CN109118501A - Image processing method and system - Google Patents
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- G16H30/00—ICT specially adapted for the handling or processing of medical images
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Abstract
The invention discloses a kind of image processing method and system, described image processing method includes: to obtain the first image data of the first image comprising process object；Processing is split to the first image according to the first image data, obtains the second image data of the process object in the first image；Obtain the second image of the process object corresponding with second image data；Automatically determine the image that correcting process is needed in second image.In the present invention, after being split processing and three-dimensional reconstruction by the image to process object, the two dimensional image for needing to be modified in image after judging automatically out dividing processing, and the image for needing correcting process filtered out is modified, the workload for efficiently reducing user, improves work efficiency；Meanwhile obtaining the 3-D image of process object again in conjunction with correction result, improve the precision and accuracy rate of processing result image.
Description
Technical field
The present invention relates to product image processing technology field, in particular to a kind of image processing method and system.
Background technique
With the continuous development of the technologies such as image processing techniques, visual computer technology, machine learning, calculates auxiliary and examine
Treatment brings great convenience for doctor, as biggish mention has been obtained in terms of medical image segmentation and three-dimensional reconstruction effect
It rises.But while there is also some shortcomings.On the one hand, there is certain limitation since computer automatically processes algorithm itself
Property, it is not able to satisfy the demand of all possibilities, meanwhile, according to machine learning techniques, algorithm itself has self-learning function, but
The result of study depends on the data for training, so that computer is automatically processed, there are certain limitations；On the other hand,
For the data of same process object, such as CT data (electronic computer break tomographic data), there may be not by different doctors
Same opinion.Therefore, when carrying out medical diagnosis using area of computer aided, after completing medical image segmentation and three-dimensional reconstruction, doctor
It is raw still to carry out confirmation and modified demand.
But since the medical image quantity after rebuilding is more, for hip joint and knee joint reconstructing three-dimensional model
CT data instance, sequence may up to 400 images, every image is successively checked and is corrected, is brought to doctor huge
Workload also reduces working efficiency.
Summary of the invention
The technical problem to be solved by the present invention is to after medical image segmentation in the prior art and three-dimensional reconstruction, there are medicine figures
Picture quantity is more, and every image is successively checked and corrected, brings huge workload to doctor, reduces working efficiency etc. and lacks
It falls into, and it is an object of the present invention to provide a kind of image processing method and system.
The present invention is to solve above-mentioned technical problem by following technical proposals:
The present invention provides a kind of image processing method, and described image processing method includes:
S1, the first image data for obtaining the first image comprising process object；
S2, processing is split to the first image according to the first image data, obtained in the first image
The process object the second image data；
S3, the second image for obtaining the process object corresponding with second image data；
S4, the image that correcting process is needed in second image is automatically determined.
Preferably, second image data includes the first two-dimensional image data, second image includes the first two dimension
Image；And/or
Second image data includes the first 3 d image data, and second image includes the first 3-D image；
Wherein, first two dimensional image includes at least one in cross sectional image, coronal image and sagittal view picture
Kind.
Preferably, working as, second image includes first two dimensional image and first two dimensional image includes the cross
When cross-sectional image, step S4 is specifically included:
According to the cross sectional image, the first contour line of process object described in the cross sectional image is obtained automatically,
And obtain the second contour line of process object described in the first image；
The first contour line be aligned comparing with second contour line, judge the first contour line with it is described
Whether the second contour line is overlapped, if not, it is determined that second image is the image for needing correcting process.
Preferably, step S4 is specifically included when second image includes first two dimensional image:
Automatically the probability that first two dimensional image needs correcting process is calculated；
Determine that the probability is greater than image of first two dimensional image for setting probability threshold value to need correcting process.
Preferably, step S4 is specifically included when second image includes first 3-D image:
Obtain the abnormal point in first 3-D image；
Obtain first two dimensional image corresponding with abnormal point described in first 3-D image；
Determine that first two dimensional image is the image for needing correcting process.
Preferably, after step S4 further include:
S5, to needing the image of correcting process to be modified processing in second image, after obtaining correcting process the
Two two dimensional images；
S6, according to after correcting process the corresponding image data of second two dimensional image and second image in be not required to
The first image data for wanting the image of correcting process obtain the second 3-D image of the process object.
Preferably, step S5 includes:
Second image is compared with corresponding the first image, obtains and needs to correct in second image
Correcting region；
The contour line in the correcting region is deleted, and repaints the corresponding contour line of the correcting region, until institute
The contour line stated in correcting region is overlapped with contour line corresponding in the first image, obtains obtaining second after correcting process
Two dimensional image；Or,
The profile curvature of a curve in the correcting region is adjusted, until the contour line and described first in the correcting region
Corresponding contour line is overlapped in image, obtains obtaining the second two dimensional image after correcting process.
Preferably, the process object includes bone.
The present invention also provides a kind of image processing system, described image processing system includes the first image data acquisition mould
Block, the second image data acquisition module, image collection module and automatically determine module；
The first image data acquisition module is used to obtain the first image data of the first image comprising process object；
The second image data acquisition module is for dividing the first image according to the first image data
Processing is cut, the second image data of the process object in the first image is obtained；
Described image obtains the second figure that module is used to obtain the process object corresponding with second image data
Picture；
The module that automatically determines is for automatically determining the image for needing correcting process in second image.
Preferably, second image data includes the first two-dimensional image data, second image includes the first two dimension
Image；And/or
Second image data includes the first 3 d image data, and second image includes the first 3-D image；
Wherein, first two dimensional image includes at least one in cross sectional image, coronal image and sagittal view picture
Kind.
Preferably, the module that automatically determines includes contour line acquiring unit, judging unit and the first determination unit；
When second image includes first two dimensional image and first two dimensional image includes the cross-sectional view
When picture, the contour line acquiring unit is used to be obtained automatically described in the cross sectional image according to the cross sectional image
The first contour line of object is managed, and obtains the second contour line of process object described in the first image；
The judging unit with second contour line for be aligned comparing the first contour line, described in judgement
Whether first contour line is overlapped with second contour line, if it is not, then calling the determination unit；
First determination unit is for determining that second image is the image for needing correcting process.
Preferably, the module that automatically determines includes probability calculation unit and the second determination unit；
When second image includes first two dimensional image, the probability calculation unit is for described in calculating automatically
First two dimensional image needs the probability of correcting process；
Second determination unit be used to determine the probability be greater than set first two dimensional image of probability threshold value as
Need the image of correcting process.
Preferably, the module that automatically determines includes abnormal point acquiring unit, image acquisition unit and third determination unit；
When second image includes first 3-D image, the abnormal point acquiring unit is for obtaining described the
Abnormal point in one 3-D image；
Described image acquiring unit is for obtaining corresponding with abnormal point described in first 3-D image described first
Two dimensional image；
The third determination unit is for determining that first two dimensional image is the image for needing correcting process.
Preferably, described image processing system includes correction module and acquiring three-dimensional images module；
The correction module is used for needing the image of correcting process to be modified processing in second image, and acquisition is repaired
Just treated the second two dimensional image；
The acquiring three-dimensional images module is used for according to the corresponding picture number of second two dimensional image after correcting process
According to the first image data with second image for not needing correcting process in image, the of the process object is obtained
Two 3-D images.
Preferably, the correction module includes correcting region acquiring unit and amending unit；
The correcting region acquiring unit is obtained for comparing second image with corresponding the first image
It takes in second image and needs modified correcting region；
The amending unit is used to delete the contour line in the correcting region, and it is corresponding to repaint the correcting region
Contour line, until the correcting region in contour line be overlapped with contour line corresponding in the first image, obtained
The second two dimensional image after correcting process；Or,
The amending unit is used to adjust the profile curvature of a curve in the correcting region, until in the correcting region
Contour line is overlapped with contour line corresponding in the first image, obtains obtaining the second two dimensional image after correcting process.
Preferably, the process object includes bone.
The positive effect of the present invention is that:
In the present invention, after being split processing and three-dimensional reconstruction by the image to process object, judges automatically out and divide
It needs to be modified the two dimensional image of processing in treated image, and the image for needing correcting process filtered out is repaired
Just, the workload for efficiently reducing user, improves work efficiency；Meanwhile obtaining process object again in conjunction with correction result
3-D image improves the precision and accuracy rate of processing result image.
Detailed description of the invention
Fig. 1 is the flow chart of the image processing method of the embodiment of the present invention 1.
Fig. 2 is the image segmentation result schematic diagram of the image processing method of the embodiment of the present invention 1.
Fig. 3 is the flow chart of the image processing method of the embodiment of the present invention 2.
Fig. 4 is the flow chart of the image processing method of the embodiment of the present invention 3.
Fig. 5 is the flow chart of the image processing method of the embodiment of the present invention 4.
Fig. 6 is the flow chart of the image processing method of the embodiment of the present invention 5.
Fig. 7 is the flow chart of the image processing method of the embodiment of the present invention 6.
Fig. 8 is the module diagram of the image processing system of the embodiment of the present invention 7.
Fig. 9 is the module diagram of the image processing system of the embodiment of the present invention 8.
Figure 10 is the module diagram of the image processing system of the embodiment of the present invention 9.
Figure 11 is the module diagram of the image processing system of the embodiment of the present invention 10.
Figure 12 is the module diagram of the image processing system of the embodiment of the present invention 11.
Figure 13 is the module diagram of the image processing system of the embodiment of the present invention 12.
Specific embodiment
The present invention is further illustrated below by the mode of embodiment, but does not therefore limit the present invention to the reality
It applies among a range.
Embodiment 1
As shown in Figure 1, the image processing method of the present embodiment includes:
S101, the first image data for obtaining the first image comprising process object；
Wherein, process object includes bone, but is not limited to bone, can also include other kinds of process object.
First image is the CT scan image of skeletal sites, is indicated in the form of a sequence, picture format DICOM
(Digital Imaging and Communications in Medicine, digital imaging and communications in medicine).DICOM is doctor
The international standard (ISO 12052) for learning image and relevant information defines the data exchange that can be used for for being able to satisfy clinical needs
Medical Image Format analyzes the numerical value for obtaining characterization tissue according to dicom standard.
Specifically, CT scan is using accurate X-ray beam, gamma-rays, ultrasonic wave etc., together with the detector high with sensitivity
Make profile scanning one by one around a certain position of human body.One sequence refers to multiple comprising all information of disease sites
The set of tomoscan image.Further, a sequence refers to all CT scan picture numbers comprising target body tissue site
According to one of DICOM file set.
S102, processing is split to the first image according to the first image data, obtains the process object in the first image
The second image data；
Specifically, FCN (Full Convolutional Network, full convolutional Neural are used according to the first image data
Network) algorithm carries out coarse segmentation processing to the first image, Level Set is then used according to coarse segmentation treated image data
Method (Level Set Method) carries out precision processing processing, obtains the second image data of the process object in the first image.
S103, the second image for obtaining process object corresponding with the second image data；
Wherein, by set display parameters, the process object region in the second image that dividing processing is obtained with
A kind of color is shown that the region except process object in the first image is shown with another color (such as Fig. 2 institute
Show, the region a indicates bony areas, and the region b indicates other regions in CT scan image other than bony areas), it is partitioned into
Deal with objects corresponding image.
Wherein, the second image data includes the first two-dimensional image data, and the second image includes the first two dimensional image；And/or
Second image data includes the first 3 d image data, and the second image includes the first 3-D image；
Wherein, at using Marching Cubes algorithm (a kind of iso-surface patch algorithm) to the first two-dimensional image data
Reason obtains the first 3 d image data；The first 3-D image of process object is obtained further according to the first 3 d image data.
Specifically, include: using the specific steps that Marching Cubes algorithm finally obtains the first 3-D image
1) the first two-dimensional image data is read in into three-dimensional array；
2) volume elements is extracted from three-dimensional array, becomes current voxel, while obtaining all information of the volume elements, such as 8
The value on a vertex, coordinate etc.；
3) value on 8 vertex of current voxel is compared with the value of given contour surface, obtains the state of the volume elements；
4) according to the state index of current voxel, the volume elements seamed edge intersected with contour surface is found out, and using linear interpolation
Method calculates the position coordinates of each intersection point；
5) calculate the plane by each seamed edge intersection point in the volume elements, using the plane normal orientation, each seamed edge intersection point as
Vertex, the first 3 d image data；
6) the first 3-D image dealt with objects according to the first 3 d image data Isosurface construction.
In addition, the first two dimensional image includes at least one of cross sectional image, coronal image and sagittal view picture.?
The contour line for sketching the contours of segmentation result edge in cross sectional image with lines, checks convenient for user and confirms segmentation result.
General user's multi-angle for convenience checks process object, shows the cross of process object simultaneously in software interactive interface
Cross-sectional image, coronal image, sagittal view picture and the first 3-D image four open image, each image position root when display
It is replaced according to actual demand.
S104, the image that correcting process is needed in the second image is automatically determined.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, efficiently reduces the workload of user, improves work efficiency.
Embodiment 2
As shown in figure 3, the image processing method of the present embodiment is the further improvement to embodiment 1, specifically:
When the second image includes the first two dimensional image and the first two dimensional image includes cross sectional image, step S104 is specific
Include:
S1041, according to cross sectional image, it is automatic to obtain the first contour line dealt with objects in cross sectional image, and obtain
The second contour line dealt with objects in first image；
S1042, first contour line be aligned comparing with the second contour line, judge first contour line and the second contour line
Whether it is completely coincident, if not, it is determined that the second image is the image for needing correcting process.
In the present embodiment, processing is split by the image to process object, the cross-sectional view after obtaining dividing processing
As in the first contour line that deals with objects and with the second contour line for being dealt with objects in the first image, judge first contour line and the
Whether two contour lines are completely coincident to determine whether the second image is the image for needing correcting process, to efficiently reduce user
Workload, improve work efficiency.
Embodiment 3
As shown in figure 4, the image processing method of the present embodiment is the further improvement to embodiment 1, specifically:
When the second image includes the first two dimensional image, step S104 is specifically included:
S1043, the automatic probability for calculating the first two dimensional image and needing correcting process；
Specifically, the method for probability is calculated are as follows: calculate two figures adjacent with the sequence number of current first two dimensional image
The differential index (di) of the segmentation result of picture, the probability for needing correcting process of the size of the differential index (di) and current first two dimensional image
It is positively correlated.
S1044, determine that probability is greater than image of the first two dimensional image for setting probability threshold value to need correcting process.
In the present embodiment, processing is split by the image to process object, every second after obtaining dividing processing
Image needs the probability of correcting process, picks out probability and is greater than the second image of setting probability threshold value as needing correcting process
Image improves work efficiency to efficiently reduce the workload of user.
Embodiment 4
As shown in figure 5, the image processing method of the present embodiment is the further improvement to embodiment 1, specifically:
When the second image includes the first 3-D image, step S104 is specifically included:
Abnormal point in S1045, the first 3-D image of acquisition；
Wherein, abnormal point, which refers to, obviously is not belonging to deal with objects the corresponding point in region of itself.
S1046, the first two dimensional image corresponding with abnormal point in the first 3-D image is obtained；
Specifically, it according to the mapping relations of the coordinate system of displaing coordinate system and threedimensional model where process object, will show
Show that the target abnormal point of interactive process selection in coordinate system is converted to the space coordinate point on threedimensional model coordinate system；
According to the mapping relations between threedimensional model coordinate system and two-dimensional image sequence, by the space on threedimensional model coordinate system
Coordinate points are scaled the point in the second image of two-dimensional image sequence, and obtain the sequence number of corresponding second image.In addition,
Since the sequence number of two-dimensional image sequence is discrete integer value, the sequence number to convert may be not present in really
Two-dimensional image sequence in, at this point, two two dimensional images nearest from the point when rebuilding threedimensional model are as needing Corrections Division
The image of reason.
S1047, determine that the first two dimensional image is the image for needing correcting process.
In the present embodiment, processing is split by the image to process object, obtains and deals with objects corresponding three-dimensional figure
Abnormal point as in obtains the first two dimensional image corresponding with abnormal point in the first 3-D image, determines that the first two dimensional image is
The image of correcting process is needed, to efficiently reduce the workload of user, is improved work efficiency.
Embodiment 5
As shown in fig. 6, the image processing method of the present embodiment is the further improvement to embodiment 1, specifically:
After step S104 further include:
S105, the image that correcting process is needed in the second image is modified to processing, second after obtaining correcting process
Two dimensional image；
S106, according to after correcting process the corresponding image data of the second two dimensional image and the second image in do not need to correct
First image data of the image of processing obtains the second 3-D image of process object.
Finally, display is to process object (such as bone) corresponding two dimensional image segmentation result (cross sectional image, coronal-plane figure
Picture and sagittal view picture) and 3-D image, until user thinks that all confirmation and amendment work are completed.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, and the image for needing correcting process filtered out is modified, to efficiently reduce use
The workload at family, improves work efficiency；Meanwhile obtaining the 3-D image of process object again in conjunction with correction result, it improves
The precision and accuracy rate of processing result image.
Embodiment 6
As shown in fig. 7, the image processing method of the present embodiment is the further improvement to embodiment 5, specifically:
Step S105 includes:
S1051, the second image is compared with corresponding first image, obtains in the second image and needs modified amendment
Region；
Specifically, left mouse button dragging is pinned, is unclamped after reaching target position, it is left with left mouse button depressed position, mouse
Key released position is in cornerwise rectangular area (i.e. correcting region), and the contour line for being included is the profile for choosing part.
Left mouse button dragging is pinned, makes to drag track formation closed curve, the contour line that encapsulation curvilinear inner is included is i.e.
For the profile for choosing part；If not formed encapsulation curve when dragging, that is, presses the coordinate of left mouse button and unclamp left mouse button
Position is inconsistent, continuous with straight line, is closed curve.
Contour line in S1052, deletion correcting region, and the corresponding contour line of correcting region is repainted, until amendment
Contour line in region is completely coincident with corresponding contour line in the first image, obtains obtaining the second X-Y scheme after correcting process
Picture；
Specifically, the mode of the corresponding contour line of correcting region is repainted are as follows: pin left mouse button dragging, mouse is mobile
Track is new contour line, unclamps left mouse button after the completion.
Or, adjustment correcting region in profile curvature of a curve, until correcting region in contour line with it is right in the first image
The contour line answered is completely coincident, and obtains obtaining the second two dimensional image after correcting process.
It chooses and needs to need modified correcting region in the second image of correcting process, left mouse button is moved to the amendment area
Position point, presses left mouse button and does not unclamp among profile in domain, mobile mouse position, release when meeting the requirements.It moves
When dynamic, new curve is to choose profile two o'clock as curve starting point and terminal, while mouse point is the secondary of third point
Spline curve；
Desired curvature of curve is inputted after choosing, computer is automatically generated to choose profile two o'clock as curve starting point and end
Point, while using input value as the curve of curvature, choose partial contour line to delete as new contour line, and by original.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, and the image for needing correcting process filtered out is modified, to efficiently reduce use
The workload at family, improves work efficiency；Meanwhile obtaining the 3-D image of process object again in conjunction with correction result, it improves
The precision and accuracy rate of processing result image.
Embodiment 7
As shown in figure 8, the image processing system of the present embodiment includes the first image data acquisition module 1, the second picture number
According to acquisition module 2, image collection module 3 and automatically determine module 4.
First image data acquisition module 1 is used to obtain the first image data of the first image comprising process object；
Wherein, process object includes bone, but is not limited to bone, can also include other kinds of process object.
First image is the CT scan image of skeletal sites, is indicated in the form of a sequence, picture format DICOM
(Digital Imaging and Communications in Medicine, digital imaging and communications in medicine).DICOM is doctor
The international standard (ISO 12052) for learning image and relevant information defines the data exchange that can be used for for being able to satisfy clinical needs
Medical Image Format analyzes the numerical value for obtaining characterization tissue according to dicom standard.
Specifically, CT scan is using accurate X-ray beam, gamma-rays, ultrasonic wave etc., together with the detector high with sensitivity
Make profile scanning one by one around a certain position of human body.One sequence refers to multiple comprising all information of disease sites
The set of tomoscan image.Further, a sequence refers to all CT scan picture numbers comprising target body tissue site
According to one of DICOM file set.
Second image data acquisition module 2 is used to be split processing to the first image according to the first image data, obtains
Second image data of the process object in the first image；
Specifically, FCN (Full Convolutional Network, full convolutional Neural are used according to the first image data
Network) algorithm carries out coarse segmentation processing to the first image, Level Set is then used according to coarse segmentation treated image data
Method (Level Set Method) carries out precision processing processing, obtains the second image data of the process object in the first image.
Image collection module 3 is used to obtain the second image of process object corresponding with the second image data；
Wherein, by set display parameters, the process object region in the second image that dividing processing is obtained with
A kind of color is shown that the region except process object in the first image is shown with another color (such as Fig. 2 institute
Show, the region a indicates bony areas, and the region b indicates other regions in CT scan image other than bony areas), it is partitioned into
Deal with objects corresponding image.Wherein, the second image data includes the first two-dimensional image data, and the second image includes the first two dimension
Image；And/or
Second image data includes the first 3 d image data, and the second image includes the first 3-D image；
Wherein, at using Marching Cubes algorithm (a kind of iso-surface patch algorithm) to the first two-dimensional image data
Reason obtains the first 3 d image data；The first 3-D image of process object is obtained further according to the first 3 d image data.
Specifically, include: using the specific steps that Marching Cubes algorithm finally obtains the first 3-D image
1) the first two-dimensional image data is read in into three-dimensional array；
2) volume elements is extracted from three-dimensional array, becomes current voxel, while obtaining all information of the volume elements, such as 8
The value on a vertex, coordinate etc.；
3) value on 8 vertex of current voxel is compared with the value of given contour surface, obtains the state of the volume elements；
4) according to the state index of current voxel, the volume elements seamed edge intersected with contour surface is found out, and using linear interpolation
Method calculates the position coordinates of each intersection point；
5) calculate the plane by each seamed edge intersection point in the volume elements, using the plane normal orientation, each seamed edge intersection point as
Vertex, the first 3 d image data；
6) the first 3-D image dealt with objects according to the first 3 d image data Isosurface construction.
In addition, the first two dimensional image includes at least one of cross sectional image, coronal image and sagittal view picture.?
The contour line for sketching the contours of segmentation result edge in cross sectional image with lines, checks convenient for user and confirms segmentation result.
General user's multi-angle for convenience checks process object, shows the cross of process object simultaneously in software interactive interface
Cross-sectional image, coronal image, sagittal view picture and the first 3-D image four open image, each image position root when display
It is replaced according to actual demand.Module 4 is automatically determined for automatically determining the image for needing correcting process in the second image.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, efficiently reduces the workload of user, improves work efficiency.
Embodiment 8
As shown in figure 9, the image processing system of the present embodiment is the further improvement to embodiment 7, specifically:
Automatically determining module 4 includes contour line acquiring unit 41, judging unit 42 and the first determination unit 43.
When the second image includes the first two dimensional image and the first two dimensional image includes cross sectional image, contour line obtains single
Member 41 obtains the first figure for obtaining the first contour line dealt with objects in cross sectional image automatically according to cross sectional image
The second contour line dealt with objects as in；
Judging unit 42 judges first contour line and for be aligned comparing first contour line with the second contour line
Whether two contour lines are completely coincident, if it is not, then calling determination unit；
First determination unit 43 is for determining that the second image is the image for needing correcting process.
In the present embodiment, processing is split by the image to process object, the cross-sectional view after obtaining dividing processing
As in the first contour line that deals with objects and with the second contour line for being dealt with objects in the first image, judge first contour line and the
Whether two contour lines are completely coincident to determine whether the second image is the image for needing correcting process, to efficiently reduce user
Workload, improve work efficiency.
Embodiment 9
As shown in Figure 10, the image processing system of the present embodiment is the further improvement to embodiment 7, specifically:
Automatically determining module 4 includes probability calculation unit 44 and the second determination unit 45.
When the second image includes the first two dimensional image, probability calculation unit 44 is needed for calculating the first two dimensional image automatically
Want the probability of correcting process；
Specifically, the difference of the segmentation result of two image adjacent with the sequence number of current first two dimensional image is calculated
Index, the size of the differential index (di) and the probability for needing correcting process of current first two dimensional image are positively correlated.Second determines
Unit 45 is used to determine that probability to be greater than image of the first two dimensional image for setting probability threshold value to need correcting process.
In the present embodiment, processing is split by the image to process object, every second after obtaining dividing processing
Image needs the probability of correcting process, picks out probability and is greater than the second image of setting probability threshold value as needing correcting process
Image improves work efficiency to efficiently reduce the workload of user.
Embodiment 10
As shown in figure 11, the image processing system of the present embodiment is the further improvement to embodiment 7, specifically:
Automatically determining module 4 includes abnormal point acquiring unit 46, image acquisition unit 47 and third determination unit 48.
When the second image includes the first 3-D image, abnormal point acquiring unit 46 is for obtaining in the first 3-D image
Abnormal point；
Wherein, abnormal point, which refers to, obviously is not belonging to deal with objects the corresponding point in region of itself.Image acquisition unit 47 is used
In acquisition the first two dimensional image corresponding with abnormal point in the first 3-D image；
Specifically, it according to the mapping relations of the coordinate system of displaing coordinate system and threedimensional model where process object, will show
Show that the target abnormal point of interactive process selection in coordinate system is converted to the space coordinate point on threedimensional model coordinate system；
According to the mapping relations between threedimensional model coordinate system and two-dimensional image sequence, by the space on threedimensional model coordinate system
Coordinate points are scaled the point in the second image of two-dimensional image sequence, and obtain the sequence number of corresponding second image.In addition,
Since the sequence number of two-dimensional image sequence is discrete integer value, the sequence number to convert may be not present in really
Two-dimensional image sequence in, at this point, two two dimensional images nearest from the point when rebuilding threedimensional model are as needing Corrections Division
The image of reason.
Third determination unit 48 is for determining that the first two dimensional image is the image for needing correcting process.
In the present embodiment, processing is split by the image to process object, obtains and deals with objects corresponding three-dimensional figure
Abnormal point as in obtains the first two dimensional image corresponding with abnormal point in the first 3-D image, determines that the first two dimensional image is
The image of correcting process is needed, to efficiently reduce the workload of user, is improved work efficiency.
Embodiment 11
As shown in figure 12, the image processing system of the present embodiment is the further improvement to embodiment 7, specifically:
Image processing system includes correction module 5 and acquiring three-dimensional images module 6.
Correction module 5 is used to for the image for needing correcting process in the second image to be modified processing, obtains correcting process
The second two dimensional image afterwards；
Acquiring three-dimensional images module 6 is used for according to the corresponding image data of the second two dimensional image and second after correcting process
The first image data that the image of correcting process is not needed in image obtains the second 3-D image of process object.
Finally, display is to process object (such as bone) corresponding two dimensional image segmentation result (cross sectional image, coronal-plane figure
Picture and sagittal view picture) and 3-D image, until user thinks that all confirmation and amendment work are completed.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, and the image for needing correcting process filtered out is modified, to efficiently reduce use
The workload at family, improves work efficiency；Meanwhile obtaining the 3-D image of process object again in conjunction with correction result, it improves
The precision and accuracy rate of processing result image.
Embodiment 12
As shown in figure 13, the image processing system of the present embodiment is the further improvement to embodiment 11, specifically:
Correction module 5 includes correcting region acquiring unit 51 and amending unit 52.
Correcting region acquiring unit 51 obtains the second image for comparing the second image with corresponding first image
It is middle to need modified correcting region；
Specifically, left mouse button dragging is pinned, is unclamped after reaching target position, it is left with left mouse button depressed position, mouse
Key released position is in cornerwise rectangular area (as correcting region), and the contour line for being included is the wheel for choosing part
It is wide.
Left mouse button dragging is pinned, makes to drag track formation closed curve, the contour line that encapsulation curvilinear inner is included is i.e.
For the profile for choosing part；If not formed encapsulation curve when dragging, that is, presses the coordinate of left mouse button and unclamp left mouse button
Position is inconsistent, continuous with straight line, is closed curve.
Amending unit 52 is used to delete the contour line in correcting region, and repaints the corresponding contour line of correcting region,
Until the contour line in correcting region is completely coincident with corresponding contour line in the first image, the after obtaining acquisition correcting process
Two two dimensional images；
Specifically, the mode of the corresponding contour line of correcting region is repainted are as follows: pin left mouse button dragging, mouse is mobile
Track is new contour line, unclamps left mouse button after the completion.
Or, amending unit 52 is used to adjust the profile curvature of a curve in correcting region, until the contour line in correcting region
It is completely coincident with contour line corresponding in the first image, obtains obtaining the second two dimensional image after correcting process.
It chooses and needs to need modified correcting region in the second image of correcting process, left mouse button is moved to the amendment area
Position point, presses left mouse button and does not unclamp among profile in domain, mobile mouse position, release when meeting the requirements.It moves
When dynamic, new curve is to choose profile two o'clock as curve starting point and terminal, while mouse point is the secondary of third point
Spline curve；
Desired curvature of curve is inputted after choosing, computer is automatically generated to choose profile two o'clock as curve starting point and end
Point, while using input value as the curve of curvature, choose partial contour line to delete as new contour line, and by original.
In the present embodiment, processing is split by the image to process object, the image after automatically determining dividing processing
The middle image for needing to be modified, and the image for needing correcting process filtered out is modified, to efficiently reduce use
The workload at family, improves work efficiency；Meanwhile obtaining the 3-D image of process object again in conjunction with correction result, it improves
The precision and accuracy rate of processing result image.
Although specific embodiments of the present invention have been described above, it will be appreciated by those of skill in the art that these
It is merely illustrative of, protection scope of the present invention is defined by the appended claims.Those skilled in the art is not carrying on the back
Under the premise of from the principle and substance of the present invention, various changes or modifications can be made to these embodiments, but these are changed
Protection scope of the present invention is each fallen with modification.
Claims (16)
1. a kind of image processing method, which is characterized in that described image processing method includes:
S1, the first image data for obtaining the first image comprising process object；
S2, processing is split to the first image according to the first image data, obtains the institute in the first image
State the second image data of process object；
S3, the second image for obtaining the process object corresponding with second image data；
S4, the image that correcting process is needed in second image is automatically determined.
2. image processing method as described in claim 1, which is characterized in that second image data includes the first X-Y scheme
As data, second image includes the first two dimensional image；And/or
Second image data includes the first 3 d image data, and second image includes the first 3-D image；
Wherein, first two dimensional image includes at least one of cross sectional image, coronal image and sagittal view picture.
3. image processing method as claimed in claim 2, which is characterized in that when second image includes first two dimension
Image and when first two dimensional image includes the cross sectional image, step S4 is specifically included:
According to the cross sectional image, the first contour line of process object described in the cross sectional image is obtained automatically, and is obtained
Take the second contour line of process object described in the first image；
The first contour line be aligned comparing with second contour line, judges the first contour line and described second
Whether contour line is overlapped, if not, it is determined that second image is the image for needing correcting process.
4. image processing method as claimed in claim 2, which is characterized in that when second image includes first two dimension
When image, step S4 is specifically included:
Automatically the probability that first two dimensional image needs correcting process is calculated；
Determine that the probability is greater than image of first two dimensional image for setting probability threshold value to need correcting process.
5. image processing method as claimed in claim 2, which is characterized in that when second image includes described first three-dimensional
When image, step S4 is specifically included:
Obtain the abnormal point in first 3-D image；
Obtain first two dimensional image corresponding with abnormal point described in first 3-D image；
Determine that first two dimensional image is the image for needing correcting process.
6. image processing method as described in claim 1, which is characterized in that after step S4 further include:
S5, to needing the image of correcting process to be modified processing in second image, the two or two after obtaining correcting process
Tie up image；
S6, according to after correcting process the corresponding image data of second two dimensional image and second image in do not need to repair
The first image data of the image just handled obtain the second 3-D image of the process object.
7. image processing method as claimed in claim 6, which is characterized in that step S5 includes:
Second image is compared with corresponding the first image, obtains in second image and needs modified repair
Positive region；
The contour line in the correcting region is deleted, and repaints the corresponding contour line of the correcting region, until described repair
Contour line in positive region is overlapped with contour line corresponding in the first image, obtains obtaining the second two dimension after correcting process
Image；Or,
The profile curvature of a curve in the correcting region is adjusted, until contour line and the first image in the correcting region
In corresponding contour line be overlapped, obtain obtaining the second two dimensional image after correcting process.
8. the image processing method as described in any one of claims 1 to 7, which is characterized in that the process object includes bone
Bone.
9. a kind of image processing system, which is characterized in that described image processing system includes the first image data acquisition module, the
Two image data acquisition modules, image collection module and automatically determine module；
The first image data acquisition module is used to obtain the first image data of the first image comprising process object；
The second image data acquisition module is used to be split place to the first image according to the first image data
Reason obtains the second image data of the process object in the first image；
Described image obtains the second image that module is used to obtain the process object corresponding with second image data；
The module that automatically determines is for automatically determining the image for needing correcting process in second image.
10. image processing system as claimed in claim 9, which is characterized in that second image data includes the first two dimension
Image data, second image include the first two dimensional image；And/or
Second image data includes the first 3 d image data, and second image includes the first 3-D image；
Wherein, first two dimensional image includes at least one of cross sectional image, coronal image and sagittal view picture.
11. image processing system as claimed in claim 10, which is characterized in that the module that automatically determines includes that contour line obtains
Take unit, judging unit and the first determination unit；
When second image includes first two dimensional image and first two dimensional image includes the cross sectional image,
The contour line acquiring unit is used to obtain process object described in the cross sectional image automatically according to the cross sectional image
First contour line, and obtain the second contour line of process object described in the first image；
The judging unit judges described first for be aligned comparing the first contour line with second contour line
Whether contour line is overlapped with second contour line, if it is not, then calling the determination unit；
First determination unit is for determining that second image is the image for needing correcting process.
12. image processing system as claimed in claim 10, which is characterized in that the module that automatically determines includes probability calculation
Unit and the second determination unit；
When second image includes first two dimensional image, the probability calculation unit for calculating described first automatically
Two dimensional image needs the probability of correcting process；
Second determination unit is used to determine that the probability to be greater than first two dimensional image for setting probability threshold value as needs
The image of correcting process.
13. image processing system as claimed in claim 10, which is characterized in that the module that automatically determines includes that abnormal point obtains
Take unit, image acquisition unit and third determination unit；
When second image includes first 3-D image, the abnormal point acquiring unit is for obtaining the described 1st
Tie up the abnormal point in image；
Described image acquiring unit is for obtaining first two dimension corresponding with abnormal point described in first 3-D image
Image；
The third determination unit is for determining that first two dimensional image is the image for needing correcting process.
14. image processing system as claimed in claim 9, which is characterized in that described image processing system includes correction module
With acquiring three-dimensional images module；
The correction module is used to obtain Corrections Division to needing the image of correcting process to be modified processing in second image
The second two dimensional image after reason；
The acquiring three-dimensional images module be used for according to after correcting process the corresponding image data of second two dimensional image and
The first image data that the image of correcting process is not needed in second image, obtain the two or three of the process object
Tie up image.
15. image processing system as claimed in claim 14, which is characterized in that the correction module includes that correcting region obtains
Unit and amending unit；
The correcting region acquiring unit obtains institute for comparing second image with corresponding the first image
It states and needs modified correcting region in the second image；
The amending unit is used to delete the contour line in the correcting region, and repaints the corresponding wheel of the correcting region
Profile obtains obtaining amendment until the contour line in the correcting region is overlapped with contour line corresponding in the first image
Treated the second two dimensional image；Or,
The amending unit is used to adjust the profile curvature of a curve in the correcting region, until the profile in the correcting region
Line is overlapped with contour line corresponding in the first image, obtains obtaining the second two dimensional image after correcting process.
16. the image processing system as described in any one of claim 9 to 15, which is characterized in that the process object includes
Bone.
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