CN111493829A - Method, system and equipment for determining mild cognitive impairment recognition parameters - Google Patents
Method, system and equipment for determining mild cognitive impairment recognition parameters Download PDFInfo
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Abstract
The invention relates to a method, a system and equipment for determining recognition parameters of mild cognitive impairment, belonging to the technical field of image analysis. The method comprises the steps of directly obtaining a copy image of a target testee, and analyzing the copy image by a computer, so that the mild cognitive impairment recognition parameters are obtained according to difference content. Medical personnel can directly discern a plurality of target testees according to the identification parameter, and convenient, swift has promoted the popularization scope. Through setting up the classifier, can divide into not mild cognitive disorder, mild cognitive disorder earlier stage, mild cognitive disorder later stage etc. with the target person under test, classify target person under test, convenient, swift.
Description
Technical Field
The invention belongs to the technical field of image analysis, and particularly relates to a method, a device and equipment for determining a mild cognitive impairment recognition parameter.
Background
Alzheimer's disease (AD, commonly known as senile dementia) is an irreversible chronic degenerative disease of the nervous system, and its main clinical manifestations include hypomnesis, cognitive decline and life inability. The survival period of the Alzheimer disease patients is generally 3-10 years, the disease is mostly generated in the elderly over 60 years old, and the incidence rate is gradually increased along with the increase of the age. AD has become a commonly faced problem worldwide. However, the specific cause of AD is not clear so far, and once AD is present, it cannot be treated. Therefore, early diagnosis and early treatment and intervention are the most effective methods to deal with AD.
Early clinical stages of alzheimer's disease manifest as Mild Cognitive Impairment (MCI), when the best diagnosis and intervention period. Thus, if MCIs can be screened or detected to some extent, effective early intervention can be performed on the patient to a large extent.
Currently, in the prior art, the MCI is usually detected in the form of a scale, i.e. a question is designed in advance, and a special medical staff inquires and detects the patient, records the result, and analyzes the result to determine the condition of the patient. However, the detection in this form requires professional medical staff, takes a long time, consumes a large amount of human resources, and cannot be popularized, so that many potential patients cannot be diagnosed in time and miss the optimal treatment period. Therefore, how to realize convenient and rapid detection of patients becomes a problem to be solved urgently.
Disclosure of Invention
In order to solve at least the above problems in the prior art, the invention provides a mild cognitive impairment recognition parameter determination method, system and device.
The technical scheme provided by the invention is as follows:
in one aspect, a mild cognitive impairment recognition parameter determination method comprises the following steps:
obtaining a copy image of a target testee based on a preset graph;
acquiring the difference content of the copying image and a preset reference graph according to the copying image, a preset processing rule and the preset reference graph;
and determining the mild cognitive impairment recognition parameters according to the difference content.
Optionally, the preset processing rule includes:
obtaining a copy image with preset colors in the copy image based on color classification;
according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image;
and matching the starting points of the target image and the preset reference image based on a preset starting point searching method.
Optionally, the obtaining, according to the copy image, a preset processing rule, and a preset reference pattern, a difference content between the copy image and the preset reference pattern includes:
extracting the pixel point coordinate of each preset color in the preset reference graph;
extracting subspace characteristics corresponding to the coordinates in the target image;
and acquiring the difference content between the copy image and the preset reference graph based on the pixel point coordinates and the subspace characteristics.
Optionally, the obtaining of the difference content between the copy image and the preset reference pattern includes:
classifying the subspace characteristics based on the pixel point coordinates, the subspace characteristics and a preset classifier;
the classifier includes: support vector machines or random forests.
In another aspect, a mild cognitive impairment recognition parameter determination system includes: acquiring a template and a processing assembly; the acquisition template is connected with the processing assembly;
the acquisition template is used for acquiring a copy image of a target testee based on a preset graph;
the processing component is used for acquiring the difference content between the copying image and a preset reference graph according to the copying image, a preset processing rule and the preset reference graph; and determining the mild cognitive impairment recognition parameters according to the difference content.
Optionally, the preset processing rule in the processing component includes: obtaining a copy image with preset colors in the copy image based on color classification; according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image; and matching the starting points of the target image and the preset reference image based on a preset starting point searching method.
Optionally, the processing component is configured to: extracting the pixel point coordinate of each preset color in the preset reference graph; extracting subspace characteristics corresponding to the coordinates in the target image; and acquiring the difference content between the copy image and the preset reference graph based on the pixel point coordinates and the subspace characteristics.
Optionally, the processing component is configured to classify the subspace features by using the pixel point coordinates, the subspace features, and a preset classifier; the classifier includes: support vector machines or random forests.
Optionally, the obtaining template is a digital plate; and/or the processing component is a computer.
In still another aspect, a mild cognitive impairment recognition parameter determination apparatus includes: a processor, and a memory coupled to the processor;
the memory is used for storing a computer program, and the computer program is at least used for executing the mild cognitive impairment recognition parameter determination method;
the processor is used for calling and executing the computer program in the memory.
The invention has the beneficial effects that:
the method comprises the steps of obtaining a copy image of a target testee based on a preset graph, obtaining difference content of the copy image and the preset reference graph according to the copy image, a preset processing rule and a preset reference graph, and determining a mild cognitive impairment identification parameter according to the difference content. The method comprises the steps of directly obtaining a copy image of a target testee, and analyzing the copy image by a computer, so that the mild cognitive impairment recognition parameters are obtained according to difference content. Medical personnel can directly discern a plurality of target testees according to the identification parameter, and convenient, swift has promoted the popularization scope. Through setting up the classifier, can divide into not mild cognitive disorder, mild cognitive disorder earlier stage, mild cognitive disorder later stage etc. with the target person under test, classify target person under test, convenient, swift.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another method for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a mild cognitive impairment recognition parameter measurement system according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a mild cognitive impairment recognition parameter measurement device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
In order to solve at least the technical problems proposed by the present invention, an embodiment of the present invention provides a method for determining a mild cognitive impairment recognition parameter.
Fig. 1 is a schematic flow chart of a method for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention, referring to fig. 1, the method according to the embodiment of the present invention may include the following steps:
s11, obtaining a copy image of the target testee based on a preset graph;
s12, determining a mild cognitive impairment recognition parameter according to the copied image, a preset processing rule and a preset reference graph;
and S13, determining the recognition parameters of the mild cognitive impairment according to the difference content.
Specifically, one or some of the multiple testees may be selected as the target testee, and the target testee may be tested. Firstly, an acquisition template can be selected to obtain a copy image of a receiving target testee based on a preset graph, a processing component is selected to obtain the difference content of the copy image and the preset reference graph according to the copy image, the preset processing rule and the preset reference graph, and the mild cognitive impairment identification parameters are determined according to the difference content.
For example, the acquisition template may be a tablet, and the processing component may be a computer, and it should be noted that the acquisition template and the processing component are listed herein, but not limited thereto.
The digital board, also known as drawing board, hand drawing board, etc. is one kind of computer input equipment, and is usually composed of one board and one pressure sensing pen, and is similar to handwriting board, etc. as non-conventional input product, and is aimed at certain group of users. The method is used for drawing creation, like a drawing board and a painting brush of an artist, and vivid pictures and lifelike characters which are common in animation movies are drawn by one stroke through a digital board. The drawing function of the digital board is a place which can not be compared with the keyboard and the handwriting board. The digital board mainly faces professional teachers and students related to design and art, advertising companies, design studios and Flash vector animation producers. The computer can be any type of computer, and is not limited herein.
In a specific testing process, a preset pattern may be preset, for example, the preset pattern may be a paper template, a paper template may be a paper pattern, each paper template may be a paper pattern or a spiral pattern, or each paper template may have a plurality of patterns, which is not limited herein. Here, the carrier with the preset pattern is taken as a paper template, and a single pattern is arranged on each paper template. The two paper templates are respectively provided with a clip graph and a spiral graph.
The two paper templates are respectively placed on the digital board, a person to be tested can draw corresponding patterns along black lines from a central starting point by using a matched electronic pen according to the shapes of the template patterns, and the digital board displays the patterns on a computer in real time through a data line and stores the patterns to obtain collected information. The two templates are used separately and collected so that each target subject gets two pictures.
After the copy image is obtained, the copy image can be subjected to preliminary processing, the processed copy image is compared with a preset reference figure, the difference content between the copy image and the preset reference figure is obtained, and the mild cognitive impairment identification parameters are determined according to the difference content. For example, the content of the difference between the copy image and the preset reference pattern may include an coincidence rate of the copy image and the preset reference pattern, and the coincidence rate is used as a mild cognitive impairment recognition parameter.
In a specific detection process, the computer displays the calculated difference content rate, and the medical staff can identify whether the target testee has mild cognitive impairment according to the difference content, such as the anastomosis rate, and determine that the target testee has mild cognitive impairment when the anastomosis rate is lower than a set threshold value.
The method for determining the mild cognitive impairment parameters based on the handwritten information comprises the steps of obtaining a copy image of a target testee based on a preset graph, obtaining difference contents of the copy image and the preset reference graph according to the copy image, a preset processing rule and a preset reference graph, and determining the mild cognitive impairment identification parameters according to the difference contents. The method comprises the steps of directly obtaining a copy image of a target testee, and analyzing the copy image by a computer, so that the mild cognitive impairment recognition parameters are obtained according to difference content. Medical personnel can directly discern a plurality of target testees according to the identification parameter, and convenient, swift has promoted the popularization scope.
Based on the general inventive concept, the embodiments of the present invention also provide another method for determining mild cognitive impairment recognition parameters.
Fig. 2 is a schematic flow chart of another method for determining a mild cognitive impairment recognition parameter according to an embodiment of the present invention, referring to fig. 2, the method according to the embodiment of the present invention may include the following steps:
and S21, acquiring a copy image of the target testee based on the preset graph.
Step S21 is the same as step S11, please refer to S11 above, and further description thereof is omitted.
S22, acquiring a copy image with preset colors in the copy image based on color classification; according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image; and matching the target image with the starting point of the preset reference graph based on a preset starting point searching method.
Specifically, black may be selected as the preset color. After the copy image of the target testee is collected, the copy image is processed according to a preset processing rule, and the preset processing rule can be as follows: removing white edges, adjusting the size and matching templates.
For example, in the copy image of the target subject, a large amount of blank portions are formed around the copy image and do not include the copy track of the target subject, so that white edges around the copy track can be deleted, rows and columns with black pixel points are found by scanning the four edges line by line through a scanning method, the rows and the columns are new edges, and the middle image information is retained, so that a black copy image can be obtained.
The size of the image without the white edge is different from that of a corresponding preset reference figure (namely, a template), and the sizes of the images are different, so that all the collected copy images can be reduced to the same size in a unified and proportional manner according to the width or height of the template picture, for example: the size of the template is reduced to 78 x 80 to make the size smaller than that of the collected image, the size of the input copy image is x y, a scaling factor c is calculated to be 80/y according to the standard of uniform width, and the width and the height of the image are resampled by using a pixel relation according to the scaling factor c. This method can prevent moire from occurring when the image is reduced. The size of the finally obtained image is x '80 (x' c x), at this time, the height of the image is still inconsistent with that of the template, and the image and the template can be filled to the standard size of 100 x 100 by adopting an edge filling method.
Since the target examinee is depicted from the center of the circle graph and the spiral graph when the copy image is collected, the input copy image and the template can be aligned from the starting point before feature extraction is carried out to remove the difference generated by collection. For example, according to a method for automatically finding a starting point of an image, in a clip chart, the left side of the starting point is all white pixel points, the upper side and the lower side of the starting point are all white pixel points, and other black pixel points do not have the characteristic, so that black pixel points are sequentially scanned from the middle part of the image according to the characteristic to find a target point. After finding the starting point of the image, for example, the coordinates of the starting point are (x, y), the coordinates of the starting point of the template are (x0, y0), the horizontal and vertical coordinate difference (u, v) between the two points is calculated, u is x0-x, v is y0-y, and the difference (u, v) is added to all the black pixel coordinates in the input copy image to obtain an image after the image is uniformly moved to the starting point of the template, namely the target image.
S23, extracting the pixel point coordinate of each preset color in the preset reference graph; extracting subspace characteristics corresponding to the coordinates in the target image; and acquiring the difference content between the copy image and the preset reference image based on the pixel point coordinates and the subspace characteristics.
Optionally, acquiring the difference content between the copy image and the preset reference pattern includes: and classifying the subspace characteristics based on the pixel point coordinates, the subspace characteristics and a preset classifier.
Specifically, after the target image is acquired, feature extraction may be performed on the target image and a preset reference pattern (i.e., a template). For example, all black pixel coordinates of the template may be extracted, and the subspace feature corresponding to the black pixel coordinates of the template in the target image may be extracted.
Since the target testee may possibly have an appropriate deviation due to the MCI during drawing, 8-domain or 4-domain pixels near each coordinate pixel can be adopted as the feature of the current coordinate point by the method of extracting the feature in the subspace.
After the pixel point coordinates and the subspace characteristics are obtained, the pixel point coordinates and the subspace characteristics can be classified according to a pre-trained classifier, and the classifier can be a support vector machine, a random forest and the like.
For example, the target subject may be classified by a classifier into non-mild cognitive impairment, pre-mild cognitive impairment, post-mild cognitive impairment, and the like.
According to the method for determining the mild cognitive impairment recognition parameters, provided by the embodiment of the invention, the target testee can be classified into non-mild cognitive impairment, early stage of mild cognitive impairment, later stage of mild cognitive impairment and the like by arranging the classifier, so that the target testee can be classified conveniently and quickly.
Based on one general inventive concept, the embodiments of the present invention also provide a mild cognitive impairment recognition parameter determination system.
Fig. 3 is a schematic structural diagram of a system for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention, referring to fig. 3, the system according to an embodiment of the present invention may include the following structures: acquiring a template 31 and a processing component 32; the acquisition template 31 is connected with the processing component 32;
the acquisition template 31 is used for acquiring a copy image of a target testee based on a preset graph;
the processing component 32 is configured to obtain a difference content between the copy image and a preset reference pattern according to the copy image, a preset processing rule, and the preset reference pattern; and determining a mild cognitive impairment recognition parameter according to the difference content.
Optionally, the preset processing rule in the processing component 32 includes: obtaining a copy image with preset colors in the copy image based on the color classification; according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image; and matching the target image with the starting point of the preset reference graph based on a preset starting point searching method.
Optionally, the processing component 32 is configured to: extracting the coordinates of pixel points of each preset color in a preset reference graph; extracting subspace characteristics corresponding to the coordinates in the target image; and acquiring the difference content between the copy image and the preset reference image based on the pixel point coordinates and the subspace characteristics.
Optionally, the processing component 32 is configured to classify the subspace characteristics according to the pixel point coordinates, the subspace characteristics, and a preset classifier; the classifier includes: support vector machines or random forests.
Optionally, the obtaining template 31 is a digitizer; and/or the processing component 32 is a computer.
With respect to the acquisition template and the processing component in the above embodiments, the specific manner in which they perform operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
The working mode of the system for measuring the mild cognitive impairment parameters based on the handwritten information provided by the embodiment of the invention comprises the steps of obtaining a copy image of a target testee based on a preset graph, obtaining the difference content of the copy image and the preset reference graph according to the copy image, a preset processing rule and a preset reference graph, and determining the mild cognitive impairment identification parameters according to the difference content. The method comprises the steps of directly obtaining a copy image of a target testee, and analyzing the copy image by a computer, so that the mild cognitive impairment recognition parameters are obtained according to difference content. Medical personnel can directly discern a plurality of target testees according to the identification parameter, and convenient, swift has promoted the popularization scope. Through setting up the classifier, can divide into not mild cognitive disorder, mild cognitive disorder earlier stage, mild cognitive disorder later stage etc. with the target person under test, classify target person under test, convenient, swift.
Based on one general inventive concept, embodiments of the present invention also provide a mild cognitive impairment recognition parameter determination apparatus.
Fig. 4 is a schematic structural diagram of a device for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention, referring to fig. 4, the device for determining mild cognitive impairment recognition parameters according to an embodiment of the present invention includes: a processor 41, and a memory 42 coupled to the processor.
The memory 42 is used for storing a computer program at least used for the method for measuring the mild cognitive impairment recognition parameter described in any one of the above embodiments; the processor 41 is used to invoke and execute computer programs in memory.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that the terms "first," "second," and the like in the description of the present invention are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present invention, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A method for determining mild cognitive impairment recognition parameters, comprising:
obtaining a copy image of a target testee based on a preset graph;
acquiring the difference content of the copying image and a preset reference graph according to the copying image, a preset processing rule and the preset reference graph;
and determining the mild cognitive impairment recognition parameters according to the difference content.
2. The method of claim 1, wherein the pre-set processing rules comprise:
obtaining a copy image with preset colors in the copy image based on color classification;
according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image;
and matching the starting points of the target image and the preset reference image based on a preset starting point searching method.
3. The method according to claim 2, wherein the obtaining the difference content between the copy image and the preset reference pattern according to the copy image, the preset processing rule and the preset reference pattern comprises:
extracting the pixel point coordinate of each preset color in the preset reference graph;
extracting subspace characteristics corresponding to the coordinates in the target image;
and acquiring the difference content between the copy image and the preset reference graph based on the pixel point coordinates and the subspace characteristics.
4. The method according to claim 3, wherein the obtaining of the difference content between the copy image and the preset reference pattern comprises:
classifying the subspace characteristics based on the pixel point coordinates, the subspace characteristics and a preset classifier;
the classifier includes: support vector machines or random forests.
5. A mild cognitive impairment recognition parameter measurement system, comprising: acquiring a template and a processing assembly; the acquisition template is connected with the processing assembly;
the acquisition template is used for acquiring a copy image of a target testee based on a preset graph;
the processing component is used for acquiring the difference content between the copying image and a preset reference graph according to the copying image, a preset processing rule and the preset reference graph; and determining the mild cognitive impairment recognition parameters according to the difference content.
6. The system of claim 5, wherein the preset processing rules in the processing component comprise: obtaining a copy image with preset colors in the copy image based on color classification; according to the copying image with the preset color and the graph proportion, adjusting the size of the copying image with the preset color to a target size, and obtaining a target image; and matching the starting points of the target image and the preset reference image based on a preset starting point searching method.
7. The system of claim 6, wherein the processing component is configured to: extracting the pixel point coordinate of each preset color in the preset reference graph; extracting subspace characteristics corresponding to the coordinates in the target image; and acquiring the difference content between the copy image and the preset reference graph based on the pixel point coordinates and the subspace characteristics.
8. The system of claim 7, wherein the processing component is configured to classify the subspace feature using the pixel coordinates, the subspace feature, and a preset classifier; the classifier includes: support vector machines or random forests.
9. The system according to any one of claims 5-8, wherein the acquisition template is a digitizer; and/or the processing component is a computer.
10. A mild cognitive impairment recognition parameter measurement device, comprising: a processor, and a memory coupled to the processor;
the memory is used for storing a computer program, and the computer program is at least used for executing the mild cognitive impairment recognition parameter determination method according to any one of claims 1 to 4;
the processor is used for calling and executing the computer program in the memory.
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