阅读说明：本技术 一种鲜活离体组织脑区位置识别的方法及装置 (Method and device for recognizing brain region position of fresh in-vitro tissue ) 是由 吴小波 高永静 张志军 姜保春 李炜 于 2020-08-11 设计创作，主要内容包括：本发明公开一种鲜活离体脑组织脑区位置识别的方法,包括以下步骤：S1、根据鲜活离体脑组织所来自的实验对象,从脑图谱模型库中获取该实验对象所对应的脑组织图谱识别模型；S2、采集鲜活离体脑组织的脑片图像信号；S3、从脑片图像信号中提取出脑片图像信号中的特征值；S4、采用脑组织图谱识别模型对提取的特征值进行分析,识别出鲜活离体脑组织的脑片图像所对应的脑图谱,从而识别出脑片图像上各脑区。本发明公开一种鲜活离体脑组织脑区位置识别的装置,包括图像获取模块、图像采集模块、图像提取模块、图像识别模块。本发明可以实现从人工观察识别离体鲜活脑组织片上的脑区域结构到机器观察识别并标记的转换。(The invention discloses a method for identifying the position of a brain area of a fresh and alive isolated brain tissue, which comprises the following steps: s1, acquiring a brain tissue map recognition model corresponding to an experimental object from a brain map model library according to the experimental object from which the fresh and alive isolated brain tissue comes; s2, collecting a brain slice image signal of the fresh isolated brain tissue; s3, extracting characteristic values in the brain picture image signal from the brain picture image signal; and S4, analyzing the extracted characteristic values by adopting a brain tissue map recognition model, and recognizing a brain map corresponding to the brain slice image of the fresh isolated brain tissue, thereby recognizing each brain area on the brain slice image. The invention discloses a device for recognizing the brain region position of fresh and alive in-vitro brain tissue, which comprises an image acquisition module, an image extraction module and an image recognition module. The invention can realize the conversion from the manual observation and identification of the brain area structure on the isolated fresh brain tissue slice to the machine observation and identification and marking.)

1. A method for recognizing the position of a brain area of a fresh and alive isolated brain tissue is characterized by comprising the following steps:

s1, acquiring a brain tissue map recognition model corresponding to an experimental object from a brain map model library according to the experimental object from which the fresh and alive isolated brain tissue comes;

s2, collecting a brain slice image signal of the fresh isolated brain tissue;

s3, extracting characteristic values in the brain slice image signal from the brain slice image signal in the step S2;

and S4, analyzing the characteristic values extracted in the step S3 by adopting the brain tissue map identification model obtained in the step S1, and identifying a brain map corresponding to the brain slice image of the fresh isolated brain tissue, so as to identify each brain area on the brain slice image.

2. The method for identifying the position of the brain region of the fresh in-vitro tissue as claimed in claim 1, wherein the step S1 of obtaining the brain tissue map identification model corresponding to the subject specifically comprises the following steps:

s1-1, pre-establishing a brain atlas model base; the brain atlas model base comprises brain tissue atlas identification models corresponding to animals of different age groups and sexes;

s1-2, obtaining a brain tissue map recognition model corresponding to the age bracket of the experimental subject adopted by the fresh living isolated brain tissue.

3. The method for identifying the position of the brain region of the fresh in-vitro tissue as claimed in claim 2, wherein the pre-establishing of the brain map model library comprises the following steps: collecting fresh in-vitro brain tissue pictures of experimental objects with different sections to establish a brain map model library; respectively extracting characteristic values from brain slice samples under each section; and training the characteristic value under each section, and constructing a brain tissue map recognition model corresponding to the experimental object.

4. The method for identifying the position of the brain region of the fresh in-vitro tissue as claimed in claim 1, wherein the step S3 of extracting the feature value in the brain slice image signal specifically comprises the following steps: and (4) respectively capturing and identifying the pixel characteristics of each acquired picture in the brain picture image signal in the step (S2) and the background difference, determining the brain level of the fresh and separated brain tissue by combining the map comparison in the standard brain map model library, covering the brain map in the brain map model library on the acquired brain picture image of the fresh and separated brain tissue in a transparent mode, and displaying the name of the brain area at the corresponding position on the brain tissue.

5. The method for identifying the position of the brain region of the fresh excised tissue as claimed in claim 1, wherein the step of identifying the brain atlas corresponding to the brain slice image of the fresh excised brain tissue in the step of S4 comprises the following steps: inputting a target brain area of a user through a window command, and automatically displaying the corresponding brain area and boundary on the in vitro living brain tissue piece in a specific color after image acquisition and identification; when the tissue section is moved, the corresponding brain region identification portion is also moved.

6. The method for identifying the position of the brain region of the fresh living ex-vivo tissue as claimed in claim 1, wherein in the step S4, the brain map corresponding to the brain slice image of the fresh living ex-vivo tissue is identified and can be obtained by an "on-line learning" method, which specifically comprises the following steps: before the brain tissue atlas model of the experimental object is collected for identification, brain tissue images of in-vitro living brain tissue slices of the experimental object in different layers and sections are collected as samples to learn the electroencephalogram identification model of the experimental object on line; when collecting the brain tissue map signal sample of the experimental object, the researcher finishes the formulation action according to the program prompt, records all brain tissue maps of the experimental object in the execution process, marks the brain tissue maps according to the front and back sequence of the positions, and can set the interval of 100 micrometers according to the difference of the slice thickness.

7. The method for identifying the position of the brain region of the fresh isolated tissue of claim 1, wherein the step S4 further comprises performing area marking on each brain region on the brain image, wherein the area marking can be marked by one or more selected colors, numbers or acronyms.

8. A device for recognizing the position of a brain area of a fresh in-vitro tissue is characterized by comprising an image acquisition module, an image extraction module and an image recognition module; wherein the content of the first and second substances,

the image acquisition module is used for acquiring a brain tissue atlas identification model corresponding to the experimental object from a pre-constructed brain atlas model library;

the image acquisition module is used for acquiring brain tissue image signal samples when the brain images of the experimental object are in different slice layers;

the image extraction module is used for extracting characteristic values from brain tissue image signal samples acquired each time;

the image identification module is used for analyzing the characteristic value extracted by the extraction unit by the brain image identification model obtained by the image acquisition module, and identifying a standard brain atlas corresponding to the brain image signal.

9. The device for recognizing the position of the brain region of the fresh in-vitro tissue as claimed in claim 8, further comprising a filtering module, wherein the filtering module is used for denoising the brain tissue image signal acquired by the sample acquisition unit according to a preset acquisition frequency.

Technical Field

The invention belongs to the technical field of neuroscience research experiments, and particularly relates to a method and a device for recognizing the position of a brain region of a fresh and alive isolated tissue.

Background

The brain is the most complex organ in the body of an animal, is composed of neurons and other cells with large number, different forms and functions, and encodes activities such as learning memory, emotion, cognition, consciousness and the like through different neurons and neural networks. The research and understanding of the brain are the foundation for the treatment of neuropsychiatric diseases, the simulation of brain functions, the optimization of artificial intelligence and other works. With the emergence and mature application of color development methods such as immunohistochemical staining and fluorescence transgenic technology, people have known the brain region structure of various models of animals such as mice and rats in more detail, and draw and complete accurate and detailed standard maps of the animals.

Currently, either the nice-stained brain map of a classical subject or the electronic picture for displaying the intracerebral expression of a specific gene by transcribing a fluorescent reporter gene is a brain structure map which is obtained by fixing the brain tissue of the subject, slicing the brain tissue according to a specific thickness and drawing the brain structure map accordingly. When the brain map is adopted to identify and identify a specific brain region, a great challenge is often provided for researchers, and the related brain region can be accurately identified by carefully comparing the brain map by the researchers with abundant experience according to an actual brain tissue sheet. In addition, due to the difference of the age, weight, sex and the like of the used experimental subjects in the research, the brain area position has certain deviation, the fresh brain tissue is different from the fixed stained brain tissue section, is mainly grey from the image and is usually 200-400 microns thick; in addition, in actual operation, the neurons on the brain slice need to keep good activity, artificial cerebrospinal fluid needs to be perfused in real time, and the factors bring great difficulty to the identification of the specific brain area on the isolated fresh brain tissue slice, which causes serious troubles to brain science research, especially researchers during the research of the physiological functions of the cells in the specific brain area of the isolated fresh brain tissue slice. According to the traditional atlas identification method, time and labor are wasted, and large errors are often caused by differences of animal individuals and differences of positions of brain tissue slices.

Disclosure of Invention

The invention aims to provide a method and a device for identifying the position of a fresh and live in-vitro tissue brain area, which are applied to neuroscience research experiments such as electrophysiology, in-vitro brain slice ion imaging and the like, can identify and display the structure of a target brain area on the fresh and live brain tissue slice in real time, can improve the accuracy and the efficiency of the target brain area during research on the living brain tissue slice such as electrophysiology, ion imaging and the like, and solve the defects or the problems in the background technology.

In order to achieve the above object, an embodiment of the present invention provides a method for recognizing a brain region position of a fresh-living brain tissue, comprising the following steps:

s1, acquiring a brain tissue map recognition model corresponding to an experimental object from a brain map model library according to the experimental object from which the fresh and alive isolated brain tissue comes;

s2, collecting a brain slice image signal of the fresh isolated brain tissue;

s3, extracting characteristic values in the brain slice image signal from the brain slice image signal in the step S2;

and S4, analyzing the characteristic values extracted in the step S3 by adopting the brain tissue map identification model obtained in the step S1, and identifying a brain map corresponding to the brain slice image of the fresh isolated brain tissue, so as to identify each brain area on the brain slice image.

In a further embodiment of the present invention, the obtaining of the brain tissue mapping identification model corresponding to the experimental subject in step S1 specifically includes the following steps:

s1-1, pre-establishing a brain atlas model base; the brain atlas model base comprises brain tissue atlas identification models corresponding to animals of different age groups and sexes;

s1-2, obtaining a brain tissue map recognition model corresponding to the age bracket of the experimental subject adopted by the fresh living isolated brain tissue.

The pre-establishment of the brain atlas model base comprises the following steps: collecting fresh in-vitro brain tissue pictures of experimental objects with different sections to establish a brain map model library; respectively extracting characteristic values from brain slice samples under each section; and training the characteristic value under each section, and constructing a brain tissue map recognition model corresponding to the experimental object.

In a further embodiment of the present invention, the step S3 of extracting feature values from the brain slice image signal specifically includes the following steps: and (4) respectively capturing and identifying the pixel characteristics of each acquired picture in the brain picture image signal in the step (S2) and the background difference, determining the brain level of the fresh and separated brain tissue by combining the map comparison in the standard brain map model library, covering the brain map in the brain map model library on the acquired brain picture image of the fresh and separated brain tissue in a transparent mode, and displaying the name of the brain area at the corresponding position on the brain tissue.

In a further embodiment of the present invention, in the step S4, the identifying of the brain atlas corresponding to the brain slice image of the fresh-living brain tissue includes the following steps: inputting a target brain area of a user through a window command, and automatically displaying the corresponding brain area and boundary on the in vitro living brain tissue piece in a specific color after image acquisition and identification; when the tissue section is moved, the corresponding brain region identification portion is also moved.

In a further embodiment of the present invention, in the step S4, the brain atlas corresponding to the brain slice image of the freshly isolated brain tissue can be obtained by an "online learning" method, which specifically includes the following steps: before the brain tissue atlas model of the experimental object is collected for identification, brain tissue images of in-vitro living brain tissue slices of the experimental object in different layers and sections are collected as samples to learn the electroencephalogram identification model of the experimental object on line; when collecting the brain tissue map signal sample of the experimental object, the researcher finishes the formulation action according to the program prompt, records all brain tissue maps of the experimental object in the execution process, marks the brain tissue maps according to the front and back sequence of the positions, and can set the interval of 100 micrometers according to the difference of the slice thickness.

In a further embodiment of the present invention, the step S4 further includes performing area marking on each brain area on the brain image, wherein the area marking may be marked by one or more selected colors, numbers or english acronyms.

The embodiment of the invention also provides a device for recognizing the position of the brain region of the fresh and living isolated tissue, which is characterized by comprising an image acquisition module, an image extraction module and an image recognition module; wherein the content of the first and second substances,

the image acquisition module is used for acquiring a brain tissue atlas identification model corresponding to the experimental object from a pre-constructed brain atlas model library;

the image acquisition module is used for acquiring brain tissue image signal samples when the brain images of the experimental object are in different slice layers;

the image extraction module is used for extracting characteristic values from brain tissue image signal samples acquired each time;

the image identification module is used for analyzing the characteristic value extracted by the extraction unit by the brain image identification model obtained by the image acquisition module, and identifying a standard brain atlas corresponding to the brain image signal.

In a further embodiment of the present invention, the device for recognizing the position of the brain region of the fresh living in-vitro tissue further includes a filtering module, and the filtering module is configured to perform noise reduction on the brain tissue image signal acquired by the sample acquisition unit according to a preset acquisition frequency.

The technical scheme of the invention has the following beneficial effects:

(1) the method is characterized in that computer software is combined with an image set of a fresh isolated brain tissue slice of an experimental object acquired by real-time images, an image recognition technology based on deep learning is utilized to be introduced into the field of neurobiology research, each image is subjected to feature recognition and marking and is compared with a standard brain map, and finally, the combination of the software and the brain map is realized, and the structure of a designated brain region and the marking and position display of a nucleus on the fresh isolated brain tissue slice of the experimental object are recognized in real time.

(2) The method and the device for identifying the isolated brain slice region structure can realize the conversion from the manual observation and identification of the brain region structure on the isolated fresh brain tissue slice to the machine observation and identification and marking, can obtain the brain slice image identification model of the experimental object, further analyze and identify the brain image acquired by the brain image model of the experimental object, and accurately position the brain region structure position on the isolated fresh brain slice of the experimental object, thereby avoiding the difference between samples and obviously improving the accurate identification of the brain region structure on the isolated fresh brain tissue.

(3) According to the invention, the brain tissue map recognition model is adopted to recognize the structure region on the brain tissue picture of the experimental object, so that the difference between individuals can be avoided, and the accuracy of the brain tissue region structure recognition is improved. The method has important practical significance for further researching the cell physiological function in the marked brain area, and can be applied to the research of brain map construction, in-vitro electrophysiological recording, in-vitro brain slice calcium ion imaging and the like, so that the brain science research is more accurate and efficient.

Drawings

FIG. 1 is a flow chart of the operation of the method for identifying the location of a brain region of fresh in vitro brain tissue according to the present invention;

fig. 2 is a schematic structural diagram of the device for identifying the position of the brain region of the fresh and alive isolated brain tissue.

Description of reference numerals: 1. an image acquisition module; 2. an image acquisition module; 3. an image extraction module; 4. and an image identification module.

Detailed Description

In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.

As shown in fig. 1, a method for identifying the position of a brain region of a fresh and alive isolated brain tissue comprises the following steps:

s1, according to the experimental object from which the fresh and alive isolated brain tissue comes, obtaining the brain tissue map recognition model corresponding to the experimental object from the brain map model library.

S1-1, pre-establishing a brain atlas model base; the brain atlas model base comprises brain tissue atlas identification models corresponding to animals of different age groups and sexes;

s1-2, obtaining a brain tissue map recognition model corresponding to the age bracket of the experimental subject adopted by the fresh living isolated brain tissue.

The pre-establishment of the brain atlas model base comprises the following steps: collecting fresh in-vitro brain tissue pictures of experimental objects with different sections to establish a brain map model library; respectively extracting characteristic values from brain slice samples under each section; and training the characteristic value under each section, and constructing a brain tissue map recognition model corresponding to the experimental object.

And S2, acquiring a brain slice image signal of the fresh and alive brain tissue.

S3, extracting characteristic values in the brain slice image signal from the brain slice image signal in the step S2;

specifically, the value and the background difference of each pixel point in the brain slice image signal in step S2 are respectively captured and recognized for each acquired picture pixel feature, and the map comparison in the standard brain map model library is combined to determine the brain level of the fresh living separated brain tissue, and the brain map in the brain map model library is covered on the acquired brain slice image of the fresh living separated brain tissue in a transparent manner to display the name of the brain area at the corresponding position on the brain tissue.

And S4, analyzing the characteristic values extracted in the step S3 by adopting the brain tissue map identification model obtained in the step S1, and identifying a brain map corresponding to the brain slice image of the fresh isolated brain tissue, so as to identify each brain area on the brain slice image. And carrying out region marking on each brain region on the brain picture image, wherein the region marking can be marked by one or more selected colors, numbers or English abbreviations.

Specifically, identifying a brain atlas corresponding to a brain slice image of a fresh, isolated brain tissue comprises the following processes: inputting a target brain area of a user through a window command, and automatically displaying the corresponding brain area and boundary on the in vitro living brain tissue piece in a specific color after image acquisition and identification; when the tissue section is moved, the corresponding brain region identification portion is also moved.

Specifically, the brain atlas corresponding to the brain slice image of the fresh and alive brain tissue can be obtained in an online learning manner, and the method specifically comprises the following steps: before the brain tissue atlas model of the experimental object is collected for identification, brain tissue images of in-vitro living brain tissue slices of the experimental object in different layers and sections are collected as samples to learn the electroencephalogram identification model of the experimental object on line; when collecting the brain tissue map signal sample of the experimental object, the researcher finishes the formulation action according to the program prompt, records all brain tissue maps of the experimental object in the execution process, marks the brain tissue maps according to the front and back sequence of the positions, and can set the interval of 100 micrometers according to the difference of the slice thickness.

As shown in fig. 2, a device for recognizing a brain region position of a living isolated tissue comprises an image acquisition module, an image extraction module and an image recognition module; wherein the content of the first and second substances,

the image acquisition module 1 is used for acquiring a brain tissue atlas identification model corresponding to an experimental object from a pre-constructed brain atlas model library;

the image acquisition module 2 is used for acquiring brain tissue image signal samples when the brain images of the experimental object are in different slice layers;

the image extraction module 3 is used for extracting characteristic values from brain tissue image signal samples acquired each time respectively;

the image recognition module 4 is configured to analyze the feature value extracted by the extraction unit with the brain image recognition model obtained by the image acquisition module, and recognize a standard brain atlas corresponding to the brain image signal.

Preferably, the device for recognizing the brain region position of the fresh and alive isolated tissue further comprises a filtering module, wherein the filtering module is used for denoising brain tissue image signals acquired by the sample acquisition unit according to a preset acquisition frequency.

While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.