CN108257202A - A kind of medical image volume based on usage scenario rebuilds optimization method - Google Patents
A kind of medical image volume based on usage scenario rebuilds optimization method Download PDFInfo
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- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/758—Involving statistics of pixels or of feature values, e.g. histogram matching
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Abstract
The invention discloses a kind of medical image volumes based on usage scenario to rebuild optimization method, and including creating the template library containing several histogram features, each histogram feature sets several mapping functions and an acquiescence mapping function；Medical image input by user is obtained, calculates its histogram feature, and matching histogram feature templates library, new sequence carries out three-dimensional reconstruction to medical image using its matched acquiescence mapping function；The mapping function that user chooses is monitored, three-dimensional reconstruction is carried out to medical image, updates the frequency of use of mapping function, is set using the acquiescence mapping function that the highest mapping function of frequency is matching histogram feature templates；It monitors newly-increased/modification/and deletes histogram feature template or mapping function, then update histogram feature template library.The present invention provides a kind of methods that can be rapidly adapted to doctor individual and diagnose custom, by optimizing mapping function, volume reconstruction are made increasingly to match the usage scenario of doctor, to improve diagosis efficiency.
Description
Technical field
The present invention relates to mapping functions in medical image volume reconstruction process (to reflect including opacity mapping function and color
Penetrate function) optimum choice method, more particularly, to a kind of medical image volume reconstructed mapped letter in fixed usage scenario
Several optimization methods.
Background technology
Need to carry out rendering to three-dimensional data in volume reconstruction to show, need during this opacity mapping function and
Color mapping function.Appropriate opacity mapping function and color mapping in the different parts image reconstruction that distinct device generates
Function is different, even same image, doctor can also wish different opacity mappings when watching different tissues
Function and color mapping, to observe different pathological characters.The usage scenario of doctor is relatively fixed (CT machines, personal diagnosis
Custom), usual three-dimensional process software can initialize a color mapping table, but this mapping table is to all devices, all uses
Doctor is fixed, therefore many initial mapping tables can not meet doctor's demand well, and it is also to compare to adjust mapping table
The operation of time-consuming and inefficient.
Invention content
Doctor individual can be rapidly adapted to the purpose of the present invention is to provide one kind and diagnoses custom, optimize the side of mapping function
Method makes volume reconstruction increasingly match the usage scenario of doctor, to improve diagosis efficiency.
To achieve the above object, the technical solution adopted by the present invention is：
A kind of medical image volume based on usage scenario rebuilds optimization method, which is characterized in that includes the following steps：
Step S100：Histogram feature template library is created, includes several histogram feature templates, each histogram feature
Template Initialize installation is several for the mapping function of different display areas and an acquiescence mapping function, and the mapping function is
The combination of opacity mapping function or color mapping function or opacity mapping function and color mapping function；Record institute
State the frequency of use of mapping function；Sampled point pixel value is mapped as different opacities by the opacity mapping function
Sampled point pixel value is mapped as rgb value by value, the color mapping function, and the frequency of use is used to record current mapping function
Accumulation access times；Mapping function is given tacit consent to described in Initialize installation；
Step S101：The new sequence of medical image input by user is obtained, calculates its histogram feature；
Step S102：By the histogram feature of the new sequence of the medical image and all histograms for having stored template
Feature templates are matched, and it is matching histogram feature templates to select the highest histogram feature template of correlation；
Step S103：The acquiescence mapping function of matching histogram feature templates is searched, using the acquiescence mapping function to institute
It states the new sequence of medical image and carries out three-dimensional reconstruction drawing three-dimensional image, matching histogram feature templates are reflected according to frequency of use
Penetrate function be ranked up it is selective；
Step S104：Monitoring user operation；
Step S105：Judge whether to have chosen mapping function, step S104 is continued to execute if without selection, if monitoring choosing
Mapping function has been taken then to perform step S106；
Step S106：According to the mapping function of selection, three-dimensional reconstruction drawing three-dimensional is carried out to the new sequence of the medical image
Image；
Step S107：The frequency of use of mapping function in the matching histogram feature templates is updated, is updated to described
The ranking results of mapping function with histogram feature template are set using the highest mapping function of frequency as the matching Nogata
The acquiescence mapping function of figure feature templates.
Preferably, the opacity mapping function is a piecewise linearity scalar mapping function, any one pixel value
Corresponding opacity can be determined by the opacity mapping function；Color of the color mapping function for scalar to RGB
Mapping, is a piecewise linear maps function, the corresponding color value of any one pixel value can be true by the color mapping function
It is fixed.
Preferably, the histogram feature method of the calculating new sequence of medical image described in step S101 is：By the medicine
The pixel value range [min, max] of the new sequence of image is divided into 100 section Qk, wherein k=1,2 ..., 100；
Work as k=1, when 2 ..., 99, Qk=[min+ (max-min) * (k-1)/100, min+ (max-min) * k/100) be
Before close rear open interval；During k=100, Q100=[min+ (max-min) * 99/100, max] is closed interval；
The pixel value of the new sequence of the medical image is counted in each pixel value section QkOccurrence rate v1,v2...v100, then
The histogram feature of the new sequence of medical image is V={ v1,v2,…,v100, wherein
Preferably, the computational methods of correlation described in step S102 are：
The correlation ρ (V, V ') of any two histogram feature V and V ', then
Wherein v '0=0, v '1=0 v '101=0, v '102=0.
Preferably, it is further comprising the steps of after step S104：Step S108：It monitors whether to increase newly or changes or delete
The histogram feature template or the mapping function, if step S104 is otherwise continued to execute, if so then execute step S109；
Step S109：Update the histogram feature template library.
The present invention gives the optimum choice methods of a transparency function and color mapping table, provide initial histogram
Feature templates and mapping function template, doctor can improve and optimize mapping function, and can be quick in use
It is fitted on and meets the mapping function that doctor individual diagnoses custom, volume reconstruction is made increasingly to match the usage scenario of doctor, the present invention
Doctor can effectively be promoted and obtain best rendering effect operating efficiency, avoid and adjust mapping table repeatedly, substantially increase diagosis effect
Rate.
Description of the drawings
Fig. 1 is the flow chart of the embodiment of the present invention；
Fig. 2 is the structure diagram of histogram feature template library of the present invention.
Specific embodiment
This patent is described in further detail below through specific implementation examples and in conjunction with the accompanying drawings, but is not limited to this
A little embodiments.
As shown in Figure 1, rebuild optimization method for a kind of medical image volume based on usage scenario of the embodiment of the present invention
Flow chart, this method include：
Step S100：Create histogram feature template library, each several mapping functions of histogram feature template-setup and
One acquiescence mapping function, Initialize installation acquiescence mapping function.
Histogram feature template library is created, there is in library N number of histogram feature template, at the beginning of each histogram feature template
Beginningization sets several mapping functions for different display areas, and included acquiescence mapping function, is reflected in the present embodiment
Combination of the function for opacity mapping function and color mapping function is penetrated, i.e. user can adjust opacity mapping letter respectively
Number and color mapping function；The frequency of use of the mapping function is recorded, for recording the accumulation access times of current mapping function.
As shown in Fig. 2, this N number of histogram feature template is Vi, i=1,2 ..., N, it is a that i-th of histogram feature corresponds to K
Different opacity mapping function Ai,jAnd color mapping function Ci,j, frequency of use Ti,j, wherein j=1,2 ..., K.Histogram
Feature database is stored in the database in a manner of following two tables.Ti,jIt is initialized as 0.
Opacity mapping function is a piecewise linearity scalar mapping function, for sampled point pixel value to be mapped as not
Same opacity value, the opacity mapping function of initial setting up can be inputted after being adjusted by user, can also be by program
Fixed a few set functions are generated, the opacity mapping function of initial setting up in the present invention is for reference only.
Color mapping function is a piecewise linearity scalar mapping function, sampled point pixel value is mapped as rgb value, initially
The color mapping function of setting can be inputted after being adjusted by user, can also be by the fixed a few set functions of Program Generating, at this
The color mapping function of initial setting up in invention is for reference only.
It is (opaque to be set as acquiescence mapping function for the selection highest mapping function of frequency of use from the mapping function of establishment
Spend mapping function and color mapping function), when frequency of use is identical, choose the mapping function finally created.
Step S101：The new sequence of medical image input by user is obtained, calculates its histogram feature.
When doctor starts diagosis, need to read the new sequence of medical image input by user, its histogram feature is calculated, by such as
Lower method calculates：
The pixel value range [min, max] of medical image is divided into 100 section Qk, wherein k=1,2 ..., 100.
Work as k=1,2 ..., Q when 99k=[min+ (max-min) * (k-1)/100, min+ (max-min) * k/100), be
Before close rear open interval；Be closed interval during k=100, i.e. Q100=[min+ (max-min) * 99/100, max].
Statistical medicine image sequence pixel value is in each pixel value section QkOccurrence rate v1,v2...v100, whereinThe histogram feature for obtaining the new sequence of medical image is V={ v1,v2,…,v100}。
Step S102：Histogram feature matches, and searches out matched histogram feature template.
The histogram feature of the new sequence of medical image obtained will be calculated and stored all histogram feature moulds of template
Plate is matched, and it is matching histogram feature templates to select the highest histogram feature template of correlation.
The correlation ρ (V, V ') of two of which histogram feature V and V ' is defined as：
v′0=0, v '1=0 v '101=0, v '102The definition of=0 above-mentioned correlation has the similitude of histogram feature
The robustness of one pixel value offset.It is further noted that the definition of above-mentioned correlation does not use v1, this is in order to avoid a large amount of
Background pixel point the calculating of similarity is interfered.
Step S103：The acquiescence mapping function of matching histogram feature templates is searched, is carried out using the mapping function three-dimensional
It rebuilds, the mapping function of matching histogram feature templates is ranked up selective.
Search matching histogram feature templates acquiescence mapping function, using the acquiescence mapping function to medical image new sequence
Row carry out three-dimensional reconstruction drawing three-dimensional image, and the mapping function of the matching histogram feature templates is arranged according to frequency of use
Sequence is selected for user；
Step S104：Monitoring user operation.
The ordering mapping function that doctor can provide when watching different tissues according to step S103, according to oneself diagosis
Custom selects different opacity mapping functions and color mapping, to observe different pathological characters, meanwhile, when selection
When mapping function is unsatisfactory for requiring, need to adjust the mapping function.
Therefore two kinds that monitor user are needed to operate：(1) mapping function of matching histogram feature templates whether is had chosen；
(2) whether increase newly/change/delete histogram feature template or mapping function.
Step S105：Judge whether to have chosen mapping function, step S104 is continued to execute if without selection, if monitoring choosing
Mapping function has been taken then to perform step S106；
Step S106：According to the mapping function that user selects, to current medical image, new sequence carries out three-dimensional reconstruction drafting
3-D view；
Step S107：The frequency of use of mapping function in matching histogram feature templates is updated, is updated to matching histogram
The ranking results of the mapping function of feature templates are set using the highest mapping function of frequency as matching histogram feature templates
Give tacit consent to mapping function.
Step S108：It monitors whether to increase newly/modification/and deletes histogram feature template or mapping function, if otherwise continuing
Step S104 is performed, if so then execute step S109；
If creating new histogram feature template, increase a histogram feature, corresponding a few set mapping functions are (impermeable
Lightness mapping function and color mapping function), and initialize corresponding mapping function frequency of use.Histogram feature library is gathered around at this time
There is N+1 histogram feature, enable N=N+1.
If monitoring the original histogram feature template of modification/deletion, some histogram feature is carried out to change/delete operation.
If monitoring newly-increased/original mapping function of modification/deletion, the corresponding transparency function to some histogram feature
And color mapping function increase, and/changing/deletes operation.
Step S109：Step S108 updates histogram feature template library immediately after performing.
When the present invention is by Rapid matching histogram feature library template and record doctor's diagosis (medical image), using reflecting
The custom of function is penetrated, doctor can improve and optimize mapping function, volume reconstruction is made increasingly to match doctor in use
Usage scenario, after the method for the present invention is used for multiple times so that the mapping function recommended to doctor more meets the individual of doctor and examines
Disconnected custom, avoids and adjusts mapping table repeatedly, substantially increase diagosis efficiency.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, for the skill of this field
For art personnel, the invention may be variously modified and varied.It is all within the spirit and principle of this patent, that is made any repaiies
Change, equivalent replacement, improvement etc., should be included within the protection domain of this patent.
Claims (5)
1. a kind of medical image volume based on usage scenario rebuilds optimization method, which is characterized in that including：
Step S100：Create histogram feature template library, comprising several histogram feature templates, each histogram feature template
Initialize installation is several for the mapping function of different display areas and an acquiescence mapping function, and the mapping function is impermeable
The combination of lightness mapping function or color mapping function or opacity mapping function and color mapping function；It is reflected described in record
Penetrate the frequency of use of function；Sampled point pixel value is mapped as different opacity values, institute by the opacity mapping function
It states color mapping function and sampled point pixel value is mapped as rgb value, the frequency of use is used to record the tired of current mapping function
Product access times；Mapping function is given tacit consent to described in Initialize installation；
Step S101：The new sequence of medical image input by user is obtained, calculates its histogram feature；
Step S102：By the histogram feature of the new sequence of the medical image and all histogram features for having stored template
Template is matched, and it is matching histogram feature templates to select the highest histogram feature template of correlation；
Step S103：The acquiescence mapping function of matching histogram feature templates is searched, using the acquiescence mapping function to the doctor
It learns the new sequence of image and carries out three-dimensional reconstruction drawing three-dimensional image, according to frequency of use to the mapping letter of matching histogram feature templates
Number is ranked up selective；
Step S104：Monitoring user operation；
Step S105：Judge whether to have chosen mapping function, continue to execute step S104 if without selection, had chosen if monitoring
Mapping function then performs step S106；
Step S106：According to the mapping function of selection, three-dimensional reconstruction drawing three-dimensional image is carried out to the new sequence of the medical image；
Step S107：The frequency of use of mapping function in the matching histogram feature templates is updated, is updated straight to the matching
It is special for the matching histogram to be set using the highest mapping function of frequency for the ranking results of the mapping function of square figure feature templates
Levy the acquiescence mapping function of template.
2. a kind of medical image volume based on usage scenario according to claim 1 rebuilds optimization method, feature exists
In：The opacity mapping function is a piecewise linearity scalar mapping function, any one pixel value is corresponding opaque
Degree can be determined by the opacity mapping function；The color mapping function for scalar to the color mapping of RGB, be one point
Section linear mapping function, the corresponding color value of any one pixel value can be determined by the color mapping function.
3. optimization method is rebuild according to a kind of medical image volume based on usage scenario of claim 1-2 any one of them,
It is characterized in that：Described in step S101 calculate the new sequence of medical image histogram feature method be：
The pixel value range [min, max] of the new sequence of the medical image is divided into 100 section Qk, wherein k=1,2 ...,
100；
Work as k=1, when 2 ..., 99, Qk=[min+ (max-min) * (k-1)/100, min+ (max-min) * k/100) be before close after
Open interval；During k=100, Q100=[min+ (max-min) * 99/100, max] is closed interval；
The pixel value of the new sequence of the medical image is counted in each pixel value section QkOccurrence rate v1,v2...v100, then it is described
The histogram feature of the new sequence of medical image is V={ v1,v2,…,v100, wherein
4. optimization method is rebuild according to a kind of medical image volume based on usage scenario of claim 1-2 any one of them,
It is characterized in that：The computational methods of correlation described in step S102 are：
The correlation ρ (V, V ') of any two histogram feature V and V ', then
Wherein v '0=0, v1'=0v1′01=0, v1′02=0.
5. optimization method is rebuild according to a kind of medical image volume based on usage scenario of claim 1-2 any one of them,
It is characterized in that：It is further comprising the steps of after step S104：
Step S108：It monitors whether to increase newly or changes or delete the histogram feature template or the mapping function, if
It is no, continue to execute step S104；If so, perform step S109；
Step S109：Update the histogram feature template library.
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Cited By (2)
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| CN111599487A (en) * | 2020-05-12 | 2020-08-28 | 成都睿明医疗信息技术有限公司 | Traditional Chinese medicine compatibility assistant decision-making method based on correlation analysis |
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