CN109993159A - Window setting method and device for image diagnostic system - Google Patents
Window setting method and device for image diagnostic system Download PDFInfo
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/0002—Inspection of images, e.g. flaw detection
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The present invention provides a kind of window setting method and device for image diagnostic system.Window setting device determines target object source point and its background source point in image；According to the target object source point and the background source point, interested targeted object region and corresponding background area are determined respectively；According to the pixel grey scale mean value of the targeted object region and the pixel grey scale mean value of the background area, according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance, corresponding target object desired display gray scale and background desired display gray scale are determined；According to the pixel grey scale mean value and the target object desired display gray scale of the pixel grey scale mean value of the targeted object region and the background area and the background desired display gray scale, target window width and the target window position of display window setting are determined.Window setting of the invention is based on human visual system, is most suitable for macroscopic picture contrast to provide for user.
Description
Technical field
The present invention relates to diagnostic imaging fields, more particularly, to the window setting of image diagnostic system.
Background technique
In current medical image diagnosis field, observer is still the pass diagnosed to subjective read with evaluation of image
Key means and important foundation.Observer directly affects the quality of diagnosis to the eye impressions of image, and for displaying images
Window setting then directly determines the visibility of observation object.
For different clinical purpose and application, the CT system of all devices manufacturer both provides specific preset window
Mouth setting.However, these are not adequate.Sometimes, even to identical clinical application, the setting of these windows preset,
Can not be between different image diagnosing equipments or the condition of scanning that same category of device is different between, consistent vision print is provided
As.In addition, observer can manually adjust window setting according to the specific region of its real concern in many cases, and it is this
The subjective operation of individual based on experience and preference, not only extends Diagnostic Time, will also between different observers, it is even same
One observer brings the deviation of display and eye impressions between difference observing time.
Therefore, by display window be arranged adaptive adjustment, come for observer provide it is a kind of be most suitable for eye-observation,
The image vision impression of stable and consistent, has important practical significance and application value.
Summary of the invention
In view of this, the present invention provides a kind of window setting method and device for image diagnostic system.
According to the first aspect of the invention, a kind of window setting method for image diagnostic system is provided, wherein should
Method includes:
Determine the target object source point and its background source point in image；
According to the target object source point and the background source point, determine respectively interested targeted object region and
Corresponding background area；
According to the pixel grey scale mean value of the targeted object region and the pixel grey scale mean value of the background area, foundation
Corresponding relationship between human visual contrast's degree resolution ratio and background luminance, determine corresponding target object desired display gray scale with
And background desired display gray scale；
According to the pixel grey scale mean value of the targeted object region and the pixel grey scale mean value of the background area, and
The target object desired display gray scale and the background desired display gray scale determine the target window width and mesh of display window setting
Mark window position；
According to the target window width and target window position, the display window setting of described image is adjusted.
Preferably, the target object starting point and background starting point in described image are obtained by median filter method
The target object source point and the background source point.
Preferably, by the target object source point, layer-by-layer iteration extension is obtained outward for the interested targeted object region
, by the background source point, layer-by-layer iteration extension is obtained outward for the background area.
It is highly preferred that the stop condition of the iteration extension includes at least:
The strength difference between pixel grey scale mean value in the gray value and current region of current pixel is more than one scheduled
Intensity threshold；
The distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold.
Preferably, the target window width WW_adapted and target window position WL_adapted is calculated really by following
It is fixed:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
M2=max ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
Gs1=min ([target object desired display gray scale background desired display gray scale])；
Gs2=max ([target object desired display gray scale background desired display gray scale])；
The maximum gradation value of Gs_max=display device.
Preferably, the target window width and target window position are applied to and other homotactic images of described image
Window setting, wherein described image belongs to one of the image sequence.
According to the second aspect of the invention, a kind of window setting device for image diagnostic system is provided, wherein should
Device includes:
First module, for determining target object source point and its background source point in image；
Second module, for determining interested mesh respectively according to the target object source point and the background source point
Mark subject area and corresponding background area；
Third module, for according to the pixel grey scale mean value of the targeted object region and the pixel of the background area
Gray average determines corresponding target object according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Desired display gray scale and background desired display gray scale；
4th module, for according to the pixel grey scale mean value of the targeted object region and the pixel of the background area
Gray average and the target object desired display gray scale and the background desired display gray scale determine that display window is arranged
Target window width and target window position；
5th module, for according to the target window width and target window position, the display window for adjusting described image to be set
It sets.
Preferably, first module is also used to:
The mesh is obtained by median filter method with background starting point to the target object starting point in described image
Mark object source point and the background source point.
Preferably, by the target object source point, layer-by-layer iteration extension is obtained outward for the interested targeted object region
, by the background source point, layer-by-layer iteration extension is obtained outward for the background area.
It is highly preferred that the stop condition of the iteration extension includes at least:
The strength difference between pixel grey scale mean value in the gray value and current region of current pixel is more than one scheduled
Intensity threshold；
The distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold.
Preferably, the target window width WW_adapted and target window position WL_adapted is calculated really by following
It is fixed:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
M2=max ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
Gs1=min ([target object desired display gray scale background desired display gray scale])；
Gs2=max ([target object desired display gray scale background desired display gray scale])；
The maximum gradation value of Gs_max=display device.
Preferably, the 5th module is also used to:
The target window width is applied to set with the window of other homotactic images of described image with target window position
It sets, wherein described image belongs to one of the image sequence.
Compared with prior art, the invention has the following advantages that
Window setting of the invention can be according to human visual system adjust automatically.Window width and window position by optimization,
So that being enhanced based on the picture contrast that gray scale is shown, the visibility for observing object is maximized.
The present invention window is arranged the adjust automatically according to human visual system, can farthest reduce image vision
Impression deviation maintains the consistency of image vision impression to a certain extent.The present invention not only makes have different personal warps
It tests or the different observers of preference is to same image can obtain consistent eye impressions, and be also possible that same observer
Consistent eye impressions are obtained in different moments to same image.Meanwhile the present invention can also reduce due to diagnostic device is different,
Image vision impression deviation caused by condition of scanning difference.
Further, compared with manually adjustment window setting, invention also saves time costs and cost of labor.
It further, can be of concern specific for observer according to the adjust automatically that window is arranged in human visual system
Region realizes that local optimum is shown, this is to mainly for the preset window set-up mode of global optimum being also at present a kind of beneficial
Supplement.
Further, for a series of image, when carrying out its window of adjust automatically according to the present invention to one of image
After setting, which may be utilized for other images of the series.
Detailed description of the invention
Below will detailed description of the present invention preferred embodiment by referring to accompanying drawing, make those skilled in the art more
Clear above and other feature and advantage of the invention, in attached drawing:
The schematic diagram of correlation curve of the Fig. 1 between mankind's visual contrast resolution ratio and background luminance；
The method flow diagram that the window for image diagnostic system of Fig. 2 embodiment according to the present invention is arranged；
Fig. 3 is the schematic device being arranged according to the window for image diagnostic system of one embodiment of the invention.
The same or similar appended drawing reference represents the same or similar component in attached drawing.
Specific embodiment
The preferred embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Preferred embodiment, however, it is to be appreciated that may be realized in various forms the disclosure without the embodiment party that should be illustrated here
Formula is limited.On the contrary, these embodiments are provided so that this disclosure will be more thorough and complete, and can be by the disclosure
Range is fully disclosed to those skilled in the art.
It is understood in advance that although the disclosure carries out citing description with the diagnostic imaging of CT system, the skill being described
The realization of art scheme is but not limited to use in CT system, but can be used for currently known or develop later any based on image
In the automatic window setting of diagnosis.
For image diagnostic system opinion, image is available to eye-observation, therefore observer is that final image connects
Receipts person.The key of image evaluation is that it should meet human visual system and display requires.Therefore, understand the characteristic of human eye
It is necessary.
To human vision studies have shown that human eye has different contrast resolution capabilities under Different background illumination.Example
Such as, if background luminance is slightly dark or slightly bright, the ability that human vision differentiates neighbor grayscale value is relatively weak.However, when in scene
Background under intermediate light, human vision is then more sensitive to the variation of grayscale information.
It is tested based on subjectivity, the non-linear relation between human visual contrast's degree resolution ratio and background luminance is studied next
The gray difference that effective district partial image is shown.The correlation curve of the two is as shown in Figure 1.
To make the object, technical solutions and advantages of the present invention clearer, by the following examples to of the invention further detailed
It describes in detail bright.
Fig. 2 is the method flow diagram being arranged according to the window for image diagnostic system of one embodiment of the invention.
Here, method of the invention can be implemented by image diagnostic system, it can also be by being installed on the diagnostic imaging system
One specific function device of system, if device is arranged in window, to implement.To be implemented below with window setting device convenient for illustrating
Method shown in Fig. 2 is illustrated.
As shown in Fig. 2, in step s 201, window setting device determines target object source point and its context sources in image
Point；In step S202, device is arranged according to the target object source point and the background source point in window, determines that sense is emerging respectively
The targeted object region and corresponding background area of interest；In step S203, device is arranged according to the target object in window
The pixel grey scale mean value in region and the pixel grey scale mean value of the background area, according to human visual contrast's degree resolution ratio and back
Corresponding relationship between scape brightness determines corresponding target object desired display gray scale and background desired display gray scale；In step
In rapid S204, device is arranged according to the pixel grey scale mean value of the targeted object region and the pixel of the background area in window
Gray average and the target object desired display gray scale and the background desired display gray scale determine that display window is arranged
Target window width and target window position；In step S205, device is arranged according to the target window width and target window position in window,
Adjust the display window setting of described image.
Specifically, in step s 201, window setting device determines target object source point and its background in observation image
Source point.
Here, target object source point is for example marked as seed_object, corresponding background source point is for example marked as
seed_background.The two can be determined at least through following manner:
1) the target object source point seed_ of the observation object in image is selected respectively by clicking mouse by observer
Object and background source point seed_background.
For example, observer can click mouse come a point of the target object for selecting its in image to wish to observe, window
Device is set using the point as object source point seed_object；Observer continues to click mouse to select the target pair in image
As a point of surrounding, device is arranged using the point as background source point seed_background in window.Accordingly, window setting dress
It sets and obtains target object source point and background source point respectively.
2) observer distinguishes selection target object starting point and background starting point in the picture first, and it is logical that device is arranged in window
Median filter method is crossed, target object source point and background source point in image are obtained.
In order to reject salt-pepper noise and by manual operation error control in a certain range, for user selection target
Object starting point and background starting point, window setting device can regain target object source point using median filter method
With background source point.
For example, the point that observer is selected in the picture is as target object starting point and background starting point, such as respectively by
Labeled as object and background.Then, a window having a size of N*N is applied to target object by window setting device
Starting point object, to be the point of intermediate value as target object source point seed_object by wherein gray value.Device is arranged in window
It is same that background source point seed_background is obtained by background starting point background using median filtering.
3) window setting device determines the target object in image by Object identifying, and from each picture of the target object
Selection target object source point in vegetarian refreshments selects background source point from the background pixel point near the target object.
For example, window be arranged device after identifying the target object in image, according to scheduled intensity value ranges from this
A target object source point seed_object is selected in each pixel of target object, and in the same way from the target
A background source point seed_background is selected in background pixel point near object.
Preferably, window setting device can be after identifying the target object in image, according to scheduled gray value model
One target object starting point object of selection from each pixel of the target object is enclosed, and in the same way from the mesh
It marks and selects a background starting point background in the background pixel point near object.Window setting device then uses intermediate value
Filtering method by the target object starting point object and background starting point background regains target object source
Point seed_object and background source point seed_background.
It will be appreciated by those skilled in the art that the determination mode of target object source point and background source point that the present invention is applicable in
Be not limited to it is above-mentioned enumerate, other existing or future methods of determination are such as determined for being suitable for the invention target pair
As source point and background source point, then should also be included within scope of patent protection of the invention.
In step S202, window is arranged device and determines that sense is emerging according to identified target object source point seed_object
The targeted object region of interest, such as it is marked as ROI_object, and according to identified background source point seed_
Background determines corresponding background area, such as is marked as ROI_background.
Here, window setting device can by various region growing algorithms (region-growing algorithm) come
Its area-of-interest is obtained to outer iteration extension by a source point.
For example, device is arranged by comparing itself and adjacent pixel in window using target object source point seed_object as starting point
Gray value, to the interest region ROI_object of outer iteration extension object, until meet preset stop condition.
Here, preset stop condition includes but is not limited to two following:
1) strength difference between the pixel grey scale mean value in the gray value and current region of current pixel is more than one predetermined
Intensity threshold；
For example, current region is by starting point of target object source point seed_object and obtained by growth iteration
Targeted object region, calculate current region in each pixel gray average, and using an adjacent pixel outside current region as
Current pixel compares the gray value and the gray average of current pixel: if the strength difference of the two is less than scheduled intensity
The current pixel point is then included in targeted object region by threshold value, and enters next round growth iteration；If the strength difference of the two
More than scheduled intensity threshold, then stop iteration, current region is final targeted object region ROI_object.
2) the distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold；
For example, current region is by starting point of target object source point seed_object and obtained by growth iteration
Targeted object region, using an adjacent pixel outside current region as current pixel, compare the target object source point pixel with
The distance between the current pixel: if the distance of the two is less than scheduled distance threshold, which is included in
Targeted object region, and enter next round growth iteration；If the distance of the two is more than scheduled distance threshold, stopping changes
Generation, current region are final targeted object region ROI_object.
It will be appreciated by those skilled in the art that although the above-mentioned application description to stop condition with target object source point and
Targeted object region is illustrated, but background source point and background area can also equally be applied to above-mentioned stop condition.
It should also be appreciated by one skilled in the art that the iteration stopping condition that is applicable in of the present invention be not limited to it is above-mentioned enumerate,
The stop condition of other influences iteration performance should be also included within scope of patent protection of the invention, other stop conditions are for example
Current display window width/window position, target object characteristic and clinical purpose etc. can be included in and be considered.
In step S203, device is arranged according to the pixel grey scale mean value of targeted object region and background area in window
Pixel grey scale mean value determines corresponding target according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Object desired display gray scale and background desired display gray scale.
The gray average that device calculates each pixel in the ROI_object of targeted object region is arranged in window, is such as labeled as
mean_object.The same manner calculates the gray average for obtaining each pixel in the ROI_background of background area, is such as labeled as
mean_background。
It is equal according to the gray average mean_object of targeted object region and the gray scale of background area that device is arranged in window
Value mean_background is determined corresponding according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Target object desired display gray scale and background desired display gray scale.Wherein, target object desired display gray scale is such as marked as
Grey_object, background desired display gray scale are such as marked as grey_background.
For example, window be arranged device by the intensity value ranges between target object and its background, i.e., [mean_object,
Mean_background], according to the nonlinear correlation between human visual contrast's degree resolution ratio shown in FIG. 1 and background luminance
Curve is mapped as capableing of the gray value strength range of effective district partial objectives for object and background, i.e. [grey_object, grey_
background]。
In step S204, device is arranged according to the pixel grey scale mean value of targeted object region and background area in window
Pixel grey scale mean value and target object desired display gray scale and background desired display gray scale, determine the mesh of display window setting
Mark window width and target window position.
Window setting device determines that the quasi- target window width being adjusted to of display window setting and target window position, the two are distinguished
Labeled as WW_adpated and WL_adpated.
Here, WW_adpated and WL_adpated can be determined based on following manner:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([mean_object mean_background])；
M2=max ([mean_object mean_background])；
Gs1=min ([grey_object grey_background])；
Gs2=max ([grey_object grey_background])；
The maximum gradation value of Gs_max=display device, such as 255.
The target window width and target window position that the image determined by above-mentioned method of determination is shown can be used as display observation figure
The best window width of picture and best window position, enable a user to observe by consistent image impression interested in the image
Targeted object region.
In step S205, device is arranged according to identified target window width and target window position, adjustment observation image in window
Display window setting.
Here, window setting device can be according to the target window width and target window position that above-mentioned calculating determines, adjustment observation figure
The display window of picture is arranged.
Accordingly, different observers can obtain consistent image impression to same image.Also, even for same observation
The adjust automatically of person, above-mentioned window setting can also make it obtain the coherent image impression to same image in different moments.
In addition, for the observation image of a sequence, if the mesh of automatic window setting has been determined based on one of image
Window width and target window position are marked, the automatic window that the target window width and target window position may be alternatively used for other images in the sequence is set
It sets.This for the image impression that observer is consistent for being advantageous.
Fig. 3 is the schematic device being arranged according to the window for image diagnostic system of one embodiment of the invention.
As shown in figure 3, window setting device 300 includes source point determining module 301, area determination module 302, grey scale mapping
Module 303, adjustment determining module 304 and setting adjustment module 305.
Wherein, source point determining module 301 is used to determine the target object source point and its background source point in image；Region determines
Module 302 is used to determine interested targeted object region respectively according to the target object source point and the background source point
And corresponding background area；Grey scale mapping module 303 is according to the pixel grey scale mean value of the targeted object region and described
The pixel grey scale mean value of background area is determined according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Corresponding target object desired display gray scale and background desired display gray scale；Determining module 304 is adjusted to be used for according to the mesh
It marks the pixel grey scale mean value of subject area and the pixel grey scale mean value of the background area and target object expectation is aobvious
Show gray scale and the background desired display gray scale, determines target window width and the target window position of display window setting；Setting adjustment mould
Block 305 is used to adjust the display window setting of described image according to the target window width and target window position.
Specifically, source point determining module 301 determines the target object source point and its background source point in observation image.
Here, target object source point is for example marked as seed_object, corresponding background source point is for example marked as
seed_background.The two can be determined at least through following manner:
1) the target object source point seed_ of the observation object in image is selected respectively by clicking mouse by observer
Object and background source point seed_background.
For example, observer can click mouse come a point of the target object for selecting its in image to wish to observe, window
Device is set using the point as object source point seed_object；Observer continues to click mouse to select the target pair in image
As a point of surrounding, source point determining module 301 is using the point as background source point seed_background.Accordingly, source point determines
Module 301 obtains target object source point and background source point respectively.
2) observer distinguishes selection target object starting point and background starting point, source point determining module in the picture first
301, by median filter method, obtain target object source point and background source point in image.
In order to reject salt-pepper noise and by manual operation error control in a certain range, for user selection target
Object starting point and background starting point, source point determining module 301 can regain target object using median filter method
Source point and background source point.
For example, the point that observer is selected in the picture is as target object starting point and background starting point, such as respectively by
Labeled as object and background.Then, a window having a size of N*N is applied to target by source point determining module 301
Object starting point object, to be the point of intermediate value as target object source point seed_object by wherein gray value.Source point determines
Module 301 is same to be filtered using median filter to obtain background source point seed_ by background starting point background
background。
3) source point determining module 301 determines the target object in image by Object identifying, and from the target object
Selecting object source point in each pixel selects background source point from the background pixel point near the target object.
For example, source point determining module 301 is after identifying the target object in image, according to scheduled intensity value ranges from
A target object source point seed_object is selected in each pixel of the target object, and in the same way from the mesh
It marks and selects a background source point seed_background in the background pixel point near object.
Preferably, source point determining module 301 can be after identifying the target object in image, according to scheduled gray value
Range selects a target object starting point object from each pixel of the target object, and in the same way from this
A background starting point background is selected in background pixel point near target object.Source point determining module 301 is then adopted
Target is regained by the target object starting point object and background starting point background with median filter method
Object source point seed_object and background source point seed_background.
It will be appreciated by those skilled in the art that the determination mode of target object source point and background source point that the present invention is applicable in
Be not limited to it is above-mentioned enumerate, other existing or future methods of determination are such as determined for being suitable for the invention target pair
As source point and background source point, then should also be included within scope of patent protection of the invention.
Area determination module 302 determines interested target pair according to identified target object source point seed_object
As region, such as it is marked as ROI_object, and is determined accordingly according to identified background source point seed_background
Background area, such as be marked as ROI_background.
Here, area determination module 302 can pass through various region growing algorithm (region-growing
Algorithm) one source point of cause obtains its interest region to outer iteration extension.
For example, using target object source point seed_object as starting point, area determination module 302 by comparing its with it is adjacent
The gray value of pixel, to the interest region ROI_object of outer iteration extension object, until meeting preset stop condition.
Here, preset stop condition includes but is not limited to two following:
1) strength difference between the pixel grey scale mean value in the gray value and current region of current pixel is more than one predetermined
Intensity threshold；
For example, current region is by starting point of target object source point seed_object and obtained by growth iteration
Targeted object region, area determination module 302 calculate the gray average of each pixel in current region, and by one outside current region
A adjacent pixel compares the gray value and the gray average of current pixel: if the strength difference of the two is not as current pixel
More than scheduled intensity threshold, then the current pixel point is included in targeted object region, and enters next round growth iteration；If
The strength difference of the two is more than scheduled intensity threshold, then stops iteration, current region is final targeted object region
ROI_object。
2) the distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold；
For example, current region is by starting point of target object source point seed_object and obtained by growth iteration
Targeted object region, area determination module 302 compare the target using an adjacent pixel outside current region as current pixel
The distance between object source point pixel and the current pixel:, should if being less than scheduled distance threshold at a distance from the two
Current pixel point is included in targeted object region, and enters next round growth iteration；If the distance of the two is more than scheduled distance
Threshold value, then stop iteration, and current region is final targeted object region ROI_object.
It will be appreciated by those skilled in the art that although the above-mentioned application description to stop condition with target object source point and
Targeted object region is illustrated, but background source point and background area can also equally be applied to above-mentioned stop condition.
It should also be appreciated by one skilled in the art that the iteration stopping condition that is applicable in of the present invention be not limited to it is above-mentioned enumerate,
The stop condition of other influences iteration performance should be also included within scope of patent protection of the invention, other stop conditions are for example
Current display window width/window position, target object characteristic and clinical purpose etc. can be included in and be considered.
Grey scale mapping module 303 is equal according to the pixel grey scale mean value of targeted object region and the pixel grey scale of background area
Value determines that corresponding target object expectation is aobvious according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Show gray scale and background desired display gray scale.
Grey scale mapping module 303 calculates the gray average of each pixel in the ROI_object of targeted object region, is such as labeled as
mean_object.The same manner calculates the gray average for obtaining each pixel in the ROI_background of background area, is such as labeled as
mean_background。
Grey scale mapping module 303 is according to the gray average mean_object of targeted object region and the ash of background area
Mean value mean_background is spent, according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance, determines phase
The target object desired display gray scale and background desired display gray scale answered.Wherein, target object desired display gray scale is such as marked
It is denoted as grey_object, background desired display gray scale is such as marked as grey_background.
For example, grey scale mapping module 303 is by the intensity value ranges between target object and its background, i.e. [mean_
Object, mean_background], according to non-thread between human visual contrast's degree resolution ratio shown in FIG. 1 and background luminance
Property correlation curve, is mapped as capableing of the gray value strength range of effective district partial objectives for object and background, i.e., [grey_object,
grey_background]。
It is equal according to the pixel grey scale mean value of targeted object region and the pixel grey scale of background area to adjust determining module 304
Value and target object desired display gray scale and background desired display gray scale, determine the target window width and mesh of display window setting
Mark window position.
Adjustment determining module 304 determines the quasi- target window width being adjusted to of display window setting and target window position, the two quilt
It is respectively labeled as WW_adpated and WL_adpated.
Here, WW_adpated and WL_adpated can be determined based on following manner:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([mean_object mean_background])；
M2=max ([mean_object mean_background])；
Gs1=min ([grey_object grey_background])；
Gs2=max ([grey_object grey_background])；
The maximum gradation value of Gs_max=display device, such as 255.
The target window width and target window position that the image determined by above-mentioned method of determination is shown can be used as display observation figure
The best window width of picture and best window position, enable a user to observe by consistent image impression interested in the image
Targeted object region.
Setting adjustment module 305 is according to identified target window width and target window position, the display window of adjustment observation image
Setting.
Here, setting adjustment module 305 can be according to the target window width and target window position that above-mentioned calculating determines, adjustment observation
The display window of image is arranged.
Accordingly, different observers can obtain consistent image impression to same image.Also, even for same observation
The adjust automatically of person, above-mentioned window setting can also make it obtain the coherent image impression to same image in different moments.
In addition, for the observation image of a sequence, if the mesh of automatic window setting has been determined based on one of image
Window width and target window position are marked, the automatic window that the target window width and target window position may be alternatively used for other images in the sequence is set
It sets.This for the image impression that observer is consistent for being advantageous.
It will be appreciated by those skilled in the art that each embodiment disclosed above, it can be without departing from invention essence
In the case of make various modifications and change.Therefore, protection scope of the present invention should be defined by the appended claims.
Claims (12)
1. a kind of window setting method for image diagnostic system, wherein this method comprises:
Determine the target object source point and its background source point in image；
According to the target object source point and the background source point, interested targeted object region and corresponding is determined respectively
Background area；
According to the pixel grey scale mean value of the targeted object region and the pixel grey scale mean value of the background area, according to the mankind
Corresponding relationship between visual contrast resolution ratio and background luminance determines corresponding target object desired display gray scale and back
Scape desired display gray scale；
According to the pixel grey scale mean value of the pixel grey scale mean value of the targeted object region and the background area and described
Target object desired display gray scale and the background desired display gray scale determine the target window width and target window of display window setting
Position；
According to the target window width and target window position, the display window setting of described image is adjusted.
2. according to the method described in claim 1, its further include:
Target object starting point and background starting point to described image obtain the target object by median filter method
Source point and the background source point.
3. according to the method described in claim 1, wherein, the interested targeted object region is by the target object source point
Successively iteration extension obtains outward, and by the background source point, layer-by-layer iteration extension is obtained outward for the background area.
4. according to the method described in claim 3, wherein, the stop condition of the iteration extension includes at least:
The strength difference between pixel grey scale mean value in the gray value and current region of current pixel is more than a scheduled intensity
Threshold value；
The distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold.
5. according to the method described in claim 1, wherein, the target window width WW_adapted and target window position WL_
Adapted is determined by following calculating:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
M2=max ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
Gs1=min ([target object desired display gray scale background desired display gray scale])；
Gs2=max ([target object desired display gray scale background desired display gray scale])；
The maximum gradation value of Gs_max=display device.
6. according to the method described in claim 1, its further include:
The target window width and target window position are applied to be arranged with the window of other homotactic images of described image,
In, described image belongs to one of the image sequence.
7. device is arranged in a kind of window for image diagnostic system, wherein the device includes:
First module, for determining target object source point and its background source point in image；
Second module, for determining interested target pair respectively according to the target object source point and the background source point
As region and corresponding background area；
Third module, for according to the pixel grey scale mean value of the targeted object region and the pixel grey scale of the background area
Mean value determines corresponding target object expectation according to the corresponding relationship between human visual contrast's degree resolution ratio and background luminance
Show gray scale and background desired display gray scale；
4th module, for according to the pixel grey scale mean value of the targeted object region and the pixel grey scale of the background area
Mean value and the target object desired display gray scale and the background desired display gray scale, determine the mesh of display window setting
Mark window width and target window position；
5th module, for adjusting the display window setting of described image according to the target window width and target window position.
8. device according to claim 7, first module is also used to:
The target pair is obtained by median filter method with background starting point to the target object starting point in described image
As source point and the background source point.
9. device according to claim 7, wherein the interested targeted object region is by the target object source point
Successively iteration extension obtains outward, and by the background source point, layer-by-layer iteration extension is obtained outward for the background area.
10. device according to claim 9, wherein the stop condition of the iteration extension includes at least:
The strength difference between pixel grey scale mean value in the gray value and current region of current pixel is more than a scheduled intensity
Threshold value；
The distance between corresponding source point pixel of current pixel is more than a scheduled distance threshold.
11. device according to claim 7, wherein the target window width WW_adapted and target window position WL_
Adapted is determined by following calculating:
WW_adapted=1/ (Gs2-Gs1) * (m2-m1) * Gs_max；
WL_adapted=1/ (Gs2-Gs1) * ((Gs_max/2-Gs1) * m2+ (Gs2-Gs_max/2) * m1)；
Wherein,
M1=min ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
M2=max ([the pixel grey scale mean value of the pixel grey scale mean value background area of targeted object region])；
Gs1=min ([target object desired display gray scale background desired display gray scale])；
Gs2=max ([target object desired display gray scale background desired display gray scale])；
The maximum gradation value of Gs_max=display device.
12. device according to claim 7, wherein the 5th module is also used to:
The target window width and target window position are applied to be arranged with the window of other homotactic images of described image,
In, described image belongs to one of the image sequence.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112053328A (en) * | 2020-08-18 | 2020-12-08 | 深圳蓝韵医学影像有限公司 | Method and system for processing digital X-ray pneumoconiosis image |
| CN112529818A (en) * | 2020-12-25 | 2021-03-19 | 万里云医疗信息科技（北京）有限公司 | Bone shadow inhibition method, device, equipment and storage medium based on neural network |
| CN113516328A (en) * | 2020-07-13 | 2021-10-19 | 阿里巴巴集团控股有限公司 | Data processing method, service providing method, device, equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105023273A (en) * | 2015-07-01 | 2015-11-04 | 张逸凡 | ROI (Region of Interest) window width and position adjusting method of medical image |
| CN105678750A (en) * | 2015-12-31 | 2016-06-15 | 上海联影医疗科技有限公司 | Gray scale mapping curve generation method and apparatus for medical images |
| CN105844597A (en) * | 2016-03-31 | 2016-08-10 | 深圳市菲森科技有限公司 | Image contrast control method and system |
-
2018
- 2018-01-02 CN CN201810001995.1A patent/CN109993159B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105023273A (en) * | 2015-07-01 | 2015-11-04 | 张逸凡 | ROI (Region of Interest) window width and position adjusting method of medical image |
| CN105678750A (en) * | 2015-12-31 | 2016-06-15 | 上海联影医疗科技有限公司 | Gray scale mapping curve generation method and apparatus for medical images |
| CN105844597A (en) * | 2016-03-31 | 2016-08-10 | 深圳市菲森科技有限公司 | Image contrast control method and system |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113516328A (en) * | 2020-07-13 | 2021-10-19 | 阿里巴巴集团控股有限公司 | Data processing method, service providing method, device, equipment and storage medium |
| CN112053328A (en) * | 2020-08-18 | 2020-12-08 | 深圳蓝韵医学影像有限公司 | Method and system for processing digital X-ray pneumoconiosis image |
| CN112529818A (en) * | 2020-12-25 | 2021-03-19 | 万里云医疗信息科技（北京）有限公司 | Bone shadow inhibition method, device, equipment and storage medium based on neural network |
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