CN108242073A - A kind of rendering intent and rendering device - Google Patents
A kind of rendering intent and rendering device Download PDFInfo
- Publication number
- CN108242073A CN108242073A CN201611213824.2A CN201611213824A CN108242073A CN 108242073 A CN108242073 A CN 108242073A CN 201611213824 A CN201611213824 A CN 201611213824A CN 108242073 A CN108242073 A CN 108242073A
- Authority
- CN
- China
- Prior art keywords
- voxel
- data block
- data
- block
- sub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
Abstract
The invention belongs to computer graphics techniques fields, provide a kind of rendering intent and rendering device.The rendering intent includes：Volume data to be measured is divided into multiple data blocks；Obtain the data block corresponding to each voxel in the volume data to be measured；Obtain the corresponding sampling step length of data block corresponding to each voxel；The corresponding sampling step length of data block according to corresponding to each voxel, renders each voxel.Efficiently solve the problems, such as that three-D ultrasonic rendering effect is false in the prior art by the present invention.
Description
Technical field
The invention belongs to computer graphics techniques field more particularly to a kind of rendering intents and rendering device.
Background technology
The three-dimensional reconstruction of medical ultrasonic image plays a very important role in modern medicine clinical diagnosis.It will pass
The two-dimensional ct image of system is handled with three dimentional reconstruction system, can vivid display human organ on the computer screen
With the three-dimensional view of tissue.By human-computer interaction, the operations such as rotation, scaling can be carried out to the image reconstructed, make doctor
Life can more fully understand the property of lesion and its three-dimensional structure relationship with surrounding tissue, intuitively be made so as to more convenient
Clinical diagnosis.Direct Volume Rendering Techniques are that three-dimensional data is converted directly into the two dimensional image observed conducive to people, without life
Into a kind of rendering intent of intermediate geometric graphic element, its essence is resampling is synthesized with color.However, existing three-D ultrasonic volume data
Capable rendering all is shone into local light mostly, this illumination only considers that light shines directly into body surface, without considering other tables
The situation in face, there are the false problems of rendering effect.
Therefore, it is necessary to a kind of new technical solution is proposed, to solve above-mentioned technical problem.
Invention content
In consideration of it, the embodiment of the present invention provides a kind of rendering intent and rendering device, it is three-dimensional super in the prior art to solve
The false problem of sound rendering effect.
The embodiment of the present invention in a first aspect, providing a kind of rendering intent, the rendering intent includes：
Volume data to be measured is divided into multiple data blocks；
Obtain the data block corresponding to each voxel in the volume data to be measured；
Obtain the corresponding sampling step length of data block corresponding to each voxel；
The corresponding sampling step length of data block according to corresponding to each voxel, renders each voxel.
The second aspect of the embodiment of the present invention, provides a kind of rendering device, and the rendering device includes：
Division module, for volume data to be measured to be divided into multiple data blocks；
Data block acquisition module, for obtaining the data block in the volume data to be measured corresponding to each voxel；
Step-length acquisition module, for obtaining the corresponding sampling step length of data block corresponding to each voxel；
Rendering module, for the corresponding sampling step length of data block according to corresponding to each voxel, to described each
Voxel is rendered.
Existing advantageous effect is the embodiment of the present invention compared with prior art：The embodiment of the present invention draws volume data to be measured
It is divided into multiple data blocks, the data block corresponding to each voxel in the volume data to be measured can be obtained, and obtain the data block
Corresponding sampling step length renders the voxel corresponding to the data block according to the step-length, so as to fulfill to the body to be measured
Data are rendered.The embodiment of the present invention by advance to volume data to be measured divide multiple data each data block in the block from
One sampling step length of setting of adaptation when voxel each in volume data to be measured renders, obtains each voxel institute
The corresponding sampling step length of corresponding data block is carried out according to the corresponding sampling step length pair of data block voxel corresponding with the data block
It renders, i.e., volume data to be measured is rendered using piecemeal rendering, improve rendering speed and render quality, solve existing skill
The false problem of three-D ultrasonic rendering effect in art.
Description of the drawings
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description be only the present invention some
Embodiment, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the realization flow chart for the rendering intent that the embodiment of the present invention one provides；
Fig. 2 a are the rendering effect exemplary plots for being not added with illumination；Fig. 2 b are local light rendering effect exemplary plots；Fig. 2 c are fixed
The rendering effect exemplary plot of sampling；Fig. 2 d are adaptively sampled rendering effect exemplary plots；
Fig. 3 is the composition schematic diagram of rendering device provided by Embodiment 2 of the present invention.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, it is right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Embodiment one：
Fig. 1 shows the realization flow for the rendering intent that the embodiment of the present invention one provides, and details are as follows for the realization flow：
Volume data to be measured is divided into multiple data blocks by step S101.
In embodiments of the present invention, the volume data to be measured includes but not limited to medical ultrasonic image etc..
It should be noted that when being divided to the volume data to be measured, of the multiple data voxel in the block
Number is identical, can be set according to actual needs, such as each data voxel number in the block is 163。
Step S102 obtains the data block corresponding to each voxel in the volume data to be measured.
In embodiments of the present invention, can be before being rendered to the volume data to be measured, advance obtaining step S101
In sampling step length corresponding to multiple data blocks.The volume data to be measured is rendered specially in the volume data to be measured
Each voxel rendered, after being rendered to all voxels in the volume data to be measured, that is, complete to described to be measured
The rendering of volume data.When voxel each in the volume data to be measured renders, first judge that the voxel belongs to step S101
Which of data block, i.e., which of step S101 data blocks include the voxel, with piecemeal rendering efficiently solve calculating effect
Rate is low, the false problem of rendering effect.For example, the voxel A in volume data to be measured is rendered, if data block b3Including body
Plain A, it is determined that the data block corresponding to voxel A is data block b3。
Step S103 obtains the corresponding sampling step length of data block corresponding to each voxel.
In embodiments of the present invention, the corresponding sampling step length of the data block refers to by individual every in the data block
The sampling step length of every light of element.Wherein, can be a plurality of by the light line number of each data each voxel in the block.
It should be noted that in order to ensure the light that light source is irradiated to each voxel is balanced, every in voxel
When light is sampled, the light value that need to keep the voxel is constant.Wherein, the light value of voxel is the light by the voxel
Item number and the product of every light up-sampling point number, the sampled point number of every light is identical.
Optionally, the corresponding sampling step length of data block obtained corresponding to each voxel includes：
Obtain the probability of the data block corresponding to each voxel；
The probability of data block according to corresponding to each voxel calculates data block corresponding to each voxel
Aromatic entropy；
The aromatic entropy of data block according to corresponding to each voxel obtains the data block corresponding to each voxel
Corresponding sampling step length.
In embodiments of the present invention, the probability of the data block can refer to the data block to the volume data to be measured
Contribution degree.
It specifically, can be according to formula H (B)=- pilogpiCalculate the aromatic entropy of each data block.Wherein, piIt is i-th
The probability of data block, H (B) are the aromatic entropy of i-th of data block.
In embodiments of the present invention, the level that can be normalized to obtain the data block to the aromatic entropy of data block is thin
Section, the data block with higher level details improve sample frequency, and the data block with lower level details reduces sample frequency,
So as to fulfill the sampling step length of the adaptive setting data block of the height according to level of detail.When sampling step length changes, pass through
The sampling number of every light of each voxel also changes in data block, in order to keep the brightness value of the voxel constant, warp
The item number for crossing the light of the voxel also accordingly changes.
Adopting corresponding to data block is set adaptively by the height according to data block level of detail in the embodiment of the present invention
Sample step-length renders the voxel corresponding to the data block according to the sampling step length, so as to complete the wash with watercolours to volume data to be measured
Dye.According to the adaptive setting sampling step length of level of detail, depth information is effectively enhanced so as to improve the diagnosis of doctor inspection
It surveys, and rendering effect is more really, can be that patient (such as pregnant woman) provides good effect of visualization.
Optionally, the probability for obtaining the data block corresponding to each voxel includes：
Obtain the contribution degree I of the data block corresponding to each voxeli, wherein, i represents i-th of data block, and i is big
In zero integer；
Obtain the distortion factor D of the data block corresponding to each voxeli；
The number K for the data block that the testing data is divided is obtained, wherein, K is the integer more than 1；
The contribution degree I of data block according to corresponding to number K, each voxeliWith distortion factor Di, calculate described every
The probability of data block corresponding to a voxelWherein, j represents j-th of data block, and j is more than zero integer.
Illustratively, when voxel A is rendered in volume data to be measured, if data block b3Comprising voxel A, then obtain
Data block b3Contribution degree IBWith distortion factor Di, the number for the data block that volume data to be measured is divided is 53, then data block b3It is general
Rate is
Optionally, the contribution degree I for obtaining the data block corresponding to each voxeliIncluding：
Obtain the average intensity value μ of all voxels in the data block corresponding to each voxeli；
Obtain the thickness t of the data block corresponding to each voxeliWith visibility νi；
Obtain the average brightness value h of the projection of data block on the screen corresponding to each voxeli；
The average intensity value μ of all voxels in data block according to corresponding to each voxeli, each voxel institute
The thickness t of corresponding data blocki, visibility νiWith being averaged for the projection of the data block corresponding to each voxel on the screen
Brightness value hi, the contribution degree I of the data block corresponding to calculating each voxeli=μi·ti·hi·νi。
Illustratively, the voxel A in volume data to be measured is rendered, data block b3Comprising voxel A, data block b is obtained3
In each voxel intensity value, then according to data block b3In the intensity value of each voxel calculate data block b3Average intensity value
μi, and obtain data block b3Thickness tiWith visibility νi, obtain data block b3The average brightness value h projected on the screeni, finally
Data block b is calculated according to above-mentioned parameter3Contribution degree I3=μ3·t3·h3·ν3。
The distortion factor D for obtaining the data block corresponding to each voxeliIncluding：
Obtain the average intensity value μ of all voxels in the data block corresponding to each voxeliAnd standard deviation sigmai；
Data block corresponding to each voxel is divided into M sub-block, wherein, M is the integer more than zero；
Obtain the average intensity value μ of all voxels in each sub-block in the M sub-blockmAnd standard deviation sigmam,
In, m represents m-th of sub-block, and m is the integer more than zero；
Obtain the data block and the covariance of sub-block each in the M sub-block corresponding to each voxel
σim；
According to the μi、σi、μm、σmAnd σim, calculate the data block corresponding to each voxel and each subdata
The distortion factor of blockWherein, A1And A2To be more than zero integer；
The distortion factor between each two sub-block in the M sub-block is obtained, and selects the maximum distortion factor
Dmmax；
According to the DmmaxAnd dim, the distortion factor of the data block corresponding to calculating each voxel
In embodiments of the present invention, the standard deviation of all voxels of the data block refers to all voxels in the data block
Intensity value standard deviation.The standard deviation of all voxels refers to the strong of all voxels in the sub-block in the sub-block
The standard deviation of angle value.
In embodiments of the present invention, the storage organization that wavelet tree is used as each data block may be used, by each data
Block is divided into M sub-block, and using data block as father node, M sub-block of the data block is as subtree.It can pass through
FormulaIt calculates in the M sub-block between any two sub-block
Then the distortion factor selects maximum value from multiple distortion factors.Wherein, M can sets itself according to actual needs, such as by number
8 sub-blocks, A are divided into according to block1And A2Can sets itself according to actual needs, for avoiding working as μx、μy、σxAnd σyApproach
The unstability brought when zero.
Step S104, the corresponding sampling step length of data block according to corresponding to each voxel, to each voxel
It is rendered.
In embodiments of the present invention, each voxel in the volume data to be measured is rendered, that is, is over and is treated to described
Survey the rendering of volume data.
Optionally, the corresponding sampling step length of data block according to corresponding to each voxel, to described per individual
Element, which render, to be included：
The corresponding sampling step length of data block according to corresponding to each voxel, to passing through every of each voxel
Light is sampled；
According to the sampling step length, the light energy of each sampled point on every light by each voxel is calculated
And opacity；
According to the light energy and opacity of each sampled point on every light of each voxel, to described per individual
Element is rendered.
It in embodiments of the present invention,, can be with for being located at the voxel of x points in order to achieve the effect that local diffusing reflection shade
A plurality of light is projected centered on x points all into sphere.Formula can be passed throughThe light energy L of each sampled point is calculated,
Pass through formulaCalculate the opacity of each sampled point.Wherein, Δ s be sampling step length, RΩHalf for sphere
Diameter, Δ B are sampling density, and α is in order to avoid voxel is from an offset for blocking setting, can voluntarily be set according to actual needs
It is fixed.If Fig. 2 a-2d are the effect exemplary plots that are rendered using four kinds of different rendering intents to three-D ultrasonic volume data, wherein,
Fig. 2 a are the rendering effect exemplary plots for being not added with illumination, and Fig. 2 b are local light rendering effect exemplary plots, and Fig. 2 c are the wash with watercolours of fixed sample
Effect exemplary plot is contaminated, Fig. 2 d are adaptively sampled rendering effect exemplary plots used by the embodiment of the present invention.From above-mentioned four width
Adaptively sampled rendering effect is best used by the it can be seen from the figure that embodiment of the present invention, improves the true of rendering effect
Property.
Optionally, according to the light energy and opacity of each sampled point on every light of each voxel, to institute
It states each voxel to be rendered, be specifically as follows：According to the luminous energy of each sampled point on every light of each voxel
Amount and opacity cover algorithm using local environment light, each voxel are rendered.
It plays, dimensionally it should be noted that the rendering intent that the embodiment of the present invention is provided is also adapted to digital three-dimensional
The scene that reason information system etc. is rendered.
The embodiment of the present invention passes through in advance to multiple data each data block adaptive in the block of volume data to be measured division
One sampling step length of setting, when voxel each in volume data to be measured renders, obtain corresponding to each voxel
The corresponding sampling step length of data block, wash with watercolours is carried out according to corresponding with the data block voxel of the corresponding sampling step length pair of data block
Dye renders volume data to be measured using piecemeal rendering, improve rendering speed and render quality, solve the prior art
The middle false problem of three-D ultrasonic rendering effect.
Embodiment two：
Fig. 3 shows the composition schematic diagram of rendering device provided by Embodiment 2 of the present invention, for convenience of description, only shows
With relevant part of the embodiment of the present invention, details are as follows：
The rendering device includes：
Division module 31, for volume data to be measured to be divided into multiple data blocks；
Data block acquisition module 32, for obtaining the data block in the volume data to be measured corresponding to each voxel；
Step-length acquisition module 33, for obtaining the corresponding sampling step length of data block corresponding to each voxel；
Rendering module 34, for the corresponding sampling step length of data block according to corresponding to each voxel, to described every
A voxel is rendered.
Optionally, the step-length acquisition module 33 includes：
Probability acquisition submodule 331, for obtaining the probability of the data block corresponding to each voxel；
Computational submodule 332 for the probability of the data block according to corresponding to each voxel, calculates described per individual
The aromatic entropy of data block corresponding to element；
Step-length acquisition submodule 333, for the aromatic entropy of the data block according to corresponding to each voxel, described in acquisition
The sampling step length corresponding to data block corresponding to each voxel.
Optionally, the probability acquisition submodule 331 includes：
Contribution degree acquiring unit, for obtaining the contribution degree I of the data block corresponding to each voxeli, wherein, i tables
Show i-th of data block, i is the integer more than zero；
Distortion factor acquiring unit, for obtaining the distortion factor D of the data block corresponding to each voxeli；
Number acquiring unit, for obtaining the number K for the data block that the testing data is divided, wherein, K is more than 1
Integer；
Probability calculation unit, for the contribution degree I of the data block according to corresponding to number K, each voxeliAnd mistake
True degree Di, the probability of the data block corresponding to calculating each voxelWherein, j represents j-th of data block,
J is more than zero integer.
Optionally, the contribution degree acquiring unit includes：
Average intensity value obtains subelement, for obtaining the flat of all voxels in the data block corresponding to each voxel
Equal intensity value μi；
Data block parameter acquiring subelement, for obtaining the thickness t of the data block corresponding to each voxeliWith it is visible
Spend νi；
Average brightness value obtains subelement, for obtaining the projection of the data block corresponding to each voxel on the screen
Average brightness value hi；
Contribution degree obtains subelement, in the data block according to corresponding to each voxel all voxels it is average strong
Angle value μi, data block corresponding to each voxel thickness ti, visibility νiWith the data block corresponding to each voxel
The average brightness value h of projection on the screeni, the contribution degree I of the data block corresponding to calculating each voxeli=μi·
ti·hi·νi；
The distortion factor acquiring unit includes：
First parameter acquiring subelement, for obtaining being averaged for all voxels in the data block corresponding to each voxel
Intensity value μiAnd standard deviation sigmai；
Subelement is divided, for the data block corresponding to each voxel to be divided into M sub-block, wherein, M is
Integer more than zero；
Second parameter acquiring subelement, for obtaining in the M sub-block all voxels in each sub-block
Average intensity value μmAnd standard deviation sigmam, wherein, m represents m-th of sub-block, and m is the integer more than zero；
Covariance obtains subelement, for obtaining the data block corresponding to each voxel and the M sub-block
In each sub-block covariance sigmaim；
First distortion factor computation subunit, for according to the μi、σi、μm、σmAnd σim, it is right to calculate each voxel institute
The data block answered and the distortion factor of each sub-blockWherein, A1And A2
To be more than zero integer；
The distortion factor obtains subelement, for obtaining the distortion factor in the M sub-block between each two sub-block,
And select maximum distortion factor Dmmax；
Second distortion factor computation subunit, for according to the DmmaxAnd dim, calculate the number corresponding to each voxel
According to the distortion factor of block
Optionally, the rendering module 34 includes：
Submodule 341 is sampled, for the corresponding sampling step length of data block according to corresponding to each voxel, to passing through
Every light of each voxel is sampled；
Parameter computation module 342, for according to the sampling step length, calculating every light by each voxel
On each sampled point light energy and opacity；
Render submodule 343, the light energy of each sampled point on every light according to each voxel and
Opacity renders each voxel.
Rendering device provided in an embodiment of the present invention can be used in aforementioned corresponding embodiment of the method one, details referring to
The description of above-described embodiment one, details are not described herein.
The technical staff in the field can be understood that, for convenience and simplicity of description, only with above-mentioned each function
The division progress of module, can be as needed and by above-mentioned function distribution by different function moulds for example, in practical application
Block is completed, i.e. the internal structure of described device is divided into different function modules, and hardware both may be used in above-mentioned function module
Form is realized, can also be realized in the form of software.In addition, the specific name of each function module is also only to facilitate mutually
Difference is not limited to the protection domain of the application.
In conclusion the embodiment of the present invention passes through in advance to multiple data each data in the block of volume data to be measured division
One sampling step length of setting of block adaptive when voxel each in volume data to be measured renders, obtains described per individual
The corresponding sampling step length of data block corresponding to element, according to the corresponding sampling step length pair of data block voxel corresponding with the data block
It is rendered, i.e., volume data to be measured is rendered using piecemeal rendering, improve rendering speed and render quality, solved existing
There is the false problem of three-D ultrasonic rendering effect in technology.
Those of ordinary skill in the art are further appreciated that all or part of the steps of the method in the foregoing embodiments are can
It is completed with instructing relevant hardware by program, the program can be stored in a computer read/write memory medium
In, the storage medium, including ROM/RAM, disk, CD etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of rendering intent, which is characterized in that the rendering intent includes：
Volume data to be measured is divided into multiple data blocks；
Obtain the data block corresponding to each voxel in the volume data to be measured；
Obtain the corresponding sampling step length of data block corresponding to each voxel；
The corresponding sampling step length of data block according to corresponding to each voxel, renders each voxel.
2. rendering intent according to claim 1, which is characterized in that the data obtained corresponding to each voxel
The corresponding sampling step length of block includes：
Obtain the probability of the data block corresponding to each voxel；
The probability of data block according to corresponding to each voxel calculates the aromatic of data block corresponding to each voxel
Entropy；
The aromatic entropy of data block according to corresponding to each voxel, the data block institute obtained corresponding to each voxel are right
The sampling step length answered.
3. rendering intent according to claim 2, which is characterized in that the data obtained corresponding to each voxel
The probability of block includes：
Obtain the contribution degree I of the data block corresponding to each voxeli, wherein, i represents i-th of data block, and i is more than zero
Integer；
Obtain the distortion factor D of the data block corresponding to each voxeli；
The number K for the data block that the testing data is divided is obtained, wherein, K is the integer more than 1；
The contribution degree I of data block according to corresponding to number K, each voxeliWith distortion factor Di, calculate described per individual
The probability of data block corresponding to elementWherein, j represents j-th of data block, and j is more than zero integer.
4. according to the method described in claim 3, it is characterized in that, described obtain data block corresponding to each voxel
Contribution degree IiIncluding：
Obtain the average intensity value μ of all voxels in the data block corresponding to each voxeli；
Obtain the thickness t of the data block corresponding to each voxeliWith visibility νi；
Obtain the average brightness value h of the projection of data block on the screen corresponding to each voxeli；
The average intensity value μ of all voxels in data block according to corresponding to each voxeli, corresponding to each voxel
Data block thickness ti, visibility νiWith the average brightness of the projection of the data block corresponding to each voxel on the screen
Value hi, the contribution degree I of the data block corresponding to calculating each voxeli=μi·ti·hi·νi；
The distortion factor D for obtaining the data block corresponding to each voxeliIncluding：
Obtain the average intensity value μ of all voxels in the data block corresponding to each voxeliAnd standard deviation sigmai；
Data block corresponding to each voxel is divided into M sub-block, wherein, M is the integer more than zero；
Obtain the average intensity value μ of all voxels in each sub-block in the M sub-blockmAnd standard deviation sigmam, wherein, m
Represent m-th of sub-block, m is the integer more than zero；
Obtain the data block and the covariance sigma of sub-block each in the M sub-block corresponding to each voxelim；
According to the μi、σi、μm、σmAnd σim, calculate the data block corresponding to each voxel and each sub-block
The distortion factorWherein, A1And A2To be more than zero integer；
The distortion factor between each two sub-block in the M sub-block is obtained, and selects maximum distortion factor Dmmax；
According to the DmmaxAnd dim, the distortion factor of the data block corresponding to calculating each voxel
5. rendering intent according to any one of claims 1 to 4, which is characterized in that described according to each voxel institute
The corresponding sampling step length of corresponding data block, to each voxel render and includes：
The corresponding sampling step length of data block according to corresponding to each voxel, to every light by each voxel
It is sampled；
According to the sampling step length, light energy and resistance of the calculating by each sampled point on every light of each voxel
Luminosity；
According to the light energy and opacity of each sampled point on every light of each voxel, to each voxel into
Row renders.
6. a kind of rendering device, which is characterized in that the rendering device includes：
Division module, for volume data to be measured to be divided into multiple data blocks；
Data block acquisition module, for obtaining the data block in the volume data to be measured corresponding to each voxel；
Step-length acquisition module, for obtaining the corresponding sampling step length of data block corresponding to each voxel；
Rendering module, for the corresponding sampling step length of data block according to corresponding to each voxel, to each voxel
It is rendered.
7. rendering device according to claim 6, which is characterized in that the step-length acquisition module includes：
Probability acquisition submodule, for obtaining the probability of the data block corresponding to each voxel；
For the probability of the data block according to corresponding to each voxel, it is right to calculate each voxel institute for computational submodule
The aromatic entropy for the data block answered；
Step-length acquisition submodule for the aromatic entropy of the data block according to corresponding to each voxel, obtains described per individual
The sampling step length corresponding to data block corresponding to element.
8. rendering device according to claim 7, which is characterized in that the probability acquisition submodule includes：
Contribution degree acquiring unit, for obtaining the contribution degree I of the data block corresponding to each voxeli, wherein, i represents i-th
A data block, i are the integer more than zero；
Distortion factor acquiring unit, for obtaining the distortion factor D of the data block corresponding to each voxeli；
Number acquiring unit, for obtaining the number K for the data block that the testing data is divided, wherein, K is whole more than 1
Number；
Probability calculation unit, for the contribution degree I of the data block according to corresponding to number K, each voxeliAnd the distortion factor
Di, the probability of the data block corresponding to calculating each voxelWherein, j represents j-th of data block, and j is big
In zero integer.
9. rendering device according to claim 8, which is characterized in that the contribution degree acquiring unit includes：
Average intensity value obtains subelement, for obtaining the average strong of all voxels in the data block corresponding to each voxel
Angle value μi；
Data block parameter acquiring subelement, for obtaining the thickness t of the data block corresponding to each voxeliWith visibility νi；
Average brightness value obtains subelement, for obtaining the flat of the projection of the data block corresponding to each voxel on the screen
Equal brightness value hi；
Contribution degree obtains subelement, for the average intensity value of all voxels in the data block according to corresponding to each voxel
μi, data block corresponding to each voxel thickness ti, visibility νiShielding with the data block corresponding to each voxel
The average brightness value h of projection on curtaini, the contribution degree I of the data block corresponding to calculating each voxeli=μi·ti·hi·
νi；
The distortion factor acquiring unit includes：
First parameter acquiring subelement, for obtaining the mean intensity of all voxels in the data block corresponding to each voxel
Value μiAnd standard deviation sigmai；
Divide subelement, for the data block corresponding to each voxel to be divided into M sub-block, wherein, M for more than
Zero integer；
Second parameter acquiring subelement, for obtaining in the M sub-block being averaged for all voxels in each sub-block
Intensity value μmAnd standard deviation sigmam, wherein, m represents m-th of sub-block, and m is the integer more than zero；
Covariance obtains subelement, every in data block and the M sub-block corresponding to each voxel for obtaining
The covariance sigma of a sub-blockim；
First distortion factor computation subunit, for according to the μi、σi、μm、σmAnd σim, calculate corresponding to each voxel
Data block and the distortion factor of each sub-blockWherein, A1And A2It is big
In zero integer；
The distortion factor obtains subelement, for obtaining the distortion factor in the M sub-block between each two sub-block, and selects
Take out maximum distortion factor Dmmax；
Second distortion factor computation subunit, for according to the DmmaxAnd dim, calculate the data block corresponding to each voxel
The distortion factor
10. according to claim 6 to 9 any one of them rendering device, the rendering module includes：
Submodule is sampled, for the corresponding sampling step length of data block according to corresponding to each voxel, to by described every
Every light of a voxel is sampled；
Parameter computation module, for according to the sampling step length, calculating every on every light by each voxel
The light energy and opacity of a sampled point；
Rendering submodule, the light energy and opacity of each sampled point on every light according to each voxel,
Each voxel is rendered.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611213824.2A CN108242073A (en) | 2016-12-23 | 2016-12-23 | A kind of rendering intent and rendering device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611213824.2A CN108242073A (en) | 2016-12-23 | 2016-12-23 | A kind of rendering intent and rendering device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108242073A true CN108242073A (en) | 2018-07-03 |
Family
ID=62703909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611213824.2A Pending CN108242073A (en) | 2016-12-23 | 2016-12-23 | A kind of rendering intent and rendering device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108242073A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109745704A (en) * | 2018-11-19 | 2019-05-14 | 苏州蜗牛数字科技股份有限公司 | A kind of management method of voxel landform |
| CN111402349A (en) * | 2019-01-03 | 2020-07-10 | 百度在线网络技术（北京）有限公司 | Rendering method, rendering device and rendering engine |
-
2016
- 2016-12-23 CN CN201611213824.2A patent/CN108242073A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| TIANJIN ZHANG 等: "Realistic Rendering of 3D Fetal Ultrasound via Local Ambient Occlusion", 《JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109745704A (en) * | 2018-11-19 | 2019-05-14 | 苏州蜗牛数字科技股份有限公司 | A kind of management method of voxel landform |
| CN109745704B (en) * | 2018-11-19 | 2022-09-09 | 苏州蜗牛数字科技股份有限公司 | Voxel terrain management method |
| CN111402349A (en) * | 2019-01-03 | 2020-07-10 | 百度在线网络技术（北京）有限公司 | Rendering method, rendering device and rendering engine |
| CN111402349B (en) * | 2019-01-03 | 2023-09-08 | 百度在线网络技术（北京）有限公司 | Rendering method, rendering device and rendering engine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lawonn et al. | A survey on multimodal medical data visualization | |
| Preim et al. | Visualization in medicine: theory, algorithms, and applications | |
| Johnson et al. | MDCT angiography with 3D rendering: a novel cinematic rendering algorithm for enhanced anatomic detail | |
| Preim et al. | Visual computing for medicine: theory, algorithms, and applications | |
| Kreiser et al. | A survey of flattening‐based medical visualization techniques | |
| CN103279975B (en) | Indicate the method and system of the light direction of volume rendered images | |
| US10580181B2 (en) | Method and system for generating color medical image based on combined color table | |
| Mistelbauer et al. | Vessel visualization using curvicircular feature aggregation | |
| Wiemker et al. | A radial structure tensor and its use for shape-encoding medical visualization of tubular and nodular structures | |
| Hachaj et al. | Framework for cognitive analysis of dynamic perfusion computed tomography with visualization of large volumetric data | |
| Huang et al. | 3D reconstruction and visualization from 2D CT images | |
| CN108242073A (en) | A kind of rendering intent and rendering device | |
| Wilson et al. | Interactive multi-volume visualization | |
| Cutroneo et al. | In vivo CT direct volume rendering: a three-dimensional anatomical description of the heart | |
| JP2021107019A (en) | Apparatus and method for visualizing digital breast tomosynthesis and anonymized data export | |
| Turlington et al. | New techniques for efficient sliding thin-slab volume visualization | |
| Jainek et al. | Illustrative hybrid visualization and exploration of anatomical and functional brain data | |
| Levin et al. | Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware | |
| US10347032B2 (en) | Slice representation of volume data | |
| van Dixhoorn et al. | BrainCove: A Tool for Voxel-wise fMRI Brain Connectivity Visualization. | |
| John et al. | Navigating and visualizing three-dimensional data sets | |
| CN105615906B (en) | For determining method, computer program, machine readable data medium and the imaging device of composograph | |
| Schultz et al. | Virtual Klingler dissection: Putting fibers into context | |
| Fiorentino et al. | Cinematic rendering technique in adult congenital heart disease | |
| Kwon et al. | GPU-accelerated 3D mipmap for real-time visualization of ultrasound volume data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180703 |