CN110911013A - Schizophrenia auxiliary diagnosis method based on painting and drawing - Google Patents
Schizophrenia auxiliary diagnosis method based on painting and drawing Download PDFInfo
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- CN110911013A CN110911013A CN201911261362.5A CN201911261362A CN110911013A CN 110911013 A CN110911013 A CN 110911013A CN 201911261362 A CN201911261362 A CN 201911261362A CN 110911013 A CN110911013 A CN 110911013A
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- electronic image
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/48—Extraction of image or video features by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
Abstract
The invention discloses a method for auxiliary diagnosis of schizophrenia based on painting and drawing, which comprises the following steps: s1, providing a basic painting tool as a reference; s2, scanning the original picture painted with good color to an electronic image with preset size; s3, analyzing the processed electronic image to obtain a plurality of preset colors, and analyzing the color components of the electronic image; s4, performing stroke analysis on the electronic image, including the stroke weight degree and the distance between the line segment stroke and the origin when starting; s5, generating a final painting tool result for distinguishing schizophrenia from healthy people. The data analysis of the invention is computerized in the whole process, professional technicians are not needed, and the authenticity and objectivity of the data are better than those of the prior art; expensive instruments are not needed, and the method is economical, practical, strong in operability, convenient to operate, simple to use and strong in popularization.
Description
Technical Field
The invention belongs to the technical field of computer image analysis, and particularly relates to a method for auxiliary diagnosis of schizophrenia based on painting and drawing.
Background
Currently, the diagnosis of schizophrenia mainly depends on various diagnostic criteria based on symptomatology, such as international classification of diseases (ICD-10), fifth edition of mental disorder diagnosis and statistics manual (DSM-5), and the like, while the method for auxiliary diagnosis of schizophrenia based on technical equipment is few, and neuropsychological tests (positive and negative symptom scale), eye tracking examination, electroencephalogram detection and the like are mainly available. In published domestic patent documents, only 10 patent documents are obtained by keywords of 'schizophrenia' and 'computer' retrieval, wherein CN109473170A discloses a system for diagnosing schizophrenia by using cognitive indexes, CN 109480864A discloses an automatic schizophrenia assessment system based on neurocognitive function and machine learning, and CN109671500A discloses an assistant diagnosis and classification method for schizophrenia based on electroencephalogram time-domain data. The clinical method for diagnosing schizophrenia has the following problems: the diagnostic standard based on symptomatology has strong subjectivity, lacks objective laboratory evidence to support diagnosis, and has differences in different diagnostic standards, resulting in deviation of consistency of clinical application; neuropsychological tests are also symptomatology-based assessments and require professional technicians to do the assessments; the eye tracking examination and the electroencephalogram detection need expensive instruments and professional technicians to operate and evaluate, and the sensitivity and the specificity of the eye tracking examination and the electroencephalogram detection are poor.
Disclosure of Invention
In view of the above, the present invention provides a method for aided diagnosis of schizophrenia based on painted painting, so as to solve the deficiencies in the prior art.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a method for aided diagnosis of schizophrenia based on painted painting is provided, which comprises the following steps:
s1, providing a basic painting tool as a reference;
s2, scanning the original picture painted with good color to an electronic image with preset size;
s3, analyzing the processed electronic image to obtain a plurality of preset colors, and analyzing the color components of the electronic image;
s4, performing stroke analysis on the electronic image, including the stroke weight degree and the distance between the line segment stroke and the origin when starting;
s5, generating a final painting tool result for distinguishing schizophrenia from healthy people.
In the method for aided diagnosis of schizophrenia based on painted painting, 64 colors are analyzed and separated from the processed electronic image by using a color histogram technology in step S3.
In the method for aided diagnosis of schizophrenia based on painted painting, in step S4, the electronic image is subjected to stroke analysis by using hough transform technology.
In the method for aided diagnosis of schizophrenia based on color painting, in step S5, a final color painting tool result is generated by using the deep structure learning model ResNet 18.
The technical scheme of the invention has the beneficial effects that:
comparing the pictures painted and drawn on the schizophrenia and the normal person by using a computer deep structure learning model, analyzing the difference between the two pictures, and identifying the schizophrenia and the normal person according to the difference;
the whole process of data analysis is computerized, professional technicians are not needed, and the authenticity and objectivity of the data are better than those of the prior art;
expensive instruments are not needed, and the method is economical, practical, strong in operability, convenient to operate, simple to use and strong in popularization.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic view of a basic painting implement of the present invention;
fig. 3 is a schematic reference diagram illustrating the principle of hough transform according to the present invention;
FIG. 4a is a schematic diagram of a conventional two-layer convolutional layer of ResNet in accordance with the present invention;
FIG. 4b is a diagram of the ResNet residual block structure according to the present invention;
FIG. 4c is a diagram of the original structure of ResNet18 according to the present invention;
fig. 4d is a schematic diagram of the metastatic learning process of the ResNet18 of the present invention to predict schizophrenia from health controls.
Detailed Description
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
Referring to fig. 1 and 2, the method for aided diagnosis of schizophrenia based on painted painting of the invention comprises the following steps:
s1, providing a basic painting tool (standardized painting picture and 12-color pencil) as a reference;
s2, scanning the color-coated original image of the patient into an electronic image with preset size, preferably, scanning the color-coated original image into an electronic image of 300 × 300 DPI.
And S3, analyzing the processed electronic image to obtain a plurality of preset colors, analyzing the color components of the electronic image, and preferably, analyzing the processed electronic image to obtain 64 colors by using a color histogram technology.
And S4, performing stroke analysis on the electronic image, including the degree of stroke weight and the distance between the line segment stroke and the origin when starting the pen, wherein in the preferred scheme, the stroke analysis is performed on the electronic image by using a Hough transform technology. Hough transform is a feature detection (feature extraction) widely used in image analysis (image analysis), computer vision (computer vision), and digital image processing (digital image processing). The hough transform is used to identify features in the found object, such as: a line. The algorithm flow is roughly as follows: given an object, the kind of shape to be distinguished, the algorithm performs a voting in the parameter space (parameter space) to determine the shape of the object, which is determined by the local maximum (local maximum) in the accumulation space (accumulator space). As shown in fig. 3, the following virtual codes may be used in the specific algorithm steps of the hough transform in the present application:
initialize H r θ 0
for each edge point in the image
forθ＝[θmintoθmax]Determining angular range
Calculating r value x cos theta + y sin theta
H [ r, theta ] + ═ 1 cumulative H value
Determining the value of (r, theta) when the value of (r, theta) is maximum
The detected line in the image is given by
Determining a monitoring line in the final image
S5, generating a final painting tool result for distinguishing schizophrenia from healthy people, and preferably, generating a final painting tool result by using a deep structure learning model ResNet 18. ResNet successfully trains a 152-deep neural network using a Residual Unit, and the structure of ResNet can speed up the training of ultra-deep neural networks very quickly. The ResNet18 network is an 18-layer network with weights, including convolutional layers and fully-connected layers. Fig. 4a, 4b, 4c and 4d are simplified diagrams illustrating a network structure model that the ResNet18 in this embodiment can adopt, where fig. 4a is a structure of a normal two-layer convolutional layer, fig. 4b is a structure of a residual block, a skip step is added between the first convolutional layer and the summation operation, fig. 4c is an original structure of ResNet18, fig. 4d is a transition learning process of ResNet18 for predicting schizophrenia from health control, and a red-dashed rectangle shows a modification compared with fig. 4 c.
The invention is a brand-new auxiliary diagnosis schizophrenia method, distinguish patients from normal persons from the perspective that the schizophrenia patients have visual perception disorder, from the beginning of drawing to the end of diagnosis, the whole process does not need the participation of professional personnel, thus ensuring the privacy of patients and providing a tool which can be screened for the people who do not want to visit the psychiatric department; the invention does not need expensive equipment, is convenient to operate, simple to use and strong in popularization; the image analysis of the invention is computerized in the whole process, and the data authenticity and objectivity are better than those of the prior art; the painting has a certain interest, can improve the participation of patients, and has a certain promotion effect on the rehabilitation of the schizophrenia patients, so the painting also has a certain promotion effect on the rehabilitation of the patients while assisting the diagnosis.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (4)
1. A method for aided diagnosis of schizophrenia based on painted painting, comprising:
s1, providing a basic painting tool as a reference;
s2, scanning the original picture painted with good color to an electronic image with preset size;
s3, analyzing the processed electronic image to obtain a plurality of preset colors, and analyzing the color components of the electronic image;
s4, performing stroke analysis on the electronic image, including the stroke weight degree and the distance between the line segment stroke and the origin when starting;
s5, generating a final painting tool result for distinguishing schizophrenia from healthy people.
2. The method for aided diagnosis of schizophrenia based on painted painting as claimed in claim 1, wherein in step S3, 64 colors are analyzed from the processed electronic image using a color histogram technique.
3. The method for aided diagnosis of schizophrenia based on painted painting as claimed in claim 1, wherein in step S4, the electronic image is subjected to stroke analysis using hough transform technique.
4. The method for aided diagnosis of schizophrenia based on color painting as claimed in claim 1, wherein in step S5, a final color painting tool result is generated using the depth structure learning model ResNet 18.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1060780A (en) * | 1991-07-26 | 1992-05-06 | 林肯 | Treating method for children's myopia using series of drawing |
| US20050079636A1 (en) * | 2001-09-25 | 2005-04-14 | White Keith D. | Method and apparatus for diagnosing schizophrenia and schizophrenia subtype |
| RU2408264C1 (en) * | 2009-06-18 | 2011-01-10 | Георгий Петрович Юрьев | Method of diagnosing psychophysical state of individual |
| US20110217679A1 (en) * | 2008-11-05 | 2011-09-08 | Carmel-Haifa University Economic Corporation Ltd. | Diagnosis method and system based on handwriting analysis |
| RU2497440C1 (en) * | 2012-07-18 | 2013-11-10 | Муниципальное казенное учреждение "Центр социальной помощи семье и детям" (МКУ "Центр Семья") | Method of estimating psychoemotional level and level of socialisation of disadapted children and teenagers in process of correction of psychoemotional disorders |
| JP5996144B1 (en) * | 2016-06-21 | 2016-09-21 | 有美 大久保 | Coloring Color Psychological Diagnosis System, Coloring Color Psychological Diagnosis Method, and Coloring Color Psychological Diagnosis Program |
-
2019
- 2019-12-10 CN CN201911261362.5A patent/CN110911013A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1060780A (en) * | 1991-07-26 | 1992-05-06 | 林肯 | Treating method for children's myopia using series of drawing |
| US20050079636A1 (en) * | 2001-09-25 | 2005-04-14 | White Keith D. | Method and apparatus for diagnosing schizophrenia and schizophrenia subtype |
| US20110217679A1 (en) * | 2008-11-05 | 2011-09-08 | Carmel-Haifa University Economic Corporation Ltd. | Diagnosis method and system based on handwriting analysis |
| RU2408264C1 (en) * | 2009-06-18 | 2011-01-10 | Георгий Петрович Юрьев | Method of diagnosing psychophysical state of individual |
| RU2497440C1 (en) * | 2012-07-18 | 2013-11-10 | Муниципальное казенное учреждение "Центр социальной помощи семье и детям" (МКУ "Центр Семья") | Method of estimating psychoemotional level and level of socialisation of disadapted children and teenagers in process of correction of psychoemotional disorders |
| JP5996144B1 (en) * | 2016-06-21 | 2016-09-21 | 有美 大久保 | Coloring Color Psychological Diagnosis System, Coloring Color Psychological Diagnosis Method, and Coloring Color Psychological Diagnosis Program |
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