CN106683058A - Calibrating method of medical image and device thereof - Google Patents
Calibrating method of medical image and device thereof Download PDFInfo
- Publication number
- CN106683058A CN106683058A CN201611215012.1A CN201611215012A CN106683058A CN 106683058 A CN106683058 A CN 106683058A CN 201611215012 A CN201611215012 A CN 201611215012A CN 106683058 A CN106683058 A CN 106683058A
- Authority
- CN
- China
- Prior art keywords
- image
- width
- medical
- medical image
- window
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000012937 correction Methods 0.000 claims description 55
- 238000013507 mapping Methods 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 238000012545 processing Methods 0.000 description 15
- 238000002591 computed tomography Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 7
- 239000003814 drug Substances 0.000 description 7
- 238000005481 NMR spectroscopy Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 6
- 210000004204 blood vessel Anatomy 0.000 description 5
- 238000013500 data storage Methods 0.000 description 5
- 238000003384 imaging method Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 210000001519 tissue Anatomy 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000002583 angiography Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000003702 image correction Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000002600 positron emission tomography Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000003795 chemical substances by application Substances 0.000 description 2
- 238000010968 computed tomography angiography Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 210000003205 muscle Anatomy 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000003325 tomography Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000002872 contrast media Substances 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 210000004247 hand Anatomy 0.000 description 1
- 238000000265 homogenisation Methods 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000002601 radiography Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 210000000278 spinal cord Anatomy 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/80—Geometric correction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30008—Bone
- G06T2207/30012—Spine; Backbone
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
The invention discloses a calibrating method of a medical image and a device thereof; the method includes steps of acquiring an initial assembling image formed by n medical images, wherein every medical image includes corresponding window width and window position; confirming an interesting zone in the n medical image; selecting one medical image as the reference image; calibrating n-1 medical images according to the image value of the interesting zone in a reference zone; assembling the reference image with the calibrated n-1 medical image, and acquiring the final assembling image. The calibrating method of the medical image and the device thereof can effectively correct the brightness of the assembled images, and meet clinical display demands.
Description
【Technical field】
The present invention relates to field of medical image processing, the bearing calibration of more particularly to a kind of medical image and its device.
【Background technology】
For nuclear magnetic resonance (MRI), magnetic resonance angiography (MRA), computed tomography (CT), positron emission
Tomoscan (Positron Emission Tomography, PET) is each in nuclear magnetic resonance, NMR (Magnetic Resonance, MR)
In the medical image that the imaging system scanning collection of class mode is obtained, due to magnetic field or coil sensitivities are uneven or radiography
Agent shows that uneven, patient pendulum position etc. affects condition, causes each section of stitching image bright when may be such that the full-scale medical image of splicing
The inconsistent problem of degree.
In process of the present invention is realized, inventor has found that at least there are the following problems in prior art：
The existing brightness correcting method for each section of stitching image is typically spliced complete image as one
It is overall, by algorithm carry out brightness from dynamic(al) correction, this method can also while the brightness between each stitching image is corrected
The local luminance of single stitching image is adjusted, may be made not needing originally the part of correcting luminance to be changed, be made knot
Fruit does not meet clinical demand.In prior art, also using luminance standard method (Intensity Standardization),
The brightness of each tissue in each section of image is all normalized in certain limit, this kind of method reaches similar CT images, each tissue is all
There is the effect of corresponding HU values scope.But such method is applied to the more fixed head image of tissue distribution, it is difficult to adapt to various
The various positions of sequence, such as full spinal column, the gamma correction of whole body stitching image.
【The content of the invention】
The technical problem to be solved proposes a kind of bearing calibration of medical image and its device, and it is right which can be realized
The brightness of stitching image is corrected to meet clinical demand.
To solve above-mentioned technical problem, the present invention provides a kind of bearing calibration of medical image, including：
The initial stitching image that n width medical image is constituted is obtained, every width medical image includes corresponding window width and window position；
Determine the area-of-interest in the n width medical image；
Choose image on the basis of a wherein width medical image；
According to the image value correction n-1 width medical images of area-of-interest in the benchmark image；
Splice the benchmark image and the n-1 width medical images after correction, obtain final stitching image；
Wherein n is the natural number more than 2.
Further, the area-of-interest in the positioning medical image, including：
According to every width medical image, the positioning image of the correspondence medical image is obtained；
The area-of-interest of the medical image is determined based on every width medical image and the positioning image.
Further, institute is obtained by the combination of entropy positioning, fit Plane equation, MIP method or preceding method
State positioning image.
Further, the image value correction n-1 width medical images according to area-of-interest in the benchmark image, bag
Include：
Obtain the average of the image value of area-of-interest in every width medical image；
According to the image value of the area-of-interest correction for mean n-1 width medical images of the benchmark image.
Further, also include, the benchmark image is the corresponding medical image of Largest Mean of the area-of-interest.
Further, the bearing calibration also includes：According to the window width and/or window position and benchmark of the initial stitching image
The window width of image and/or n width medical image described in window bit correction, obtain the final stitching image.
Further, the splicing window width minimum and the image of the benchmark image of the initial stitching image are calculated respectively
Window width minimum；
At least two width medical science according to the mapping relations correction of the splicing window width minimum and image window width minimum
Image, obtains the final stitching image.
Further, the bearing calibration of the medical image also includes：
Obtain the correction instruction of stitching image；
The value of n width medical images is changed according to the correction instruction, the final stitching image is obtained.
To solve above-mentioned technical problem, the present invention also provides a kind of correcting unit of medical image, including：
Acquiring unit, for obtaining the initial stitching image of n width medical image composition, every width medical image is comprising corresponding
Window width and window position；
Determining unit, for determining the area-of-interest in the n width medical image；
First correction unit, for image on the basis of a selection wherein width medical image；Feel according in the benchmark image
The image value correction n-1 width medical images in interest region；
Concatenation unit, for the n-1 width medical images after splicing the benchmark image and correction, obtains final spliced map
Picture；Wherein n is the natural number more than 2.
Further, also include：Second correction unit, for the window width according to the initial stitching image and/or window position
With the window width of benchmark image and/or medical image described in window bit correction, the final stitching image is obtained.
Compared with prior art, it is an advantage of the current invention that：The present invention provide a kind of bearing calibration of medical image and its
Device, according to splicing purpose, calculates the brightness of the information correction medical image of the image value in interest region, so that spliced
Complete image brightness uniformity, to meet clinical demand；By by the window width and/or window bit correction according to the initial stitching image
The medical image so that final stitching image shows the brightness of image for meeting clinical demand under default window width and window level, keeps away
The problem of brightness modification may be carried out in having exempted from prior art to the local of single stitching image, is retained to greatest extent original
The contrast of image, to meet clinical demand.
【Description of the drawings】
Fig. 1 is one embodiment of the invention Chinese medicine method for correcting image schematic flow sheet；
Fig. 2 a~2b is the schematic diagram before and after full spinal column spelling in one embodiment of the invention；
Fig. 3 is further embodiment of this invention Chinese medicine method for correcting image schematic flow sheet；
Fig. 4 is the final stitching image schematic diagram of full spinal column in further embodiment of this invention；
Correcting unit schematic diagrams of the Fig. 5 for one embodiment of the invention Chinese medicine image；
Schematic diagrams of the Fig. 6 for one embodiment of the invention Chinese medicine image device place system；
Correcting unit schematic diagrams of the Fig. 7 for further embodiment of this invention Chinese medicine image.
【Specific embodiment】
Elaborate many details in order to fully understand the present invention in the following description.But the present invention can be with
Much it is different from alternate manner described here to implement, this neighborhood technique personnel can be in the situation without prejudice to intension of the present invention
Under do similar popularization, therefore the present invention is not embodied as being limited by following public.
Secondly, the present invention is described in detail using schematic diagram, when the embodiment of the present invention is described in detail, for purposes of illustration only, institute
It is embodiment to state schematic diagram, and its here should not limit the scope of protection of the invention.Make above-mentioned purpose, the feature and excellent of the present invention
Point can become apparent from it is understandable, below gather drawings and Examples to the present invention specific embodiment be described in detail.
Embodiment 1
As shown in figure 1, the present embodiment provides a kind of bearing calibration of medical image, according to the image value of area-of-interest
The brightness of information correction medical image, each width medical image after splicing correction, obtain final stitching image, it is to avoid existing skill
When spliced medical image is corrected in art, can also carry out local directed complete set to the brightness inside medical image, may make originally not
Correcting luminance, brightness uniformity part is needed to be changed, so as to retain the contrast of original image to greatest extent, to meet
Clinical demand.
The bearing calibration can be performed by image correction apparatus, and described device can be by software and/or the side of hardware
Formula realizes that described device can be integrated in any equipment for needing and carry out medical image reconstruction, for example typically medical science three
Dimension scanning device, such as conventional CT scanners, helical CT scanners or nuclear magnetic resonance scanner etc., or pass through computer equipment
Connection is outside；Described device can also be by completing corresponding function by cloud computing platform.Wherein, cloud computing platform bag
Include but be not limited to the storage-type cloud platform based on data storage, the calculation type cloud platform based on processing data and take into account data
Storage and the comprehensive cloud computing platform for processing.The cloud platform used by system can be public cloud, private clound, community cloud or mixing
Cloud etc..For example, according to actual needs, some medical images that system is received, can be calculated by cloud platform and/or be deposited
Storage.Other medical images, can be calculated and/or be stored by local diagnosis unit and/or system database.
As shown in figure 1, the bearing calibration, including：
Execution step S101：N width medical images are obtained, every width medical image includes corresponding window width and window position.This enforcement
In example, the n width medical image obtains three-dimensional or two dimensional image by the imaging system scanning collection of all kinds of mode, it is also possible to logical
Such as cloud platform is crossed, storage is image archiving and communication system (Picture Archiving and Communication
Systems, PACS) etc. internal or external storage system transmission obtain.The mode includes but is not limited to nuclear magnetic resonance
(MRI), magnetic resonance angiography (MRA), computed tomography (CT), positron emission computerized tomography (Positron
Emission Tomography, PET) etc. one or more of combination.
For image obtain comprising whole body or large-scale is needed, as examined position is much larger than visual detector face
Long-pending contradiction causes preferably observe complete or wide-field tissue result, such as spinal column, blood vessel and whole body system etc..
However, due to restriction or the discontinuity of scan plan of technology, doctor can obtainable be n width medical images.For example by
In the restriction of scanning board size, wide-field image cannot be disposably obtained using imaging device scanning, need to regard greatly target
Open country carry out it is continuous several times scan, adjacent scanning twice includes overlapping region, a series of containing overlapping region so as to obtain
The medical image in three-dimensional data, i.e. the present embodiment, according to the initial stitching image of the n width medical image acquisition.Obtain
The every width medical image for taking includes corresponding window width and window position, and the window width and window level is obtained by calculating or user preset automatically
Take.
The three sections of spine images for being obtained by scanning human body for MRA equipment as shown in Figure 2 a.To obtain the panorama sketch of spinal column
Picture, needs carry out registration at least two width medical images, are spliced into the stitching image of panorama, are to each section as shown in Figure 2 b
The full spine image obtained after spine image registration, i.e., the described initial stitching image in the present embodiment.
Due to Equipment, such as magnetic field or situations such as uneven coil sensitivities, or as user puts position or makes
The impact of shadow agent, causes the brightness irregularities between each width medical image for obtaining, and affects clinical demand.As shown in figures 2 a and 2b,
Brightness (i.e. gray value) in medical image I, III each width image of medical image II and medical image is not of uniform size, and the doctor
In image I, on cervical region, spinal region is excessively dark so that initial stitching image does not meet clinical demand, it is therefore desirable to correct each width doctor
Learn image, the final stitching image homogeneous to obtain brightness.
Execution step S102：Determine the area-of-interest of every width medical image in the n width medical image, the n is big
In and equal to 2 natural number.As the purpose of image mosaic is different, the area-of-interest of clinical concern also therewith and is differed,
For example for the splicing of full spine image, the brightness that clinic focuses on vertebra block is homogeneous, and for blood vessel splicing image, is then blood vessel
Region, for whole body stitching image is then highlighted fat region or partially dark muscle region.Sense in the medical image
Interest region can be obtained by entropy positioning, MIP method or preceding method combination.Exemplary, for spinal column is spelled
The scene for connecing, can automatically extract spinal cord point and intervertebral is made an inventory according to the morphological feature of vertebra, and fit Plane equation is rebuild
Obtain positioning image, the positioning image is to process after the medical image comprising the most image of interested area information.Root
According to the positioning image by using level set algorithm, based on the extracting method of threshold value, based on the extracting method at edge, based on area
The extracting method in domain, based on the extracting method of cluster analyses, based on the extracting method of wavelet transformation, the side based on mathematical morphology
Method, the region of interest that the medical image is obtained based on methods such as the method for artificial neural network, methods based on genetic algorithm
Domain, such as vertebra block region.
Execution step S103~S104：Choose image on the basis of a wherein width medical image；According in the benchmark image
The image value of area-of-interest corrects the image value of the n-1 width medical images in addition to benchmark image, obtains the n-1 width after correction
Medical image；Splice the benchmark image and the n-1 width medical images after correction, obtain final stitching image.In this step, meter
The Image with Region of Interest value of each width medical image that abovementioned steps are obtained is calculated, described image value can be the area-of-interest
The maximum of gray value average, or gray value, described image value can pass through empirical value or precondition is obtained.Appoint
Image on the basis of a wherein width medical image is taken, remaining n-1 is corrected with the image value of the area-of-interest of the benchmark image
Width medical image, uniforms the image value of the area-of-interest in each width medical image, to realize each width in final stitching image
The brightness of medical image is homogeneous.
It is in the present embodiment, different according to splicing purpose, the image value of the area-of-interest collected based on each width medical image
Carry out the correction of brightness so that the brightness homogenization of final stitching image.
Embodiment 2
A kind of bearing calibration of medical image is provided in the present embodiment, based on 1 method of embodiment by each width medical image
Area-of-interest image value area tend to it is homogeneous while so that final stitching image shows satisfaction under default window width and window level
The brightness of image of clinical demand.The correcting unit that methods described can pass through in embodiment 1 is performed.Methods described as shown in figure 3,
Including：
Execution step S301：Obtain the initial stitching image that n width medical image is constituted.Wherein, every width medical image includes
Respective window width and window position, the n are the natural number more than or equal to 2.Obtain n width medical images to obtain as described in Example 1.
Obtain n width medical image can by a series of images method for registering, such as three-dimensional registration, two dimension registration, Rigid Registration and/or
Non-rigid registration obtains the initial stitching image.In the initial stitching image, due to the scanning circumstance of each width medical image
Difference deposits the display difference for causing initial stitching image each several part brightness, as shown in Figure 2 b, affects actual clinical demand.
Execution step S302~S303：According to every width medical image, the positioning image of the correspondence medical image is obtained；Base
The area-of-interest of the medical image is determined in the positioning image.Due to the purpose difference of image mosaic, clinical concern
Area-of-interest also therewith and is differed, such as, for the splicing of full spine image, clinic focuses on vertebra block, and for blood vessel is spelled
Map interlinking picture, then be angiosomeses, for whole body stitching image is then highlighted muscle region.In the present embodiment, can pass through
Entropy positioning, fit Plane equation, MIP or preceding method combination obtain the positioning image.For example, for blood vessel
Splicing scene, causes angiosomeses that highlight regions are presented in medical image as contrast agent is acted on, for each width vascular medicine
Image makees MIP in Coronal, obtains two-dimentional MIP image, conserved density maximum region (image in the MIP image
In be shown as brightness upper zone) so that the image as far as possible include most vessel informations.By using level set algorithm,
Based on the extracting method of threshold value, based on the extracting method at edge, based on the extracting method in region, the extraction side based on cluster analyses
Method, based on the extracting method of wavelet transformation, based on the method for mathematical morphology, based on the method for artificial neural network, based on something lost
The methods such as the method for the propagation algorithm process positioning image, obtains the area-of-interest of each width medical image.
Execution step S304~S305：Obtain the average of the image value of area-of-interest in every width medical image.Appoint and take one
Image on the basis of width medical image；N-1 width doctor according to the correction for mean of the image value of the benchmark image in addition to benchmark image
Learn the image value of image.For example, for the splicing scene of full spinal column, choose the corresponding doctor of Largest Mean of the area-of-interest
Image on the basis of image is learned, the brightness of remaining n-1 width medical image is adjusted, in order to clinical diagosis.Exemplary, according to public affairs
Formula 1 corrects the image value of remaining medical image.In formula 1, MmeanFor the image value of the area-of-interest of the benchmark image
Average, XimeanFor the image value average of the area-of-interest of remaining n-1 width medical image, on the basis of both ratio image with
The adjustment system of image intensity value, X between remaining medical imageBefore iAnd XAfter iBefore and after being the correction in remaining medical image respectively
Image value.To meet splicing purpose and correction rate, in the present embodiment, school can be carried out only for the image value of area-of-interest
Just.
Execution step S306：Root according to the window width of the window width and/or window position and benchmark image of the initial stitching image and/
Or window position, adjust the n width medical image.The splicing window width minimum and the benchmark of the initial stitching image are calculated respectively
The image window width minimum of image.Every width medical image has to having respective window width, window position.Window width, window position are medical science shadows
The display parameters of picture, within the specific limits, density shows shadow less than the organizational structure of window width minimum, there is no longer gray scale difference
It is different, conversely, density shows white shadow higher than the organizational structure of window width peak, there is no longer gray difference.Increase window width, then show
Grey level between the increasing number of organizational structure, but each organizational structure is reduced；Reduce window width, then show the number of organizational structure
Amount is reduced, but the grey level between each organizational structure increases.Window width, the change of window position can change the brightness of image.
The brightness of each width medical image shows uniformly by abovementioned steps, but due to benchmark image and each width medical image
Window width and window level is different from the window width and window level of stitching image, may cause each width medical image after correction in the window width of stitching image
Under window position, brightness is too high, may affect image display effect, therefore can be done by step and further correct.
Specifically, the splicing window width minimum and the image window of the benchmark image of the initial stitching image are calculated respectively
Wide minimum；The splicing window width minimum SminWith image window width minimum MminFormula (2) and formula (3) can be passed through respectively
Obtain.Wherein MWWAnd MWLOn the basis of image window width and window position, the benchmark image can be the area-of-interest maximum
The corresponding medical image of average；SWWAnd SWLThe window width of respectively initial stitching image and window position.The window width and window level can pass through
It is default to obtain, it is also possible to directly to calculate the medical image and initial stitching image is obtained.The A and B are respectively constant, this reality
Apply in example, the A and B can be chosen for 0.5.
Smin=SWL-A×SWWFormula (2)
Mmin=MWL-B×MWWFormula (3)
At least two width medical science according to the mapping relations correction of the splicing window width minimum and image window width minimum
Image image value, described image value can be the gray values of pixel or tissue points in the n width medical image, obtain described final
Stitching image.Exemplary, the mapping relations can be obtained by formula (4), among, the XBefore iAnd XAfter iIt is any respectively
Image value before and after the correction of one width medical image.
Execution step S307：Splice the benchmark image and the n-1 width medical images after correction, obtain final spliced map
Picture.As shown in Figure 4 for full spinal column splicing result carries out the final stitching image of image rectification acquisition, image Chinese medicine image
Ith, brightness (i.e. gray value) in III each width image of medical image II and medical image situation not of uniform size, the medical image
In I, cervical spine region is excessively dark, causes the brightness uniformity of each width medical image by the image value of area-of-interest, then basis
Default stitching image window width and/or window position adjust the value of each width medical image, obtain the display effect of clinical demand.
Embodiment 3
A kind of bearing calibration of medical image is provided in the present embodiment, based on the image mosaic that previous embodiment 1 and 2 is obtained
As a result, when by observation, user judges that the complete image does not meet clinical demand, by obtaining stitching image correction instruction to most
Whole stitching image carries out manual correction.For example, obtain the correction instruction of stitching image；N width doctor is corrected according to the correction instruction
Window width and/or the window position of image are learned, the final stitching image is obtained.
Embodiment 4
The correcting unit and its place application system of a kind of medical image are provided in the present embodiment, as shown in Figure 5 and Figure 6,
Described device place system can include one or more processing units, one or more memory element, one or more inputs
Unit, one or more output units, between unit can be it is distributed can also be it is centralized, can be local
Can also be long-range.
It is exemplary, as shown in fig. 6, the system includes：Input block U100, memory element U200, processing unit U300,
With output unit U400.
The input block U100, for obtaining medical image.The medical image medical science is including but not limited to by each
The imaging system scanning collection of class mode obtains three-dimensional or two dimensional image, it is also possible to be image archiving and communication by such as storage
Inside or outside system (Picture Archiving and Communication Systems, PACS) etc., storage system is passed
Defeated acquisition.The mode includes but is not limited to nuclear magnetic resonance (MRI), magnetic resonance angiography (MRA), computed tomography
(CT), CT angiographic images (CTA, CT angiography), positron emission computerized tomography (Positron Emission
Tomography, PET) etc. one or more of combination.Medical image can be sent single to storage by the input block U100
First U200 makees storage process, it is also possible to which transmitting to processing unit U300 carries out image procossing.
Memory element U200 can be the equipment with store function.The data that storage input block U100 is collected
The various data produced in (for example the medical image that, imaging device shoots) and the U300 work of meter processing unit.The storage is single
First U200 can be local, or long-range.Memory element U200 can by after information digitalization again with utilize
The storage device of electricity, the mode such as magnetically or optically is stored.Memory element U200 may also be used for depositing various information examples
Such as program and data etc..Above-mentioned storage device simply lists some examples, in the present embodiment, medical image correction side
The storage device that can be used in the working environment of method is not limited thereto.
The processing unit U300, including the medical image correcting unit, for processing the medical image, obtain bright
Final stitching image after degree correction.Described device includes acquiring unit U311, for obtaining n width medical images, every width medical science
Image includes corresponding window width and window position；Determining unit U312, for determining the every width medical image in the n width medical image
Area-of-interest；First correction unit U313, the image on the basis of a wherein width medical image is chosen；Root is according to the benchmark
In image, the image value of area-of-interest corrects the image of area-of-interest in the n-1 width medical images in addition to benchmark image
Value, obtains the n-1 width medical images after correction；Concatenation unit U314, for the n-1 width after splicing the benchmark image and correction
Medical image, obtains final stitching image；Wherein n is the natural number more than or equal to 2.
The output unit U400 can be to processing unit U300 input datas, it is also possible to which reception processing unit U300 is exported
Data, such as the initial stitching image before gamma correction and correction after final stitching image, and by output data with number
The forms such as word, character, image, sound show.The data of output can be sent to external equipment, it is also possible to not send.No
The output data of transmission can be stored in the memory unit.The output unit can include but is not limited to display device, print
The combination of one or more in equipment, drawing apparatuss, image output system, voice output system, magnetic recording equipment etc..At some
In embodiment, some external equipments can play a part of simultaneously to be input into and export, for example, desktop computer, notebook, intelligent handss
Machine, panel computer, personal digital assistant (personal digital assistance, PDA) etc..
Above-mentioned processing unit U300 can be actually existed in application system, it is also possible to completed accordingly by cloud computing platform
Function.Wherein, cloud computing platform include but is not limited to data storage based on storage-type cloud platform, based on processing data in terms of
Calculation type cloud platform and take into account data storage and process comprehensive cloud computing platform.The cloud platform used by system can be public
Cloud, private clound, community cloud or mixed cloud etc..For example, according to actual needs, some medical images that system is received, can pass through
Cloud platform is calculated and/or is stored.Other medical images, can be entered by local diagnosis unit and/or system database
Row is calculated and/or is stored.
It should be noted that between input block U100, memory element U200, processing unit U300, output unit U400
Connection or communication can be wired, or wireless.
Above for the description of medical image adjusting means and its application system, only for convenience of description, can not be this Shen
Within the scope of please being limited in illustrated embodiment.It is appreciated that for a person skilled in the art, in the original for understanding the system
After reason, combination in any may be carried out to unit in the case of without departing substantially from this principle, or constitute subsystem and other
Unit connects, the various amendments and change to implementing said method and in systematic difference field form and details.For example, store
Unit U200 can be the cloud computing platform with data storage function, including but not limited to public cloud, private clound, community cloud and
Mixed cloud etc..Such deformation, within the protection domain of the application.
Embodiment 5
The present embodiment provides a kind of correcting unit of medical image, and compared with Example 4, difference is also to include：Second
Correction unit U324, for obtaining the initial stitching image of the composition of n width medical images, according to the window of the initial stitching image
Wide and/or the window width of medical image described in window bit correction and/or window position, obtain the final stitching image.Carried based on embodiment 4
For device in by the image value area of the area-of-interest in each width medical image tend to it is homogeneous while so that final stitching image
The brightness of image for meeting clinical demand is shown under default window width and window level.
In sum, the present embodiment present invention provides a kind of bearing calibration and its device of medical image, according to splicing mesh
, the brightness of the information correction medical image of the image value in interest region is calculated, so that spliced complete image brightness is equal
It is even, to meet clinical need；By by the window of the window width according to the initial stitching image and/or medical image described in window bit correction
Wide and/or window position so that final stitching image shows the brightness of image for meeting clinical demand under default window width and window level, it is to avoid
The problem of brightness modification may be carried out in prior art to the local of single stitching image, retains original graph to greatest extent
The contrast of picture, to meet clinical demand.
It should be noted that through the above description of the embodiments, those skilled in the art can be understood that
Part or all of to the present invention can be by software and the required general hardware platform of set is realizing.Based on such understanding,
Can be embodied in the form of software product the part that technical scheme is substantially contributed to prior art in other words
Out, the computer software product may include one or more machine readable medias for being stored thereon with machine-executable instruction,
These instructions can be caused when by one or more machines execution such as computer, computer network or other electronic equipments should
One or more machine embodiments in accordance with the present invention are performing operation.Machine readable media may include, but be not limited to, floppy disk,
CD, CD-ROM (read only memory), magneto-optic disk, ROM (read only memory), RAM (random access memory), EPROM are (erasable
Except programmable read only memory), EEPROM (Electrically Erasable Read Only Memory), magnetic or optical card, flash memory or be suitable to deposit
Other kinds of medium/the machine readable media of storage machine-executable instruction.
The present invention can be used in numerous general or special purpose computing system environment or configuration.For example：Personal computer, service
Device computer, handheld device or portable set, laptop device, multicomputer system, based on the system of microprocessor, top set
Box, programmable consumer-elcetronics devices, network PC, minicomputer, mainframe computer, including any of the above system or equipment
Distributed computing environment etc..
The present invention can be described in the general context of computer executable instructions, such as program
Module.Usually, program module includes execution particular task or realizes the routine of particular abstract data type, program, object, group
Part, data structure etc..The present invention is put into practice in a distributed computing environment can also, in these distributed computing environment, by leading to
Cross communication network and connected remote processing devices are performing task.In a distributed computing environment, program module can be with position
In local and remote computer-readable storage medium including including storage device.
Although the present invention is disclosed as above with preferred embodiment, so which is not limited to the present invention, any this area skill
Art personnel, without departing from the spirit and scope of the present invention, when a little modification and perfect, therefore the protection model of the present invention can be made
Enclose to work as and be defined so that content is defined described in claims.
Claims (10)
1. a kind of bearing calibration of medical image, it is characterised in that include：
N width medical images are obtained, every width medical image includes corresponding window width and window position；
Determine the area-of-interest of every width medical image in the n width medical image；
Choose image on the basis of the width medical image in n width medical images；
Corrected in n-1 width medical images in addition to benchmark image according to the image value of area-of-interest in the benchmark image and felt
The image value in interest region, obtains the n-1 width medical images after correction；
Splice the benchmark image and the n-1 width medical images after correction, obtain final stitching image；
Wherein n is the natural number more than or equal to 2.
2. the bearing calibration of medical image according to claim 1, it is characterised in that the determination n width medical science figure
Area-of-interest in each image as in, including：
According to every width medical image, the positioning image of the correspondence medical image is obtained；
The area-of-interest of the medical image is determined based on every width medical image and the positioning image.
3. the bearing calibration of medical image according to claim 2, it is characterised in that by entropy positioning, fit Plane side
The combination of journey, MIP method or preceding method obtains the positioning image.
4. the correction method of medical image according to claim 1, it is characterised in that described according to the benchmark image
The image value of middle area-of-interest corrects the n-1 width medical images in addition to benchmark image, including：
Obtain the average of the image value of area-of-interest in every width medical image；
According to the average that the image value of area-of-interest in image is positioned per width, scheme on the basis of choosing a wherein width medical image
Picture；
The figure of the n-1 width medical images according to the correction for mean of the area-of-interest in the benchmark image in addition to benchmark image
Picture value.
5. the correction method of medical image according to claim 4, it is characterised in that also include, the benchmark image
Medical image corresponding to average the maximum of the image value of the area-of-interest.
6. the bearing calibration of medical image according to claim 1, it is characterised in that the bearing calibration also includes：Obtain
The initial stitching image of the composition of n width medical images is taken, according to the window width and/or window position and reference map of the initial stitching image
As window width and/or window position, the n width medical image is corrected, obtain the final stitching image.
7. the bearing calibration of medical image according to claim 6, it is characterised in that calculate the initial spliced map respectively
The splicing window width minimum and the image window width minimum of the benchmark image of picture；
At least two width medical science according to the mapping relations correction of the splicing window width minimum and benchmark image window width minimum
Image, obtains the stitching image.
8. the bearing calibration of medical image according to claim 1, it is characterised in that the bearing calibration of the medical image
Also include：
Obtain the correction instruction of stitching image；
N width medical image values are changed according to the correction instruction, the final stitching image is obtained.
9. a kind of correcting unit of medical image, it is characterised in that include：
Acquiring unit, for obtaining n width medical images, every width medical image includes corresponding window width and window position；
Determining unit, for determining the area-of-interest of the every width medical image in the n width medical image；
First correction unit, for image on the basis of a selection wherein width medical image；According to interested in the benchmark image
The image value of area-of-interest in n-1 width medical images of the image value correction in region in addition to benchmark image, after obtaining correction
N-1 width medical images；
Concatenation unit, for the n-1 width medical images after splicing the benchmark image and correction, obtains final stitching image；Its
Middle n is the natural number more than or equal to 2.
10. the correcting unit of medical image according to claim 9, it is characterised in that also include：Second correction unit,
For obtaining the initial stitching image of the composition of n width medical images, according to the window width of the initial stitching image and/or window position and
Benchmark image window width and/or window position, correct window width and/or the window position of the medical image, obtain the final stitching image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611215012.1A CN106683058A (en) | 2016-12-26 | 2016-12-26 | Calibrating method of medical image and device thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611215012.1A CN106683058A (en) | 2016-12-26 | 2016-12-26 | Calibrating method of medical image and device thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106683058A true CN106683058A (en) | 2017-05-17 |
Family
ID=58871393
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611215012.1A Pending CN106683058A (en) | 2016-12-26 | 2016-12-26 | Calibrating method of medical image and device thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106683058A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107977936A (en) * | 2017-11-21 | 2018-05-01 | 上海联影医疗科技有限公司 | The off-line correction method, apparatus and equipment of sequence image |
| CN111583120A (en) * | 2020-05-22 | 2020-08-25 | 上海联影医疗科技有限公司 | Image splicing method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102938145A (en) * | 2012-10-23 | 2013-02-20 | 深圳大学 | Consistency regulating method and system of splicing panoramic picture |
| CN104599247A (en) * | 2015-01-04 | 2015-05-06 | 深圳市腾讯计算机系统有限公司 | Image correction method and device |
| CN105046643A (en) * | 2015-07-06 | 2015-11-11 | 电子科技大学 | Image splicing method based on brightness adaptive registration |
| CN105069453A (en) * | 2015-08-12 | 2015-11-18 | 青岛海信电器股份有限公司 | Image correction method and apparatus |
-
2016
- 2016-12-26 CN CN201611215012.1A patent/CN106683058A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102938145A (en) * | 2012-10-23 | 2013-02-20 | 深圳大学 | Consistency regulating method and system of splicing panoramic picture |
| CN104599247A (en) * | 2015-01-04 | 2015-05-06 | 深圳市腾讯计算机系统有限公司 | Image correction method and device |
| CN105046643A (en) * | 2015-07-06 | 2015-11-11 | 电子科技大学 | Image splicing method based on brightness adaptive registration |
| CN105069453A (en) * | 2015-08-12 | 2015-11-18 | 青岛海信电器股份有限公司 | Image correction method and apparatus |
Non-Patent Citations (1)
| Title |
|---|
| 陈洪猛等: "一种高精度的DBS图像拼接算法", 《西安电子科技大学学报（自然科学版）》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107977936A (en) * | 2017-11-21 | 2018-05-01 | 上海联影医疗科技有限公司 | The off-line correction method, apparatus and equipment of sequence image |
| CN107977936B (en) * | 2017-11-21 | 2021-06-22 | 上海联影医疗科技股份有限公司 | Off-line correction method, device and equipment for sequence image |
| CN111583120A (en) * | 2020-05-22 | 2020-08-25 | 上海联影医疗科技有限公司 | Image splicing method, device, equipment and storage medium |
| CN111583120B (en) * | 2020-05-22 | 2023-11-21 | 上海联影医疗科技股份有限公司 | Image stitching method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11869202B2 (en) | Method and system for processing multi-modality image | |
| CN100470560C (en) | A method for encoding image pixels, a method for processing images and a method for processing images aimed at qualitative recognition of the object reproduced by one or more image pixels | |
| US8355553B2 (en) | Systems, apparatus and processes for automated medical image segmentation using a statistical model | |
| CN102737395B (en) | Image processing method and device in a kind of medical X-ray system | |
| CN103222876B (en) | Medical image-processing apparatus, image diagnosing system, computer system and medical image processing method | |
| US20150287188A1 (en) | Organ-specific image display | |
| CN103914852B (en) | DICOM medical images kinematic nonlinearity based on CUDA adjusts window method | |
| JP2003175023A (en) | Radiographic scoring method | |
| CN111080584A (en) | Quality control method for medical image, computer device and readable storage medium | |
| CN111882513A (en) | Clinically driven image fusion | |
| CN112785632B (en) | Cross-modal automatic registration method for DR and DRR images in image-guided radiotherapy based on EPID | |
| Fajar et al. | Reconstructing and resizing 3D images from DICOM files | |
| CN101901469A (en) | Method and system for rendering of diagnostic images on a display | |
| CN111127487B (en) | Real-time multi-tissue medical image segmentation method | |
| CN102169530A (en) | Method for image processing of mammographic images | |
| CN112053767A (en) | Artificial intelligence assignment in medical treatment | |
| CN116312986A (en) | Three-dimensional medical image labeling method and device, electronic equipment and readable storage medium | |
| CN106683058A (en) | Calibrating method of medical image and device thereof | |
| CN114365188A (en) | Analysis method and product based on VRDS AI inferior vena cava image | |
| US9996929B2 (en) | Visualization of deformations using color overlays | |
| US10832420B2 (en) | Dynamic local registration system and method | |
| CN113299369B (en) | Medical image window adjusting optimization method | |
| US20070286525A1 (en) | Generation of imaging filters based on image analysis | |
| Cordes et al. | Pre-operative segmentation of neck CT datasets for the planning of neck dissections | |
| CN114387380A (en) | Method for generating a computer-based visualization of 3D medical image data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 201807 No. 2258 Chengbei Road, Jiading Industrial Zone, Jiading District, Shanghai. Applicant after: Shanghai Lianying Medical Technology Co., Ltd Address before: 201807 No. 2258 Chengbei Road, Jiading Industrial Zone, Jiading District, Shanghai. Applicant before: SHANGHAI UNITED IMAGING HEALTHCARE Co.,Ltd. |
|
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170517 |