CN110400299A - A kind of method and device of lung's pleural effusion detection - Google Patents
A kind of method and device of lung's pleural effusion detection Download PDFInfo
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Abstract
The invention discloses a kind of method and devices of lung's pleural effusion detection, this method includes obtaining lung image information, according to lung image information, determine pleural effusion region, determine the area in pleural effusion region, according to the position of the area in pleural effusion region and pleural effusion region, the pleural effusion of lung is detected.Pleural effusion region is determined by lung image information, to obtain the area in pleural effusion region, further according to the position in pleural effusion region, determine whether the pleural effusion region is pleural effusion, for the mode of traditional diagnosis, Error Diagnostics rate caused by can reduce because of doctor's level difference, to improve the accuracy of pleural effusion detection.
Description
Technical field
A kind of detected the present embodiments relate to machine learning techniques field more particularly to lung's pleural effusion method and
Device.
Background technique
With getting worse for environmental pollution, more and more diseases show the trend of high outburst rate.Modern medical service skill
The development of art is very mature, and doctor can be diagnosed to be various diseases by medical knowledge and medical experience.That is, existing
There is most diagnosis by doctor of the determination disease in technology, however since the medical level in each area is very inconsistent, and
Personal experience's level of doctor is also irregular, and therefore, the method for traditional diagnosis disease is easy by regional healthcare water
Flat and doctor's personal experience's level image, leads to the problem that Error Diagnostics are larger.
By taking lung's pleural effusion as an example, doctor usually requires artificially to observe lung's 3D image, with what is suffered to patient
The case where pleural effusion is analyzed, this process inevitably will appear mistaken diagnosis.
Based on this, a kind of method for detecting pleural effusion is needed at present, for improving the accuracy rate of detection pleural effusion.
Summary of the invention
The embodiment of the present invention provides a kind of method and device of lung's pleural effusion detection, to improve detection pleural effusion
Accuracy rate.
A kind of first aspect method of lung's pleural effusion detection provided in an embodiment of the present invention, comprising:
Obtain lung image information；
According to the lung image information, pleural effusion region is determined；
Determine the area in the pleural effusion region；
According to the position of the area in the pleural effusion region and the pleural effusion region, the thoracic cavity of the lung is detected
Hydrops.
In above-mentioned technical proposal, pleural effusion region is determined by lung image information, to obtain pleural effusion area
The area in domain determines whether the pleural effusion region is pleural effusion, compared to tradition further according to the position in pleural effusion region
Diagnosis mode for, Error Diagnostics rate caused by can reduce because of doctor's level difference, to improve pleural effusion
The accuracy of detection.
Optionally, the lung image information includes lung's 3D image；
It is described according to the lung image information, determine pleural effusion region, comprising:
The lung 3D image is input in the first pleural effusion parted pattern, the pleural effusion region is obtained；
The first pleural effusion parted pattern is to be trained study according to marked pleural effusion image to obtain.
Optionally, the lung image information further includes that lung segmentation image and/or lung split segmentation image；
It is described according to the lung image information, determine pleural effusion region, comprising:
The lung 3D image and lung segmentation image and/or the lung are split into segmentation image and are input to the second thoracic cavity
In hydrops parted pattern, the pleural effusion region is obtained；
The second pleural effusion parted pattern is according to marked pleural effusion image and marked lung segmentation
Image and/or marked lung split segmentation image and are trained what study obtained.
Optionally, the area in the determination pleural effusion region, comprising:
According to the quantity of the pixel in the pleural effusion region, the area in the pleural effusion region is determined.
Optionally, described according to the area in the pleural effusion region and the position in the pleural effusion region, detect institute
State the pleural effusion of lung, comprising:
According to the area in the pleural effusion region, determine that area is greater than the pleural effusion region of first threshold；
The area is greater than to the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined
For the pleural effusion of the lung.
Optionally, the pleural effusion for being determined as the lung, further includes:
Determine that lung's pleural effusion is located at left lung pleural effusion or right lung pleural effusion.
Second aspect, the embodiment of the present invention provide a kind of device of lung's pleural effusion detection, comprising:
Acquiring unit, for obtaining lung image information；
Processing unit, for determining pleural effusion region according to the lung image information；Determine the pleural effusion
The area in region；According to the position of the area in the pleural effusion region and the pleural effusion region, the lung is detected
Pleural effusion.
Optionally, the processing unit is specifically used for:
The lung 3D image is input in the first pleural effusion parted pattern, the pleural effusion region is obtained；
The first pleural effusion parted pattern is to divide image according to marked pleural effusion image, marked lung
Segmentation image, which is split, with marked lung is trained what study obtained.
Optionally, the lung image information further includes that lung segmentation image and/or lung split segmentation image；
The processing unit is specifically used for:
The lung 3D image and lung segmentation image and/or the lung are split into segmentation image and are input to the second thoracic cavity
In hydrops parted pattern, the pleural effusion region is obtained；
The second pleural effusion parted pattern is according to marked pleural effusion image and marked lung segmentation
Image and/or marked lung split segmentation image and are trained what study obtained.
Optionally, the processing unit is specifically used for:
According to the quantity of the pixel in the pleural effusion region, the area in the pleural effusion region is determined.
Optionally, the processing unit is specifically used for:
According to the area in the pleural effusion region, determine that area is greater than the pleural effusion region of first threshold；
The area is greater than to the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined
For the pleural effusion of the lung.
Optionally, the processing unit is also used to:
Determine that lung's pleural effusion is located at left lung pleural effusion or right lung pleural effusion.
Correspondingly, the embodiment of the invention also provides a kind of calculating equipment, comprising:
Memory, for storing program instruction；
Processor executes above-mentioned lung according to the program of acquisition for calling the program instruction stored in the memory
The method of pleural effusion detection.
Correspondingly, the embodiment of the invention also provides a kind of computer-readable non-volatile memory medium, including computer
Readable instruction, when computer is read and executes the computer-readable instruction, so that computer executes above-mentioned lung thoracic cavity product
The method of liquid detection.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment
Attached drawing is briefly introduced, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill in field, without creative efforts, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is a kind of schematic diagram of system architecture provided in an embodiment of the present invention；
Fig. 2 is a kind of flow diagram of the method for lung's pleural effusion detection provided in an embodiment of the present invention；
Fig. 3 is a kind of schematic diagram of lung 3D image provided in an embodiment of the present invention；
Fig. 4 is a kind of structural schematic diagram of the device of lung's pleural effusion detection provided in an embodiment of the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into
It is described in detail to one step, it is clear that described embodiments are only a part of the embodiments of the present invention, rather than whole implementation
Example.Based on the embodiments of the present invention, obtained by those of ordinary skill in the art without making creative efforts
All other embodiment, shall fall within the protection scope of the present invention.
Fig. 1 is a kind of system architecture provided in an embodiment of the present invention.Refering to what is shown in Fig. 1, the system architecture can be service
Device 100, including processor 110, communication interface 120 and memory 130.
Wherein, the terminal device that communication interface 120 is applicable in for doctor communicates, and receives and dispatches the letter of terminal device transmission
Breath realizes communication.
Processor 110 is the control centre of server 100, utilizes various interfaces and the entire server 100 of connection
Various pieces by running or execute the software program/or module that are stored in memory 130, and are called and are stored in storage
Data in device 130, the various functions and processing data of execute server 100.Optionally, processor 110 may include one
Or multiple processing units.
Memory 130 can be used for storing software program and module, and processor 110 is stored in memory 130 by operation
Software program and module, thereby executing various function application and data processing.Memory 130 can mainly include storage journey
Sequence area and storage data area, wherein storing program area can application program needed for storage program area, at least one function etc.；
Storage data area can store the data etc. created according to business processing.In addition, memory 130 may include high random access
Memory, can also include nonvolatile memory, a for example, at least disk memory, flush memory device or other are volatile
Property solid-state memory.
It should be noted that above-mentioned structure shown in FIG. 1 is only a kind of example, it is not limited in the embodiment of the present invention.
Based on foregoing description, Fig. 2 illustratively shows a kind of lung's pleural effusion detection provided in an embodiment of the present invention
Method process, which can be executed by device that lung's pleural effusion detects, which can be located at clothes shown in FIG. 1
It is engaged in device 100, is also possible to the server 100.
As shown in Fig. 2, the process specifically includes:
Step 201, lung image information is obtained.
The lung image information may include lung's 3D image.The lung image information also may include lung's 3D image and
Lung divides image or the lung image information includes lung's 3D image and lung splits segmentation image or the lung image information includes
Lung's 3D image, lung segmentation image and lung split segmentation image.Wherein, lung 3D image is 3-D image.Lung's 3D image can be with
It is computer tomography (Computed Tomography, CT) image, magnetic resonance imaging (Magnetic Resonance
Imaging, MRI) image etc., for clearer description lung 3D image, Fig. 3 illustrates the lung of a patient
CT images.Lung segmentation image is the image of the binaryzation of lung CT.It is the binaryzation that lung's lung splits CT that lung, which splits segmentation image,
Image, lung split the case where segmentation image is for distinguishing lung's each lobe of the lung.
Step 202, according to the lung image information, pleural effusion region is determined.
Specifically, lung's 3D image can be input to the first thoracic cavity product when lung image information is lung 3D image
In liquid parted pattern, pleural effusion region is obtained, wherein the first pleural effusion parted pattern is according to marked pleural effusion
Image is trained what study obtained.
It, can also be by lung's 3D image when lung image information further includes lung segmentation image and/or lung splits segmentation image
And lung segmentation image and/or lung split segmentation image and are input in the second pleural effusion parted pattern, obtain pleural effusion region,
Wherein, the second pleural effusion parted pattern be according to marked pleural effusion image and marked lung segmentation image and/
Or marked lung splits segmentation image and is trained what study obtained.
It should be noted that the first pleural effusion model and the second pleural effusion model can be known as pleural effusion point
Cut model, wherein " first " " second " is to distinguish two different pleural effusion parted patterns.In specific application, should
Pleural effusion parted pattern may include that pretreatment cutting module, full convolutional neural networks segmentation module and segmentation result merge mould
Block.Lung 3D image cutting is several groups 2D image bearing layer by the pretreatment cutting module, such as each frame figure can be taken along Z-direction
Picture, for each frame image contract continuously several frames as a group image layer.
The full convolutional neural networks segmentation module can be full connection convolutional neural networks, such as FCN, U-NET etc..With U-
It may include a 3D convolution feature extraction block, three down-sampling blocks and three up-sampling blocks for NET.And 3D convolution is special
It includes two continuous convolution units that sign, which extracts block, and each unit includes N × N × M 3D convolutional layer, a batch
Normalization (normalization) layer and a relu excitation function layer.Down-sampling block includes Y × Y × Y 3D max
Pooling (pond) down-sampling layer and a convolution feature extraction block.Up-sampling block includes Y × Y × Y deconvolution
Up-sample layer, a splicing layer and a convolution feature extraction block.Splice the output result and correspondence of layer splicing preceding layer
The output result of down-sampling layer.In the specific application process, several groups 2D image bearing layer, lung segmentation image and lung are split into segmentation image
As 3 dimension single channel array of pixels, down-sampling knot is obtained by a convolution feature extraction block, then by three down-sampling blocks
Fruit, down-sampling result pass through the probability results of the segmentation in the pleural effusion region of three up-sampling available lungs of block again,
It is exactly the probability graph of lung image.It should be noted that each up-sampling block is after up-sampling and the down-sampling block of correspondingly-sized
As a result it connects.
By giving a threshold value (such as 0.5), probability graph can be split, be divided into binary map, so as to obtain lung
The pleural effusion region in portion.Such as can be pleural effusion region that whole white part is lung or completely black color part is lung
Pleural effusion region.
Step 203, the area in the pleural effusion region is determined.
After obtaining the area in pleural effusion region, so that it may according to the quantity of the pixel in pleural effusion region, really
Determine the area in pleural effusion region, that is, calculate the quantity with the pleural effusion region of same pixel point, so that it may obtain
The area in pleural effusion region.
Step 204, according to the position of the area in the pleural effusion region and the pleural effusion region, the lung is detected
The pleural effusion in portion.
Specifically, can determine that area is greater than the pleural effusion area of first threshold according to the area in pleural effusion region
Area is greater than the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined as lung by domain
Pleural effusion.Wherein, those skilled in the art can rule of thumb set the specific value of first threshold with actual conditions, this
Place is without limitation.
Also can determine whether out while the pleural effusion for determining lung lung's pleural effusion be located at left lung pleural effusion or
Right lung pleural effusion, in order to provide diagnosis thinking for doctor.
Above-described embodiment shows that obtaining lung image information determines pleural effusion region according to lung image information,
The area for determining pleural effusion region detects lung according to the position of the area in pleural effusion region and pleural effusion region
Pleural effusion.Pleural effusion region is determined by lung image information, so that the area in pleural effusion region is obtained, further according to
The position in pleural effusion region determines whether the pleural effusion region is pleural effusion, compared to the side of traditional diagnosis
For formula, Error Diagnostics rate caused by can reduce because of doctor's level difference, to improve the accuracy of pleural effusion detection.
Based on the same technical idea, Fig. 4 illustratively shows a kind of lung thoracic cavity product provided in an embodiment of the present invention
The structure of the device of liquid detection, the device can execute the process of lung's pleural effusion detection, which can be located at shown in Fig. 1
Server 100 in, be also possible to the server 100.
As shown in figure 4, the device specifically includes:
Acquiring unit 401, for obtaining lung image information；
Processing unit 402, for determining pleural effusion region according to the lung image information；Determine the thoracic cavity
The area in hydrops region；According to the position of the area in the pleural effusion region and the pleural effusion region, the lung is detected
The pleural effusion in portion.
Optionally, the lung image information includes lung's 3D image；
The processing unit 402 is specifically used for:
The lung 3D image is input in the first pleural effusion parted pattern, the pleural effusion region is obtained；
The first pleural effusion parted pattern is to divide image according to marked pleural effusion image, marked lung
Segmentation image, which is split, with marked lung is trained what study obtained.
Optionally, the lung image information further includes that lung segmentation image and/or lung split segmentation image；
The processing unit 402 is specifically used for:
The lung 3D image and lung segmentation image and/or the lung are split into segmentation image and are input to the second thoracic cavity
In hydrops parted pattern, the pleural effusion region is obtained；
The second pleural effusion parted pattern is according to marked pleural effusion image and marked lung segmentation
Image and/or marked lung split segmentation image and are trained what study obtained.
Optionally, the processing unit 402 is specifically used for:
According to the quantity of the pixel in the pleural effusion region, the area in the pleural effusion region is determined.
Optionally, the processing unit 402 is specifically used for:
According to the area in the pleural effusion region, determine that area is greater than the pleural effusion region of first threshold；
The area is greater than to the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined
For the pleural effusion of the lung.
Optionally, the processing unit 402 is also used to:
Determine that lung's pleural effusion is located at left lung pleural effusion or right lung pleural effusion.
Based on the same technical idea, the embodiment of the invention also provides a kind of calculating equipment, comprising:
Memory, for storing program instruction；
Processor executes above-mentioned lung according to the program of acquisition for calling the program instruction stored in the memory
The method of pleural effusion detection.
Based on the same technical idea, the embodiment of the invention also provides a kind of computer-readable non-volatile memories to be situated between
Matter, including computer-readable instruction, when computer is read and executes the computer-readable instruction, so that computer executes
The method for stating the detection of lung's pleural effusion.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (10)
1. a kind of method of lung's pleural effusion detection characterized by comprising
Obtain lung image information；
According to the lung image information, pleural effusion region is determined；
Determine the area in the pleural effusion region；
According to the position of the area in the pleural effusion region and the pleural effusion region, the thoracic cavity product of the lung is detected
Liquid.
2. the method as described in claim 1, which is characterized in that the lung image information includes lung's 3D image；
It is described according to the lung image information, determine pleural effusion region, comprising:
The lung 3D image is input in the first pleural effusion parted pattern, the pleural effusion region is obtained；
The first pleural effusion parted pattern is to be trained study according to marked pleural effusion image to obtain.
3. method according to claim 2, which is characterized in that the lung image information further include lung segmentation image and/or
Lung splits segmentation image；
It is described according to the lung image information, determine pleural effusion region, comprising:
The lung 3D image and lung segmentation image and/or the lung are split into segmentation image and are input to the second pleural effusion
In parted pattern, the pleural effusion region is obtained；
The second pleural effusion parted pattern is to divide image according to marked pleural effusion image and marked lung
And/or marked lung splits segmentation image and is trained what study obtained.
4. the method as described in claim 1, which is characterized in that the area in the determination pleural effusion region, comprising:
According to the quantity of the pixel in the pleural effusion region, the area in the pleural effusion region is determined.
5. such as the described in any item methods of Claims 1-4, which is characterized in that the face according to the pleural effusion region
Long-pending and the pleural effusion region position, detects the pleural effusion of the lung, comprising:
According to the area in the pleural effusion region, determine that area is greater than the pleural effusion region of first threshold；
The area is greater than to the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined as institute
State the pleural effusion of lung.
6. a kind of device of lung's pleural effusion detection characterized by comprising
Acquiring unit, for obtaining lung image information；
Processing unit, for determining pleural effusion region according to the lung image information；Determine the pleural effusion region
Area；According to the position of the area in the pleural effusion region and the pleural effusion region, the thoracic cavity of the lung is detected
Hydrops.
7. device as claimed in claim 6, which is characterized in that the lung image information includes lung's 3D image；
The processing unit is specifically used for:
The lung 3D image is input in the first pleural effusion parted pattern, the pleural effusion region is obtained；
The first pleural effusion parted pattern is to be trained study according to marked pleural effusion image to obtain.
8. device as claimed in claim 7, which is characterized in that the lung image information further include lung segmentation image and/or
Lung splits segmentation image；
The processing unit is specifically used for:
The lung 3D image and lung segmentation image and/or the lung are split into segmentation image and are input to the second pleural effusion
In parted pattern, the pleural effusion region is obtained；
The second pleural effusion parted pattern is to divide image according to marked pleural effusion image and marked lung
And/or marked lung splits segmentation image and is trained what study obtained.
9. device as claimed in claim 6, which is characterized in that the processing unit is specifically used for:
According to the quantity of the pixel in the pleural effusion region, the area in the pleural effusion region is determined.
10. such as the described in any item devices of claim 6 to 9, which is characterized in that the processing unit is specifically used for:
According to the area in the pleural effusion region, determine that area is greater than the pleural effusion region of first threshold；
The area is greater than to the pleural effusion region for being located at the bottom of lung in the pleural effusion region of first threshold, is determined as institute
State the pleural effusion of lung.
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| CN112869758A (en) * | 2020-12-31 | 2021-06-01 | 杭州依图医疗技术有限公司 | Method and device for determining pleural effusion |
| CN113017687A (en) * | 2021-02-19 | 2021-06-25 | 上海长征医院 | Automatic identification method for B-ultrasonic image of abdominal dropsy |
| CN113763352A (en) * | 2021-09-06 | 2021-12-07 | 杭州类脑科技有限公司 | Method and system for processing abdominal cavity effusion image |
| CN114599291A (en) * | 2019-12-23 | 2022-06-07 | 深圳华大智造科技股份有限公司 | Ultrasonic detection method, system, mobile device and storage medium for trauma |
| CN114931125A (en) * | 2022-03-16 | 2022-08-23 | 江苏靶标生物医药研究所有限公司 | Method for constructing mouse lung cancer pleural effusion model |
| KR102454374B1 (en) * | 2021-10-07 | 2022-10-14 | 주식회사 피맥스 | Method for detecting pleurl effusion and apparatus therof |
| KR20230049937A (en) * | 2021-10-07 | 2023-04-14 | 주식회사 피맥스 | Method for detecting pleurl effusion and the apparatus for therof |
| CN116137033A (en) * | 2023-04-20 | 2023-05-19 | 天津医科大学总医院 | A method for effusion assessment based on thoracic imaging and drainage data analysis |
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