CN116269155B - Image diagnosis method, image diagnosis device, and image diagnosis program - Google Patents
Image diagnosis method, image diagnosis device, and image diagnosis program Download PDFInfo
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- A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
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Abstract
The invention relates to the technical field of image processing, and provides an image diagnosis method, an image diagnosis device and an image diagnosis program, wherein the method comprises the following steps: planning and acquiring a focus peeping route according to focus position information, sending out an endoscope image acquisition permission when the front end of an endoscope is close to the focus position, acquiring an endoscope image, randomly capturing a first processing point, and denoising to acquire a first denoising processing point; traversing to obtain a plurality of noise reduction processing points; collecting tunnel muscle tremor data; the method comprises the steps of taking a plurality of noise reduction processing points as basic data, taking duct muscle tremor data as correction data, synthesizing noise reduction processing images, outputting and displaying, solving the technical problems of low adaptation degree of image noise reduction and application scene of an endoscope and poor image quality of synchronous display, realizing the technical effects of using the muscle tremor data for image noise reduction processing according to the application scene of the endoscope, comprehensively reducing noise in digital images of the endoscope, protecting image details, improving the image quality of synchronous display and maintaining the credibility of the endoscope images.
Description
Technical Field
The present invention relates to the field of image processing, and more particularly, to an image diagnosis method, an image diagnosis apparatus, and an image diagnosis program.
Background
The endoscope is composed of a bendable part, a light source and a group of lenses, is widely used in departments such as otorhinolaryngology, urology surgery, ophthalmology, orthopaedics, neurosurgery, medical and aesthetic plastic, has certain specificity in application scenes of the endoscope, is affected by use environment, inevitably has some noise in an endoscope image, seriously reduces image quality, damages image details and reduces the credibility of the endoscope image.
The objective of endoscopic image noise reduction is to reduce interference signals during endoscopy, improve image quality, and generally reduce noise by filtering, downsampling, weighted averaging, etc. using digital signal processing techniques, although different types of endoscopes may require different noise reduction methods and strategies.
In summary, the prior art has the technical problems of low image noise reduction and application scene adaptation of the endoscope, and poor image quality of synchronous display.
Disclosure of Invention
The application aims to solve the technical problems of low adaptation degree of image noise reduction and application scene of an endoscope and poor quality of synchronously displayed images in the prior art by providing an image diagnosis method, an image diagnosis device and an image diagnosis program.
In view of the above, embodiments of the present application provide an image diagnosis method, an image diagnosis apparatus, and an image diagnosis program.
In a first aspect of the present disclosure, an image diagnosis method is provided, where the method is applied to an image diagnosis apparatus, and the image diagnosis apparatus is communicatively connected to an information interaction management platform and a peripheral display screen, and the method includes: after the endoscopic observation instruction is led into the information interaction management platform, planning a route by referring to focus position information to obtain a focus peeping route; the front end of the endoscope is close to the focus position according to the focus peeping route, and after the bending part of the endoscope is overlapped with the focus peeping route, the acquisition permission of the endoscope image is sent; after receiving the endoscope image acquisition permission, acquiring an endoscope image; randomly capturing the endoscope image to obtain a first processing point, and performing noise reduction processing on the first processing point to obtain a first noise reduction processing point; traversing the endoscope image to obtain a plurality of noise reduction processing points; collecting tunnel muscle tremor data at the curved portion of the endoscope; and taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on the peripheral display screen.
In another aspect of the present disclosure, there is provided an image diagnosis apparatus, wherein the apparatus includes: the route planning module is used for carrying out route planning by referring to focus position information after the endoscopic observation instruction is led into the information interaction management platform, so as to obtain a focus peeping route; the image acquisition permission issuing module is used for issuing an endoscope image acquisition permission after the endoscope bending part is overlapped with the focus peeping route according to the focus peeping route and is close to the focus position; the endoscope image acquisition module is used for acquiring and acquiring an endoscope image after receiving the endoscope image acquisition permission; the first noise reduction processing module is used for randomly capturing the first processing point in the endoscope image, performing noise reduction processing on the first processing point and obtaining a first noise reduction processing point; the whole noise reduction processing module is used for traversing the endoscope image and acquiring a plurality of noise reduction processing points; the tunnel muscle tremor acquisition module is used for acquiring tunnel muscle tremor data at the bending part of the endoscope; the noise reduction processing image output module is used for taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on a peripheral display screen.
In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of the first aspects when the program is executed.
In a fourth aspect, the present application provides an image diagnostic program comprising a computer program and/or instructions which, when executed by a processor, implement the steps of the method of any of the first aspects.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
after the endoscopic observation instruction is led into the information interaction management platform, the route planning is carried out by referring to the focus position information, and the focus peeping route is obtained; the front end of the endoscope sends out an endoscope image acquisition permission according to a focus peeping route and near a focus position, acquires an endoscope image, randomly captures the endoscope image to obtain a first processing point, performs noise reduction processing, and obtains the first noise reduction processing point; traversing the endoscope image to obtain a plurality of noise reduction processing points; collecting tunnel muscle tremor data at the bending part of the endoscope; the method has the advantages that the plurality of noise reduction processing points are used as basic data, the pore canal muscle tremor data is used as correction data, noise reduction processing images are synthesized, synchronous display and output are achieved on the peripheral display screen, the muscle tremor data are used for image noise reduction processing according to the application scene of an endoscope, noise in the digital image of the endoscope is comprehensively reduced, details of the image are protected, the quality of synchronously displayed images is improved, and the credibility of the image of the endoscope is maintained.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
FIG. 1 is a schematic diagram of a possible flow chart of an image diagnosis method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a possible flow of a marker center point passing through in an image diagnosis method according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of a possible process for obtaining the first median substitution data in the image diagnosis method according to the embodiment of the present application;
fig. 4 is a schematic diagram of a possible structure of an image diagnosis apparatus according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Reference numerals illustrate: the system comprises a route planning module 100, an image acquisition permission issuing module 200, an endoscope image acquisition module 300, a first noise reduction processing module 400, an overall noise reduction processing module 500, a tunnel muscle tremor acquisition module 600, a noise reduction processing image output module 700, an electronic device 30, a memory 301, a processor 302, a communication interface 303 and a bus architecture 304.
Detailed Description
The embodiment of the application provides an image diagnosis method, an image diagnosis device and an image diagnosis program, solves the technical problems of low adaptation degree of image noise reduction and application scene of an endoscope and poor image quality of synchronous display, and achieves the technical effects of using muscle tremor data for image noise reduction according to the application scene of the endoscope, comprehensively reducing noise in digital images of the endoscope, protecting image details, improving the image quality of synchronous display and maintaining the credibility of the images of the endoscope.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides an image diagnosis method, where the method is applied to an image diagnosis device, and the image diagnosis device is communicatively connected with an information interaction management platform and a peripheral display screen, and the method includes:
s10: after the endoscopic observation instruction is led into the information interaction management platform, planning a route by referring to focus position information to obtain a focus peeping route;
step S10 includes the steps of:
s11: reading a user diagnosis record;
s12: acquiring focus position information through the user diagnosis record;
s13: and taking the oral cavity as a starting point of route planning, taking the focus position as an ending point of route planning, carrying out route planning, and synthesizing a focus peeping route.
Specifically, the image diagnosis device is in communication connection with the information interaction management platform and the peripheral display screen, the communication connection is simply through signal transmission interaction, a communication network is formed between the image diagnosis device and the information interaction management platform as well as between the image diagnosis device and the peripheral display screen, and hardware support is provided for endoscope image noise reduction;
the doctor logs in the internal information interaction management platform of hospital, and the doctor who possesses endoscope use authority sends out the endoscopic observation instruction, will after the endoscopic observation instruction is imported the information interaction management platform, consults focus position information and carries out route planning, acquires focus peeping route, specifically includes: reading a user visit record (the user visit record may be an electronic medical record of the user); acquiring focus position information through the illness state record in the user diagnosis record; the oral cavity is used as a starting point of route planning, the focus position is used as an ending point of route planning, route planning is carried out according to natural pore channels of a human body (the oral cavity and anus belong to the natural pore channels of the human body), a focus peeping route is synthesized, and support is provided for reducing mucous membrane damage caused by endoscope peeping.
Step S13 includes the steps of:
s131: acquiring user basic data;
s132: synthesizing a natural pore distribution map of the user according to the user basic data and the natural pore distribution rule of the human body;
s133: marking the positions of the oral cavity and the focus on the natural duct distribution diagram of the user to generate a focus peeping route.
Specifically, the method uses the oral cavity as a starting point of route planning, uses the focus position as an ending point of route planning, performs route planning, synthesizes focus peeping routes, and specifically comprises the following steps: acquiring user basic data, wherein the user basic data comprise height, weight and the like; according to the natural pore distribution rule of the human body (the natural pore distribution rule is a human body standard pore diagram, the human body standard pore diagram can be filtered and screened out from a human body standard viscera diagram), scaling the human body standard pore diagram according to the user basic data (scaling can be equal-proportion elongation according to the height of the user), and then obtaining a user natural pore distribution diagram; marking the positions of the oral cavity and the focus on the distribution map of the natural pore canal of the user, taking the oral cavity as a starting point of route planning, taking the position of the focus as an end point of route planning, and generating a focus peeping route, wherein the focus peeping route comprises a plurality of positioning points, the positioning points are positioned at the center of the pore canal of the natural pore canal, and support is provided for furthest reducing the damage of the mucous membrane caused by peeping of an endoscope.
S20: the front end of the endoscope is close to the focus position according to the focus peeping route, and after the bending part of the endoscope is overlapped with the focus peeping route, the acquisition permission of the endoscope image is sent;
as shown in fig. 2, step S20 includes the steps of:
s21: marking a central point at the front end of the endoscope to obtain a marked central point;
s22: the marking center point drives the bending part of the endoscope to pass through a natural duct of a user according to the focus peeping route;
s23: and the mark center point passes through to the focus position, and the endoscope bending part is overlapped with the focus peeping route.
Specifically, the endoscope front end is close to the focus position according to the focus peeping route, and the endoscope bending part is overlapped with the focus peeping route, specifically comprising: marking a central point at the front end of the endoscope to obtain a marked central point; the marking center point passes through according to the focus peeping route to drive the bending part of the endoscope to pass through the natural duct of the user, and the bending part of the endoscope is centrosymmetric, so that if the marking center point passes through according to the focus peeping route, the marking center point overlaps with the center point of the natural duct, and in theory, the damage degree of the mucous membrane in the endoscope passing process is the lowest; and when the mark center point passes through to the focus position, the endoscope bending part is overlapped with the focus peeping route, and after the endoscope bending part is determined to be overlapped with the focus peeping route, an endoscope image acquisition permission is sent out, wherein the endoscope image acquisition permission is used for starting an image sensor (an image sensor is arranged at the front end of the endoscope, namely a lens device) at the front end of the endoscope, and a basis is provided for carrying out endoscope image acquisition on the focus position by using the image sensor subsequently.
S30: after receiving the endoscope image acquisition permission, acquiring an endoscope image;
s40: randomly capturing the endoscope image to obtain a first processing point, and performing noise reduction processing on the first processing point to obtain a first noise reduction processing point;
step S40 includes the steps of:
s41: performing gray scale processing on the endoscope image to obtain a pixel gray scale image;
s42: randomly capturing the endoscope image to obtain a first processing point, marking the first processing point in the pixel gray level image, and obtaining a first gray level processing point;
s43: acquiring a first neighborhood set corresponding to the first gray processing point;
s44: and carrying out noise reduction processing on the first processing point through the first neighborhood set to obtain a first noise reduction processing point.
Specifically, after receiving the endoscope image acquisition permission, starting an image sensor at the front end of the endoscope, and acquiring an endoscope image from the focus position; randomly capturing the endoscope image to obtain a first processing point, and performing noise reduction processing on the first processing point to obtain a first noise reduction processing point, wherein the method specifically comprises the following steps of: according to a gray scale processing formula: gray= (r+g+b)/3 (average method), where GRAY is a pixel GRAY value, R is a red image, G is a green image, B is a blue image (red, green, blue are three primary colors, and an endoscope image can be obtained after overlapping the red image, the green image, and the blue image), and GRAY processing is performed on the endoscope image to obtain a pixel GRAY image; randomly capturing in the endoscope image (randomly capturing is the prior art, if random capturing records exist in the randomly captured points, namely discarding capturing results) to obtain first processing points, marking the first processing points in the pixel gray level image, and obtaining first gray level processing points; acquiring a first neighborhood set corresponding to the first gray processing point, wherein the elements of the first neighborhood set are pixel points in contact with the first gray processing point; and carrying out noise reduction processing on the first processing points through the first neighborhood set to obtain first noise reduction processing points, and providing technical support for reducing noise in the digital image of the endoscope.
Step S44 includes the steps of:
s441: performing differential operation at a first processing point according to a median theorem based on the first neighborhood set to obtain first median substitution data;
s442: based on the first neighborhood set, gray difference value calculation is carried out, and a first gray difference value set is obtained, wherein the first gray difference value set is arranged from large to small according to the difference of pixel gray values;
s443: and referring to the first gray level difference value set, performing median substitution on the first processing point by using first median substitution data to obtain a first noise reduction processing point.
Specifically, the denoising processing is performed on the first processing point through the first neighborhood set, so as to obtain a first denoising processing point, which specifically includes: performing differential operation at a first processing point according to a median theorem based on the first neighborhood set to obtain first median substitution data; performing gray difference calculation (gray difference calculation: the gray value of the pixel point of each point in the first neighborhood set minus the gray value of the pixel point of the first processing point) based on the first neighborhood set to obtain a first gray difference set, wherein the first gray difference set is arranged according to the difference of the pixel gray values from large to small; and referring to the first gray level difference value set, performing median substitution (median substitution: substituting that the gray level value difference of the contacted surrounding pixel points is larger for substituting that the gray level value difference of the contacted surrounding pixel points is closer) on the first processing point by using the first median substitution data to obtain a first noise reduction processing point, and due to the continuity of the endoscope image, the contrast between the pixel points can be improved by a median substitution mode, so that the definition of the endoscope image is improved.
As shown in fig. 3, step S441 includes the steps of:
s441-1: based on the first neighborhood set, grouping to obtain a first point position set and a first symmetrical point position set;
s441-2: performing differential operation in groups according to the first point bit set and the first symmetrical point bit set to obtain a first median computing data set;
s441-3: and calculating the mean value of the first median calculation data set, and recording the mean value of the first median calculation data set as first median substitution data.
Specifically, based on the first neighborhood set, performing differential operation at a first processing point according to a median theorem to obtain first median substitution data, which specifically includes: based on the first neighborhood set, acquiring a first point bit set and a first symmetrical point bit set in a grouping way, if a first processing point is taken as an origin, on the endoscope image, the pixel points in the first point bit set and the pixel points in the first symmetrical point bit set are origin symmetry (for example, origin symmetry points of coordinate points (1, 1) are coordinate points (-1, -1)); median theorem: [ f (b) -f (a) ]/(b-a) =f (epsilon) ', wherein b is any point in a first point bit set, a is a pixel point symmetrical to the origin of b in the first symmetry point bit set, epsilon (a, b) is performed according to the first point bit set and the first symmetry point bit set, differential operation is performed in median positioning by grouping substitution, and f (epsilon)' is first median calculation data, so that a first median calculation data set is obtained; and calculating the mean value of the first median calculated data set, and marking the mean value of the first median calculated data set as first median substituted data to provide a data basis for subsequent processing.
S50: traversing the endoscope image to obtain a plurality of noise reduction processing points;
s60: collecting tunnel muscle tremor data at the curved portion of the endoscope;
s70: and taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on the peripheral display screen.
Specifically, performing a noise reduction processing operation on a plurality of pixel points on the endoscope image in a traversing manner to obtain a plurality of noise reduction processing points; collecting muscle movements around a pore canal around a needle electrode by utilizing the needle electrode, synthesizing an electromyogram (the electromyogram is periodic), intercepting an electromyogram periodic chart with highest occurrence frequency in the electromyogram (the electromyogram periodic chart is an electromyogram with a single period), and carrying out data expression on the electromyogram periodic chart to obtain pore canal muscle tremor data (generally, pore canal muscle tremor is 4-8 times per second); and taking the plurality of noise reduction processing points as basic data, taking the duct muscle tremor data as correction data (due to the fact that the muscle tremors, the image sensor and focus position information have tiny relative movement, so that tiny displacement can occur in an acquired image, correction is performed on the tiny displacement according to the duct muscle tremor data), synthesizing a noise reduction processing image, synchronously displaying and outputting the noise reduction processing image on the peripheral display screen, reducing noise in an endoscope digital image, and providing support for maintaining the reliability of the display output image of the peripheral display screen.
In summary, the image diagnosis method, the image diagnosis apparatus, and the image diagnosis program provided in the embodiments of the present application have the following technical effects:
1. after the endoscopic observation instruction is led into the information interaction management platform, route planning is performed by referring to focus position information, a focus peeping route is obtained, the front end of the endoscope is close to the focus position, an endoscopic image acquisition permission is sent, an endoscopic image is acquired and obtained, a first processing point is randomly captured, noise reduction processing is performed, and a first noise reduction processing point is obtained; traversing the endoscope image to obtain a plurality of noise reduction processing points; collecting tunnel muscle tremor data at the bending part of the endoscope; the method and the device have the technical effects that the muscle tremor data are used for image noise reduction processing according to the application scene of an endoscope, noise in digital images of the endoscope is comprehensively reduced, image details are protected, the synchronously displayed image quality is improved, and the credibility of the endoscope images is maintained.
2. Because the first neighborhood set is adopted, differential operation is carried out at a first processing point according to a median theorem, and first median substitution data is obtained; based on the first neighborhood set, gray difference value calculation is carried out, and a first gray difference value set is obtained; and referring to the first gray level difference value set, performing median substitution on the first processing point by using first median substitution data to obtain a first noise reduction processing point, and improving the contrast between pixel points by a median substitution mode due to continuity of the endoscopic image so as to improve the definition of the endoscopic image.
Example two
Based on the same inventive concept as the image diagnosis method in the foregoing embodiments, as shown in fig. 4, an embodiment of the present application provides an image diagnosis apparatus, wherein the apparatus includes:
the route planning module 100 is configured to perform route planning with reference to focus position information after the endoscopic observation instruction is led into the information interaction management platform, so as to obtain a focus peeping route;
an image acquisition permission issuing module 200, configured to issue an endoscope image acquisition permission after the endoscope bending portion overlaps with the focus peeping route according to the focus peeping route and the focus position is close to the focus position;
an endoscope image acquisition module 300, configured to acquire an endoscope image after receiving the endoscope image acquisition permission;
the first noise reduction processing module 400 is configured to randomly capture a first processing point in the endoscope image, perform noise reduction processing on the first processing point, and obtain a first noise reduction processing point;
the overall noise reduction processing module 500 is used for traversing the endoscope image and acquiring a plurality of noise reduction processing points;
the tunnel muscle tremor acquisition module 600 is used for acquiring tunnel muscle tremor data at the bending part of the endoscope;
the noise reduction processing image output module 700 is configured to take the plurality of noise reduction processing points as basic data, take the tunnel muscle tremor data as correction data, synthesize a noise reduction processing image, and display and output synchronously on a peripheral display screen.
Further, the apparatus includes:
the diagnosis record reading module is used for reading the diagnosis record of the user;
the focus position information acquisition module is used for acquiring focus position information through the user treatment record;
the focus peeping route synthesis module is used for taking the oral cavity as a starting point of route planning, taking the focus position as an end point of route planning, carrying out route planning and synthesizing a focus peeping route.
Further, the apparatus includes:
the user basic data acquisition module is used for acquiring user basic data;
the user natural pore canal distribution diagram synthesis module is used for synthesizing a user natural pore canal distribution diagram according to the natural pore canal distribution rule of a human body and the user basic data;
the focus peeping route generation module is used for marking the positions of the oral cavity and the focus on the natural duct distribution diagram of the user to generate a focus peeping route.
Further, the apparatus includes:
the central point marking module is used for marking the central point at the front end of the endoscope and obtaining a marked central point;
the endoscope passing module is used for driving the bending part of the endoscope to pass through a natural duct of a user according to the focus peeping route by the marking center point;
the marking center point passing module is used for passing to the focus position at the marking center point, and the bending part of the endoscope is overlapped with the focus peeping route.
Further, the apparatus includes:
the gray processing module is used for carrying out gray processing on the endoscope image to obtain a pixel gray image;
the random capturing module is used for randomly capturing a first processing point in the endoscope image, marking the first processing point in the pixel gray level image and obtaining a first gray level processing point;
the first neighborhood set acquisition module is used for acquiring a first neighborhood set corresponding to the first gray processing point;
the noise reduction processing module is used for carrying out noise reduction processing on the first processing points through the first neighborhood set to obtain first noise reduction processing points.
Further, the apparatus includes:
the differential operation module is used for carrying out differential operation on the first processing point according to the median theorem based on the first neighborhood set to obtain first median substitution data;
the gray difference value calculation module is used for carrying out gray difference value calculation based on the first neighborhood set to obtain a first gray difference value set, and the first gray difference value set is arranged from large to small according to the difference of pixel gray values;
and the median substitution module is used for referring to the first gray level difference value set, carrying out median substitution on the first processing point by using first median substitution data, and obtaining a first noise reduction processing point.
Further, the apparatus includes:
the set grouping module is used for grouping and acquiring a first point bit set and a first symmetry point bit set based on the first neighborhood set;
the first median computing data set acquisition module is used for carrying out differential operation on the first point bit set and the first symmetrical point bit set in groups to acquire a first median computing data set;
and the average value calculation module is used for calculating the average value of the first median calculation data set and recording the average value of the first median calculation data set as first median substitution data.
The electronic device of the present application is described below with reference to figure 5,
based on the same inventive concept as the image diagnosis method in the foregoing embodiments, the present application also provides an image diagnosis apparatus including: a processor coupled to a memory for storing a program that, when executed by the processor, causes an apparatus to perform the method of any of the embodiments.
The electronic device 30 includes: a processor 302, a communication interface 303, a memory 301. Optionally, the electronic device 30 may also include a bus architecture 304. Wherein the communication interface 303, the processor 302 and the memory 301 may be interconnected by a bus architecture 304; the bus architecture 304 may be an Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into address buses, data buses, control buses, and the like. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.
Processor 302 may be a CPU, microprocessor, ASIC, or one or more integrated circuits for controlling the execution of the programs of the present application.
The communication interface 303 uses any transceiver-like means for communicating with other devices or communication networks, such as ethernet, radio access network (radio access network, RAN), wireless local area network (wireless local area networks, WLAN), wired access network, etc.
The memory 301 may be, but is not limited to, ROM or other type of static storage device that may store static information and instructions, RAM or other type of dynamic storage device that may store information and instructions, or may be an EEPROM (electrically erasable Programmable read-only memory), a compact disc-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through bus architecture 304. The memory may also be integrated with the processor.
The memory 301 is used for storing computer-executable instructions for executing the embodiments of the present application, and is controlled by the processor 302 to execute the instructions. The processor 302 is configured to execute computer-executable instructions stored in the memory 301, thereby implementing the image diagnosis method provided in the above-described embodiment of the present application.
Alternatively, the computer-executable instructions in the present application may be referred to as application code, which is not specifically limited in this application.
The application provides an image diagnosis method, wherein the method is applied to an image diagnosis device, the image diagnosis device is in communication connection with an information interaction management platform and a peripheral display screen, and the method comprises the following steps: after the endoscopic observation instruction is led into the information interaction management platform, planning a route by referring to focus position information to obtain a focus peeping route; the front end of the endoscope is close to the focus position according to the focus peeping route, and after the bending part of the endoscope is overlapped with the focus peeping route, the acquisition permission of the endoscope image is sent; after receiving the endoscope image acquisition permission, acquiring an endoscope image; randomly capturing the endoscope image to obtain a first processing point, and performing noise reduction processing on the first processing point to obtain a first noise reduction processing point; traversing the endoscope image to obtain a plurality of noise reduction processing points; collecting tunnel muscle tremor data at the curved portion of the endoscope; and taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on the peripheral display screen.
Those of ordinary skill in the art will appreciate that: the various numbers of first, second, etc. referred to in this application are merely for ease of description and are not intended to limit the scope of this application nor to indicate any order. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any one," or the like, refers to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one of a, b, or c (species ) may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more servers, data centers, etc. that can be integrated with the available medium. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SolidStateDisk, SSD)), etc.
The various illustrative logical units and circuits described herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the general purpose processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the present application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software elements may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In an example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may reside in a terminal. In the alternative, the processor and the storage medium may reside in different components in a terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
Although the present application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and drawings are merely exemplary illustrations of the present application as defined in the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the present application. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to include such modifications and variations.
Claims (9)
1. An image diagnosis method, characterized in that the method is applied to an image diagnosis device, the image diagnosis device is in communication connection with an information interaction management platform and a peripheral display screen, and the method comprises the following steps:
after the endoscopic observation instruction is led into the information interaction management platform, planning a route by referring to focus position information to obtain a focus peeping route;
the front end of the endoscope is close to the focus position according to the focus peeping route, and after the bending part of the endoscope is overlapped with the focus peeping route, the acquisition permission of the endoscope image is sent;
after receiving the endoscope image acquisition permission, acquiring an endoscope image;
randomly capturing the endoscope image to obtain a first processing point, and performing noise reduction processing on the first processing point to obtain a first noise reduction processing point;
traversing the endoscope image to obtain a plurality of noise reduction processing points;
collecting tunnel muscle tremor data at the curved portion of the endoscope;
and taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on the peripheral display screen.
2. The method of claim 1, wherein route planning is performed with reference to lesion location information to obtain a lesion peeping route, the method comprising:
reading a user diagnosis record;
acquiring focus position information through the user diagnosis record;
and taking the oral cavity as a starting point of route planning, taking the focus position as an ending point of route planning, carrying out route planning, and synthesizing a focus peeping route.
3. The method of claim 2, wherein route planning is performed with the mouth as a starting point and the lesion location as an ending point of the route planning, and wherein the method comprises:
acquiring user basic data;
synthesizing a natural pore distribution map of the user according to the user basic data and the natural pore distribution rule of the human body;
marking the positions of the oral cavity and the focus on the natural duct distribution diagram of the user to generate a focus peeping route.
4. The method of claim 1, wherein the endoscope front end follows the lesion peep path, adjacent to the lesion site, and wherein the endoscope bend overlaps the lesion peep path, the method comprising:
marking a central point at the front end of the endoscope to obtain a marked central point;
the marking center point drives the bending part of the endoscope to pass through a natural duct of a user according to the focus peeping route;
and the mark center point passes through to the focus position, and the endoscope bending part is overlapped with the focus peeping route.
5. The method of claim 1, wherein a first processing point is randomly captured in the endoscopic image, the first processing point is subjected to noise reduction processing, and a first noise reduction processing point is obtained, the method comprising:
performing gray scale processing on the endoscope image to obtain a pixel gray scale image;
randomly capturing the endoscope image to obtain a first processing point, marking the first processing point in the pixel gray level image, and obtaining a first gray level processing point;
acquiring a first neighborhood set corresponding to the first gray processing point;
and carrying out noise reduction processing on the first processing point through the first neighborhood set to obtain a first noise reduction processing point.
6. The method of claim 5, wherein the first processing point is noise reduced by the first neighborhood set to obtain a first noise reduction processing point, the method comprising:
performing differential operation at a first processing point according to a median theorem based on the first neighborhood set to obtain first median substitution data;
based on the first neighborhood set, gray difference value calculation is carried out, and a first gray difference value set is obtained, wherein the first gray difference value set is arranged from large to small according to the difference of pixel gray values;
and referring to the first gray level difference value set, performing median substitution on the first processing point by using first median substitution data to obtain a first noise reduction processing point.
7. The method of claim 5, wherein performing a differential operation at a first processing point according to a median theorem based on the first neighborhood set results in first median substitution data, the method comprising:
based on the first neighborhood set, grouping to obtain a first point position set and a first symmetrical point position set;
performing differential operation in groups according to the first point bit set and the first symmetrical point bit set to obtain a first median computing data set;
and calculating the mean value of the first median calculation data set, and recording the mean value of the first median calculation data set as first median substitution data.
8. An image diagnosis apparatus for carrying out the image diagnosis method according to any one of claims 1 to 7, comprising:
the route planning module is used for carrying out route planning by referring to focus position information after the endoscopic observation instruction is led into the information interaction management platform, so as to obtain a focus peeping route;
the image acquisition permission issuing module is used for issuing an endoscope image acquisition permission after the endoscope bending part is overlapped with the focus peeping route according to the focus peeping route and is close to the focus position;
the endoscope image acquisition module is used for acquiring and acquiring an endoscope image after receiving the endoscope image acquisition permission;
the first noise reduction processing module is used for randomly capturing the first processing point in the endoscope image, performing noise reduction processing on the first processing point and obtaining a first noise reduction processing point;
the whole noise reduction processing module is used for traversing the endoscope image and acquiring a plurality of noise reduction processing points;
the tunnel muscle tremor acquisition module is used for acquiring tunnel muscle tremor data at the bending part of the endoscope;
the noise reduction processing image output module is used for taking the plurality of noise reduction processing points as basic data, taking the channel muscle tremor data as correction data, synthesizing noise reduction processing images, and synchronously displaying and outputting on a peripheral display screen.
9. An image diagnostic apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.
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