improve the speed of convergence of iteration.
As mentioned above, by utilize the known CT image of reference substance device 11 and in iteration the corresponding reconstruction image of reference substance device 11 and more new images decide iteration step length, can more suitably determine step-length, thereby the process of acceleration of iterative convergence greatly, improves the efficiency of iterative approximation mode.
Below, illustrate the variation that the above-mentioned adaptive step based on reference substance device determines.In the decision process of above-mentioned adaptive step, reference substance area image is the regional area in whole CT image, therefore, optimized step-length (relaxation factor) based on this region may make iterative process be absorbed in local optimum, although reference substance region has rebuild the precision that reaches very high, but it is optimum that whole image reconstruction result does not still reach, thereby cause stopping iteration or iteration is slow.In this case, use random step-length can effectively jump out local optimum.
As using random step-length to jump out a kind of situation of local optimum, in iterative approximation when residual error is very little but while not yet meeting stopping criterion for iteration, use random step-length to jump out local optimum.; in the situation that the difference (being residual error) between the data for projection of the current reconstruction image of the scan-data of scanning area and scanning area is less than the first defined threshold T1, CT video generation device 12 is used the arbitrary width in specialized range in this iteration.At this, above-mentioned residual error can be used projection residual errors Δ S, also can use residual image Δ I.The first defined threshold T1 generally can be set to first run iteration residual error 5% or according to concrete performance test determination.In addition, arbitrary width is the random number being controlled in certain limit, according to actual experiment, measures this random number range.
As using random step-length to jump out the another kind of situation of local optimum, when the very little but residual error of step-length not yet meets stopping criterion for iteration in iterative approximation, use random step-length to jump out local optimum.That is,, in the situation that the step-length of using in last iteration is less than the second defined threshold, CT video generation device 11 is used the arbitrary width in specialized range in this iteration.At this, the second defined threshold generally can be set to first run step-length (relaxation factor) 5% or according to concrete performance test determination.In addition, arbitrary width is the random number being controlled in certain limit, according to actual experiment, measures this random number range.
Fig. 5 is the comparison diagram of the experimental result in the situation of adaptive step and self-adaptation+arbitrary width.As shown in Figure 5, in low residual error situation (corresponding to above-mentioned the first situation), the iteration of using arbitrary width can make iteration converge to soon setting in the situation that the convergence of adaptive step successive iterations is slower stops target (meeting stopping criterion for iteration).Equally, in low step-length situation, (corresponding to above-mentioned second case), also can access similar effect.; problem for the local optimum that may occur in utilizing the process of reference substance device 11 decision iteration step lengths; by use random step-length under said circumstances, jump out local optimum; can prevent within the scope of local optimum, vibrating and restraining and slowly maybe can not restrain, thereby improve precision and the efficiency of iteration convergence.
Below, illustrate another embodiment of the invention, based on reference substance device, carry out iterative approximation convergence and judge.
In traditional iterative approximation, as described in Fig. 3, often according to new images more, whether be approximately 0 end condition that is used as iteration, or according to projection residual errors, whether be approximately 0 and be used as stopping criterion for iteration, but because projection and projection model are approximate models, more new images and projection residual errors may can not be approximately 0 all the time, cause method sometimes can lose efficacy.Therefore the present invention utilizes reference substance device 11, has proposed a kind of convergence decision procedure based on reference substance device.That is, in iterative approximation, in the situation that the current reconstruction image in reference substance region reaches definite quality, or the quality of the reconstruction image in reference substance region in this iteration lower than last iteration in the situation that, CT video generation device 12 stops iteration.
Example as the concrete stopping criterion for iteration based on reference substance device, in the situation that the difference between the known CT image of reference substance device 11 and the current reconstruction image in reference substance region is less than the 3rd defined threshold, the current reconstruction image that CT video generation device 12 is judged as reference substance region reaches definite quality.In addition, the in the situation that of in the known CT image of reference substance device 11 and the difference between the reconstruction image in reference substance region are greater than once iteration in this iteration, the quality of reconstruction image that CT video generation device 12 is judged as reference substance region in this iteration lower than on once in iteration.Below contrast the example of the above-mentioned concrete stopping criterion for iteration based on reference substance device of accompanying drawing explanation.Fig. 6 is the schematic diagram that the iterative approximation convergence based on reference substance device is judged.As shown in Figure 6, in rebuilding image, the squared difference of the reference substance region CT image value corresponding with reference substance material is less than threshold value T
stoptime, or in this iteration, this squared difference is greater than this squared difference in last iteration, stops iteration, with formula, can be expressed as
Or
(formula 5)
T wherein
stopcan be specified by user's image quality level as requested.At this, the known CT image of reference substance device 11 and difference between the reconstruction image in reference substance region are not limited to show as the squared difference of rebuilding CT image value corresponding to reference substance region and reference substance material in image, also can show by other suitable values such as absolute value of this difference, the threshold value corresponding with it is now suitably set.
In the above-mentioned iterative approximation convergence based on reference substance device is judged, because the CT image of reference substance device 11 is known, therefore with in the past, based on more new images or residual error etc., utilize the situation of approximate model to compare, can more accurately and reliably carry out iterative approximation convergence and judge.
Below, illustrate another embodiment of the invention, based on reference substance device-adaptive regularization filtering parameter is set.
In iterative approximation, regularization filtering is corresponding to the prior imformation item in objective function, such as neighbor in image, often having approximate these class prior imformations such as pixel value is fused in objective function by regularization filtering, the complex filters of often using some smoothing filters or edge to keep, as Gaussian smoothing filtering, bilateral filtering, Geman filtering etc., the parameter in these wave filters arranges according to the noise intensity of image often.But in iterative process, it is different that each takes turns the noise intensity of iteration result, in practical application, preset parameter of operated by rotary motion or according to the good part of certain consistance in image, as estimating noise intensity, certain organ-tissue region regulates, but the organ-tissue region in reconstruction image can not have crash consistency, estimate that the noise intensity obtaining also exists certain error.
For the problems referred to above of the prior art, at this, a kind of adaptive regularization filtering parameter set-up mode based on reference substance device has been proposed.; CT video generation device 12 also carries out regularization filtering processing; the corresponding residual image of difference between the data for projection of the reconstruction image of the scan-data of scanning area and scanning area is carried out to the processing of regularization filtering; in regularization filtering is processed; CT video generation device 12, according to the noise of the reconstruction image in reference substance region, determines the filter parameter using in regularization filtering.Fig. 7 is the schematic diagram that the adaptive regularization filtering parameter based on reference substance device arranges.As shown in Figure 7, calculate the standard deviation SD that rebuilds the noise in reference substance region in image
noise(step 701), then goes to arrange the parameter (step 702) of regularization wave filter according to this standard deviation, design parameter arranges according to different wave filters and difference, and for example, for Gaussian smoothing filtering, the variance in Gaussian filter is proportional to standard deviation SD
noise, stronger noise needs larger level and smooth intensity.SD
noisecomputing method as shown in the formula:
Wherein, mean is mean value function,
for reference substance area pixel in image, N is reference substance area pixel sum in all images.
Above-mentioned based on reference substance device-adaptive arrange in the embodiment of regularization filtering parameter, utilize known reference substance device 11 that regularization filtering parameter is set, compare with estimating to arrange based on experience in prior art, regularization filtering parameter can be more suitably set.Particularly at reference substance device 11, have in very high conforming situation, can regularization filtering parameter be set with high precision.
Below, illustrate another embodiment of the invention, based on reference substance device correction iteration initialization image.
The iteration initialization image correction that Fig. 8 describes based on reference substance device is processed.In iterative approximation, initial pictures is often used traditional filtered back projection's result images, but when actual projection data is incomplete, as shown in the left figure in Fig. 8, the form of the filtered back projection's image obtaining and scanning thing will have very large difference.
Consider that iterative process is the optimization procedure of objective function, if the image initial state of iteration approaches final image, can accelerate the process of iteration.Therefore, in the situation that reference substance device 11 one or split be configured in the annular region of sweep object, in iterative approximation, CT video generation device 12 will be made as 0 than the pixel value in this annular region region more in the outer part in initial pictures.That is, as shown in Figure 8, the region 801 outside reference substance device 802, owing to being all air, the value of net result image must be 0 entirely, therefore, in initialisation image, the pixel value that the region 801 outside reference substance device is set is 0.Like this can so that initial pictures closer to net result image, thereby the process of accelerating convergence.
Below, illustrate CT image generating method involved in the present invention.CT image generating method involved in the present invention can be carried out by CT device 1, more specifically can be carried out by the CT video generation device 12 of CT device 1.Fig. 9 means the process flow diagram of CT image generating method of the present invention.As shown in Figure 9, CT image generating method involved in the present invention, according to scanning area being scanned by X ray the scan-data obtaining, generates the CT image of the sweep object that is arranged in scanning area.Wherein, utilize the known CT image information of the reference substance device 12 that is arranged on the assigned position place in scanning area in CT device 1, scan-data is carried out to iterative approximation, generate thus the CT image of sweep object.
In iterative approximation, first in step S1, using to scan-data carry out back projection and the image that obtains as initial reconstruction image.Then, in step S2, the difference between the data for projection of the reconstruction image of the scan-data based on scanning area and scanning area, obtains the more new images of scanning area.In step S3, according to the reconstruction image in the reference substance region at reference substance device 11 places in the known CT image of reference substance device 11 and scanning area and new images more, determine the step-length of using in this iteration.In step S4, according to the reconstruction image of scanning area in last iteration and new images more, utilize the step-length determining, obtain the new reconstruction image of scanning area.In step S5, judge whether to meet stopping criterion for iteration, if do not meet stopping criterion for iteration, repeatedly perform step S2～S4.When meeting iteration stopping condition, according to the current reconstruction image of scanning area, generate the CT image of sweep object and finish.
According to CT image generating method of the present invention, for example, when utilizing iterative approximation mode to generate the CT image of sweep object (human body), utilization is arranged on the reference substance device of the CT image information known (for example given material) at the assigned position place near scanning area sweep object, utilize especially the known CT image of reference substance device and in iteration the corresponding reconstruction image of reference substance device and more new images decide iteration step length.Thus, can effectively reduce the number of times of iteration in iterative approximation, improve the efficiency of iterative approximation.Due to iterative approximation mode, to have safe and picture quality high, further improved again the efficiency of iterative approximation mode, thereby greatly improved the practicality of iterative approximation mode at this.
In CT image generating method of the present invention, not only can adopt the adaptive step determining method based on reference substance device in above-mentioned embodiment, but also can adopt separately or suitably in conjunction with the iterative approximation based on reference substance device in the arbitrary width establishing method in above-mentioned variation, above-mentioned other embodiments, restrain decision method, the adaptive regularization filtering parameter method to set up based on reference substance device, the iteration initialization image correcting method based on reference substance device etc.Below, illustrate an example that combines the respective embodiments described above and variation CT image generating method of the present invention afterwards.
Figure 10 means the process flow diagram of an example of CT image generating method of the present invention.First, in step 901, utilize the iteration initialization image correcting method based on reference substance device in above-mentioned embodiment to revise filtered back projection's initialisation image.Then in step 902, carry out projection and obtain data for projection.In step 903, further calculate projection residual errors.In step 904, then projection residual errors is carried out to back projection obtain residual image.In step 905, utilize in above-mentioned embodiment the adaptive regularization filtering parameter based on the setting of reference substance device to carry out regularization filtering to residual image and obtain more new images.Then in step 906, judge whether the cumulative sum of projection residual errors is less than threshold value T1.If be less than, in step 908, use the random adaptive step (relaxation factor) in above-mentioned variation.Otherwise the above-mentioned embodiment of foundation is based on reference substance device estimation self-adaptive step-length in step 907.Then in step 909, to the more adaptive step weighting obtaining in the random adaptive step obtaining in step 908 or step 907 for new images, and the cumulative reconstruction image that is updated to.In step 910, calculate noise mean square value and the standard deviation of the reference substance region respective pixel in current reconstruction image.At this, the standard deviation of calculating in step 910 regulates the parameter of next round iteration regularization filtering for self-adaptation, and the mean square value of calculating in step 910 is for carrying out the judgement of the condition of convergence.In step 911, if meet the stopping criterion for iteration based on reference substance device in above-mentioned embodiment, stop iteration and obtain net result, otherwise continue to turn back to step 902, carry out next step iteration.
In an above-mentioned example of CT image generating method, certainly can further be out of shape according to each embodiment and the variation of the CT device 1 having illustrated in this instructions.For example, in step 906, also can judge as previously mentioned whether step-length is less than the second defined threshold, when the very little but residual error of step-length not yet meets stopping criterion for iteration in iterative approximation, use random step-length to jump out local optimum.In addition, in step 911, can reach definite quality or judge in lower than last iteration and meet the condition of convergence in this iteration according to the quality of the reconstruction image in reference substance region according to the current reconstruction image in reference substance region.
Above with reference to the accompanying drawings of the specific embodiment of the present invention.Wherein, embodiment described above is only object lesson of the present invention, for understanding the present invention, and is not used in the scope of the present invention that limits.Those skilled in the art can carry out the reasonable omission of various distortion, combination and key element to embodiment based on technological thought of the present invention, the mode obtaining is thus also included within scope of the present invention.
Claims (12)
1. a CT device, scans scanning area by X ray, generates the CT image of the sweep object that is arranged in described scanning area, it is characterized in that possessing:
Reference substance device, is arranged on the assigned position in described scanning area; And
CT video generation device, according to the scan-data of the known CT image information of described reference substance device and the described scanning area that obtains by scanning, generates the CT image of described sweep object.
2. CT device as claimed in claim 1, is characterized in that,
Described CT video generation device utilizes the known CT image information of described reference substance device, and the scan-data of the described scanning area obtaining by scanning is carried out to iterative approximation, generates thus the CT image of described sweep object.
3. CT device as claimed in claim 2, is characterized in that,
In described iterative approximation, described CT video generation device, according to the current reconstruction image in the reference substance region at reference substance device place described in the known CT image of described reference substance device and described scanning area and new images more, determines the step-length of using in this iteration.
4. CT device as claimed in claim 3, is characterized in that,
In described iterative approximation, in the situation that the difference between the data for projection of the current reconstruction image of the scan-data of described scanning area and described scanning area is less than the first defined threshold, described CT video generation device is used the arbitrary width in specialized range in this iteration.
5. CT device as claimed in claim 3, is characterized in that,
In described iterative approximation, in the situation that the step-length of using in last iteration is less than the second defined threshold, described CT video generation device is used the arbitrary width in specialized range in this iteration.
6. CT device as claimed in claim 2, is characterized in that,
In described iterative approximation, in the situation that the current reconstruction image in described reference substance region reaches definite quality, or the quality of the reconstruction image in described reference substance region in this iteration lower than last iteration in the situation that, described CT video generation device stops iteration.
7. CT device as claimed in claim 6, is characterized in that,
In the situation that the difference between the known CT image of described reference substance device and the current reconstruction image in described reference substance region is less than the 3rd defined threshold, the current reconstruction image that described CT video generation device is judged as described reference substance region reaches definite quality
Difference between the known CT image of described reference substance device and the reconstruction image in described reference substance region in this iteration, be greater than once iteration in the situation that, the quality of reconstruction image that described CT video generation device is judged as described reference substance region in this iteration lower than on once in iteration.
8. CT device as claimed in claim 2, is characterized in that,
In described iterative approximation, described CT video generation device also carries out regularization filtering processing, it is the corresponding residual image of difference between the data for projection of the reconstruction image of the scan-data of described scanning area and described scanning area to be carried out to the processing of regularization filtering that this regularization filtering is processed
In described regularization filtering is processed, described CT video generation device, according to the noise of the reconstruction image in described reference substance region, determines the filter parameter using in regularization filtering.
9. CT device as claimed in claim 2, is characterized in that,
Be configured in the annular region of described sweep object to described reference substance device one or split,
In described iterative approximation, described CT video generation device will be made as 0 than the pixel value in described annular region region more in the outer part in initial pictures.
10. CT device as claimed in claim 1, is characterized in that,
The annular that described reference substance device is integrated, the rectangle of one, a plurality of rectangles of split are, a certain in a plurality of circles of split, equably round described sweep object configuration.
11. 1 kinds of CT picture systems, is characterized in that possessing:
CT device in claim 1～10 described in any one; And
CT image output device, the CT image of the described sweep object that output is generated by described CT video generation device.
12. 1 kinds of CT image generating methods, according to by X ray, scanning area being scanned the scan-data obtaining, generate the CT image of the sweep object that is arranged in described scanning area, it is characterized in that,
Utilization is arranged on the known CT image information of the reference substance device at the assigned position place in described scanning area, and described scan-data is carried out to iterative approximation, generates thus the CT image of described sweep object,
In described iterative approximation, using to scan-data carry out back projection and the image that obtains as initial reconstruction image, repeatedly carry out following step (1)～(3) until meet iteration stopping condition:
(1) difference between the data for projection of the reconstruction image of the scan-data based on described scanning area and described scanning area, obtains the more new images of described scanning area;
(2) according to the reconstruction image in the reference substance region at reference substance device place described in the known CT image of described reference substance device and described scanning area and new images more, determine the step-length of using in this iteration;
(3) according to the reconstruction image of described scanning area and new images more, utilize the described step-length determining, obtain the new reconstruction image of described scanning area;
When meeting iteration stopping condition, according to the current reconstruction image of described scanning area, generate the CT image of sweep object.
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