CN106846318A - A kind of tumour Precise Position System for medical treatment - Google Patents

A kind of tumour Precise Position System for medical treatment Download PDF

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CN106846318A
CN106846318A CN201710170977.1A CN201710170977A CN106846318A CN 106846318 A CN106846318 A CN 106846318A CN 201710170977 A CN201710170977 A CN 201710170977A CN 106846318 A CN106846318 A CN 106846318A
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tumor
ddr
registration
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CN106846318B (en
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Nanjing Huaplastic Plastics Manufacturing Co.,Ltd.
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30096—Tumor; Lesion

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • Apparatus For Radiation Diagnosis (AREA)

Abstract

The invention provides a kind of tumour Precise Position System for medical treatment, including DDR tumor images acquisition module, DR tumor images acquisition module, image registration module, tumor-localizing module；The DDR tumor images acquisition module is used for the DDR images in the patient tumors region for gathering the telltale mark point containing positioning patient tumors；The DR tumor images acquisition module is used to gather the DR images in patient tumors region；Described image registration module is used to carry out the DDR images, DR images image registration, obtains tumor-localizing parameter；The tumor-localizing module is used to reposition tumour according to the tumor-localizing parameter.The present invention can realize being accurately positioned for tumour.

Description

A kind of tumour Precise Position System for medical treatment
Technical field
The present invention relates to field of medical technology, and in particular to a kind of tumour Precise Position System for medical treatment.
Background technology
Because tumour is located in body mostly, therefore, it is still difficult point place to be accurately positioned for tumour.Due to body table The skin in face is easily moved, therefore, only by skin surface position is present than larger error.Correlation technique In, generally external devices are fixed on body and are positioned, but so can be greatly painful to sufferer band.Because patient is clapping After CT images carry out tumor-localizing, treatment system generally formulates treatment plan according to the position of the CT image tumours, but generally exists Clap CT images and formally upper therapeutic bed is treated for some time, after therapeutic bed is gone up again, its body position all can some changes Change, it is impossible to just the same with position when clapping CT images, accordingly, there exist than larger position error.
The content of the invention
Regarding to the issue above, the present invention provides a kind of tumour Precise Position System for medical treatment.
The purpose of the present invention is realized using following technical scheme：
There is provided a kind of tumour Precise Position System for medical treatment, including DDR tumor images acquisition module, DR tumour figures As acquisition module, image registration module, tumor-localizing module；The DDR tumor images acquisition module is used for collection and contains positioning The DDR images in the patient tumors region of the telltale mark point of patient tumors；The DR tumor images acquisition module is used to gather suffers from The DR images of person's tumor region；Described image registration module is used to carry out image registration to the DDR images, DR images, obtains Tumor-localizing parameter；The tumor-localizing module is used to reposition tumour according to the tumor-localizing parameter.
Beneficial effects of the present invention are：Using image registration techniques, the accurate positioning of tumour is realized.
Brief description of the drawings
Using accompanying drawing, the invention will be further described, but embodiment in accompanying drawing is not constituted to any limit of the invention System, for one of ordinary skill in the art, on the premise of not paying creative work, can also obtain according to the following drawings Other accompanying drawings.
Fig. 1 structure connection block diagrams of the invention；
Fig. 2 is the workflow diagram of DR tumor images acquisition module of the present invention.
Reference：
DDR tumor images acquisition module 1, DR tumor images acquisition module 2, image registration module 3, tumor-localizing module 4.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, the tumour Precise Position System for medical treatment that the present embodiment is provided includes that DDR tumor images gather mould Block 1, DR tumor images acquisition module 2, image registration module 3, tumor-localizing module 4；The DDR tumor images acquisition module 1 DDR images for gathering the patient tumors region of the telltale mark point containing positioning patient tumors；The DR tumor images are adopted Collection module 2 is used to gather the DR images in patient tumors region；Described image registration module 3 is used for the DDR images, DR images Image registration is carried out, tumor-localizing parameter is obtained；The tumor-localizing module 4 is used for according to the tumor-localizing parameter to tumour Reposition.
Preferably, the DDR images in the patient tumors region of telltale mark point of the collection containing positioning patient tumors, bag Include：Gather the CT images of patient, DDR images are generated according to the CT image reconstructions of patient.
Preferably, the DR images in the collection patient tumors region, including：Patient tumors region is shot from different perspectives, Obtain multiple DR images.
The above embodiment of the present invention uses image registration techniques, realizes the accurate positioning of tumour.
Preferably, referring to Fig. 2, the collection contains the patient tumors region of the telltale mark point of positioning patient tumors DDR images, also include：Using customized screening function from multiple preferable CT images of CT optical sieving mass, for weight Build generation DDR images：Wherein described customized screening function is：
Q={ Qi,Qi>0, i=1 ..., m }
Wherein
In formula, Q is the target image set after screening, ZiIt is i-th average gray value of image in multiple images, m is to adopt The quantity of the image of collection, WiIt is i-th edge sharpness of image in multiple images, W is sharp according to the edge of actual conditions setting Degree threshold value, whenWhen,When,
This preferred embodiment, the CT images after screening is used to rebuild generation DDR images, it is possible to increase the DDR figures of generation The quality degree of picture, to realize tumour, accurately positioning lays the foundation.
Preferably, image registration is carried out to the DDR images, DR images, including：
(1) DDR images are chosen as reference picture S0, DR images calculate reference picture S as image S subject to registration respectively0 With the Arimoto entropys of the entropy diagram picture of image S subject to registrationVS, define Arimoto entropys computing formula be：
In formula, VS(x,y)Represent the Arimoto entropys of the entropy diagram picture of image S (x, y), U1、U2It is the regulation parameter of setting, And U1>0,U1≠ 1, c (i, j) be centered on pixel (x, y), size as n × image block of n, wherein n is odd number,J [c (i, j)] represents the gray level of image block c (i, j), nkIt is K-th frequency of gray level appearance, A is total pixel of image block c (i, j)；
(2) based on differomorphism Demons algorithms, regard the registration of image as a gas diffusion process, give iteration The initial value Ψ of displacement field0, displacement field is updated by following iterative formula：
In formula, GδIt is Gaussian filter, δ represents the mean square deviation of Gaussian filter kernel function, and * represents convolution operation, ΨkTable Show displacement field during kth step iteration, Ψk-1Represent the displacement field during step iteration of kth -1, PSRepresent the gray scale of image S subject to registration Value,The gray value of reference picture is represented,Represent the gradient of reference picture；
(3) constantly iteration updates displacement field, if meeting the stop condition of the object function of differomorphism Demons algorithms, jumps Go out circulation and obtain final mean annual increment movement Ψ, otherwise continue to update displacement field, until reaching maximum iteration；
(4) using final mean annual increment movement Ψ as the optimal transformation between image subject to registration, reference picture S is completed0With figure subject to registration The registration of picture.
In this preferred embodiment, brief biography of a deceased person DDR images, DR image registrations are entered using aforesaid way, reduce gray scale between image The influence that difference is caused to registration result, improves the precision of image registration, so as to be advantageously implemented high-precision tumor-localizing.
Preferably, it is to realize the image registration effect that more optimizes, the object function to differomorphism Demons algorithms is carried out Optimization, introduces regularization term and gradient distribution distance in object function, and the object function after definition optimization is：
The stop condition of objective function is：
In formula,It is the regularization term for introducing, B1、B2It is weight factor, ξ (Ψk) it is displacement field Ψk Jacobian, M represents the number of pixels of lap between reference picture and image subject to registration,Represent and use Displacement field ΨkEntropy diagram picture to image subject to registration carries out deformation；For introduce gradient distribution away from From item, α is the sample point in image gradient,The gradient distribution of image S subject to registration is represented,Represent reference picture Gradient distribution.
It is same to differential in this preferred embodiment, it is contemplated that the rough problem in spatial information and registration between pixel The object function of embryo Demons algorithms is optimized, and regularization term and gradient distribution distance is introduced in object function, then Optimal solution is asked for using the object function of the differomorphism Demons algorithms after optimization, relative to traditional differomorphism Demons Algorithm, is obtained in that registration accuracy higher such that it is able to obtain the tumor-localizing effect of degree of precision.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected The limitation of scope is protected, although being explained to the present invention with reference to preferred embodiment, one of ordinary skill in the art should Work as understanding, technical scheme can be modified or equivalent, without deviating from the reality of technical solution of the present invention Matter and scope.

Claims (6)

1. a kind of for medical tumour Precise Position System, it is characterized in that, including DDR tumor images acquisition module, DR tumours Image capture module, image registration module, tumor-localizing module；The DDR tumor images acquisition module is used to gather containing fixed The DDR images in the patient tumors region of the telltale mark point of position patient tumors；The DR tumor images acquisition module is used to gather The DR images in patient tumors region；Described image registration module is used to carry out image registration to the DDR images, DR images, obtains Take tumor-localizing parameter；The tumor-localizing module is used to reposition tumour according to the tumor-localizing parameter.
2. according to claim 1 a kind of for medical tumour Precise Position System, it is characterized in that, the collection contains The DDR images in the patient tumors region of the telltale mark point of patient tumors are positioned, including：Gather patient CT images, according to trouble The CT image reconstructions generation DDR images of person.
3. according to claim 2 a kind of for medical tumour Precise Position System, it is characterized in that, the collection patient The DR images of tumor region, including：Patient tumors region is shot from different perspectives, obtains multiple DR images.
4. according to claim 3 a kind of for medical tumour Precise Position System, it is characterized in that, the collection contains The DDR images in the patient tumors region of the telltale mark point of patient tumors are positioned, is also included：Using it is customized screening function from Multiple preferable CT images of CT optical sieving mass, for rebuilding generation DDR images.
5. according to claim 4 a kind of for medical tumour Precise Position System, it is characterized in that, described is self-defined Screening function be：
Q={ Qi,Qi>0, i=1 ..., m }
Wherein
Q i = W i - W Σ i m W i × f ( Z i - 1 3 Σ i m Z i )
In formula, Q is the target image set after screening, ZiIt is i-th average gray value of image in multiple images, m is the figure of collection The quantity of picture, WiIt is i-th edge sharpness of image in multiple images, W is the edge sharpness threshold value set according to actual conditions, WhenWhen,When,
6. according to claim 5 a kind of for medical tumour Precise Position System, it is characterized in that, the DDR is schemed Picture, DR images carry out image registration, including：
(1) DDR images are chosen as reference picture S0, DR images calculate reference picture S as image S subject to registration respectively0With treat The Arimoto entropys of the entropy diagram picture of registering image SVs, define Arimoto entropys computing formula be：
V S ( x , y ) = U 2 + U 1 U 1 - 1 ( 1 - Σ k = 1 J [ c ( i , j ) ] ( n k A ) U 1 U 1 )
In formula, Vs(x,y)Represent the Arimoto entropys of the entropy diagram picture of image S (x, y), U1、U2It is the regulation parameter of setting, and U1 >0,U1≠ 1, c (i, j) be centered on pixel (x, y), size as n × image block of n, wherein n is odd number,J [c (i, j)] represents the gray level of image block c (i, j), nkIt is K-th frequency of gray level appearance, A is total pixel of image block c (i, j)；
(2) based on differomorphism Demons algorithms, regard the registration of image as a gas diffusion process, give the displacement of iteration The initial value Ψ of field0, displacement field is updated by following iterative formula：
Ψ k = G δ * [ Ψ k - 1 + ( P S - P S 0 ) ▿ S 0 ( ▿ S 0 ) 2 + ( P S - P S 0 ) 2 ]
In formula, GδIt is Gaussian filter, δ represents the mean square deviation of Gaussian filter kernel function, and * represents convolution operation, ΨkRepresent kth Displacement field during step iteration, Ψk-1Represent the displacement field during step iteration of kth -1, PSThe gray value of image S subject to registration is represented,Table Show the gray value of reference picture,Represent the gradient of reference picture；
(3) constantly iteration updates displacement field, if meeting the stop condition of the object function of differomorphism Demons algorithms, jumps out and follows Ring obtains final mean annual increment movement Ψ, otherwise continues to update displacement field, until reaching maximum iteration；
(4) using final mean annual increment movement Ψ as the optimal transformation between image subject to registration, reference picture S is completed0With matching somebody with somebody for image subject to registration It is accurate.
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CN107495978A (en) * 2017-09-20 2017-12-22 上海联影医疗科技有限公司 X-ray shooting system and image-pickup method
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CN110689550B (en) * 2019-10-12 2022-06-21 嘉应学院 High-efficiency automatic screening system and method for CT (computed tomography) images of sagittal plane of lumbar vertebra
CN113827340A (en) * 2021-09-09 2021-12-24 王其景 Navigation system and method for managing information of surgical patient

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