Capsule device for measuring length of intestinal tract and measuring method thereof

Abstract

The invention discloses a capsule device for measuring the length of an intestinal tract and a measuring method thereof. The device comprises an intestinal tract recognition module, an image acquisition module, a storage module, a control module, a central processing module and a battery module, the intestinal tract recognition module carries out intestinal tract recognition and sends out a recognition instruction; the central processing module receives the identification instruction and then sends a shooting instruction and a control instruction; the control module receives the control instruction to set the shooting interval time, and the image acquisition module receives the shooting instruction and then carries out shooting according to the interval time set by the control module; the storage module receives and stores the shot image; the central processing module calculates through a built-in image processing module and a built-in distance measuring and calculating module to obtain the length of the intestinal tract; the battery module supplies power by connecting the modules. According to the invention, non-invasive and dynamic measurement of the length of the intestinal tract is realized, and data support is provided for diagnosis and treatment of intestinal diseases.

Description

Technical Field

[0001] The present invention relates to the technical field of intestinal measurement, and in particular to a capsule device for measuring intestinal length and a measuring method thereof. Background Art

[0002] In the field of modern medicine, accurate measurement of intestinal length is of great significance for the diagnosis, formulation of treatment plans and disease monitoring of various diseases. For example, in the diagnosis and treatment of congenital intestinal malformations, short bowel syndrome, intestinal tumors, intestinal inflammatory diseases, etc., accurate data on intestinal length can provide doctors with key information to help determine the extent of disease progression, formulate surgical plans and evaluate treatment effects. However, there is currently a lack of an efficient, accurate and convenient method for measuring intestinal length in clinical practice, which to some extent limits the improvement of the diagnosis and treatment level of related diseases.

[0003] With the development of science and technology, some non-invasive methods for measuring intestinal length have emerged in the existing technology, such as imaging-based measurement technology, including X-ray angiography, CT scanning and MRI examination. These methods image the intestine and then use image processing technology to measure the length of the intestine. Compared with traditional surgical measurement, these imaging methods have certain advantages. They are non-invasive examinations, with less physical trauma to patients, and are more easily accepted by patients. At the same time, the intestine can be observed and measured without surgery, which can be used for long-term follow-up and dynamic monitoring of patients. However, the existing imaging measurement technology also has obvious shortcomings. X-ray angiography requires the use of contrast agents, which can cause adverse reactions such as allergies to patients, and X-rays have certain radioactivity. Long-term or frequent use can cause potential harm to the patient's health. CT scanning also has radiation problems, and its image resolution is not clear enough for the display of intestinal fine structures, affecting the accuracy of measurement. Although MRI examinations do not have radiation, the examination time is long, the cost is high, and there are restrictions on patients with metal implants in their bodies, so it is not suitable for all patients. In addition, existing imaging measurement methods also have large measurement errors during image analysis and processing, making it difficult to meet clinical needs for accurate measurement of intestinal length.

[0004] Therefore, the present invention proposes a capsule device for measuring intestinal length and a measuring method thereof, which solves the technical problems existing in the prior art. Summary of the invention

[0005] Based on the above content, the present application provides a capsule device for measuring intestinal length, including an intestinal identification module, an image acquisition module, a storage module, a control module, a central processing module and a battery module;

[0006] The intestinal tract recognition module recognizes the intestinal tract and sends a recognition instruction to the central processing module;

[0007] After receiving the recognition instruction, the central processing module sends a shooting instruction and a control instruction to the image acquisition module and the control module; the control module receives the control instruction to set the shooting interval time, and the image acquisition module receives the shooting instruction and shoots the intestinal image according to the interval time set by the control module;

[0008] The storage module receives the image captured by the image acquisition module, stores it, and transmits it to the central processing module;

[0009] The central processing module calculates and obtains the intestinal length through the built-in image processing module and distance measurement module;

[0010] The battery module is powered by connecting the modules.

[0011] Preferably, the intestinal recognition module includes a texture module and a shell sensor module; the texture module analyzes the image captured by the image acquisition module, obtains the inner wall characteristics to form the first recognition data; the shell sensor module includes a chemical sensor module and a pressure sensor module, the chemical sensor module forms the second recognition data by obtaining the pH value of the intestine; the pressure sensor module forms the third recognition data by obtaining the pressure change around the capsule and combining it with the pressure fluctuation caused by intestinal peristalsis; if the first recognition data, the second recognition data and the third recognition data all meet the preset conditions of the intestinal environment characteristics, a start signal is sent to the image acquisition module, and a stop signal is sent if no recognition is achieved.

[0012] Preferably, after receiving the control instruction sent by the central processing module, the control module calculates the shooting interval time T through the intestinal peristalsis state data collected in real time by the housing sensor module, including the peristalsis frequency f and the peristalsis amplitude A, and the formula is: Among them, T 0 is the initial basic shooting interval, k is the clinical trial constant; when the intestinal peristalsis amplitude A is larger and the frequency f is higher, the shooting interval T will be shortened; conversely, when the intestinal peristalsis amplitude is smaller and the frequency is lower, the shooting interval T will be appropriately extended, and the shooting interval is dynamically adjusted according to the real-time status of intestinal peristalsis.

[0013] Preferably, the image acquisition module includes an anti-shake stabilization module and a photosensitive module: the anti-shake stabilization module monitors the capsule's posture change data in real time, solves the capsule's posture change data in real time through an intestinal posture prediction model, generates a posture control signal according to the posture solution result, adjusts the lens shooting angle, compensates for the shaking of the capsule, and ensures that the lens is always aimed at the target shooting area; the photosensitive module calculates the intestinal sensitivity value according to the intestinal lighting prediction model, based on the current light intensity and the predicted lighting changes, and fine-tunes the capsule luminance according to the intestinal sensitivity value to obtain clear and accurate intestinal image information.

[0014] Preferably, the intestinal posture prediction model calculates the posture change data of the capsule in real time to generate a posture control signal, specifically:

[0015] Get the capsule's attitude change data, including the capsule's real-time angular velocity vector With the linear acceleration vector The intestinal posture prediction model is used to calculate the capsule posture change in real time. The formula is: in is the predicted attitude angle vector at the next moment t, is the current attitude angle vector, Δt is the time interval, k is the acceleration influence coefficient, and the calculated By comparing the preset stable posture angle vector Generate attitude deviation vector The formula is: By generating a posture deviation vector Then get the attitude control signal vector The formula is: Where K p , K i , K d They are the attitude proportion, integral, and differential coefficients respectively, and the attitude control signal vector Drive the lens angle adjustment, adjust the lens shooting angle, compensate for the shaking of the capsule, and make the lens always aim at the target shooting area.

[0016] Preferably, the photosensitive module calculates the intestinal photosensitivity value through the intestinal illumination prediction model, fine-tunes the capsule luminance, and obtains intestinal image information, specifically:

[0017] Get the current light intensity I in the intestine c , combined with historical light data and intestinal peristalsis law, the light changes in the short term in the future are predicted. The formula is: Among them I p To predict the light intensity, w i is the historical light change ΔI i The corresponding weight coefficient, n is the number of historical illumination data referenced, according to the current illumination intensity I c and the predicted light intensity I p , calculate the intestinal sensitivity value, the formula is: Where ISO is the sensitivity value, K is the sensitivity coefficient, L is the preset ideal image brightness value, α is the factor affecting the light change, the calculated intestinal sensitivity value ISO is compared with the preset sensitivity range, and the deviation sensitivity value ΔISO is calculated. The formula is: ΔISO = ISO-ISOs, where ISO sTo preset the sensitivity, the adjustment amount ΔB of the capsule luminance is obtained through the deviation sensitivity value ΔISO. The formula is: ΔB=β·ΔISO, where β is the luminance adjustment coefficient. The capsule luminance is fine-tuned according to ΔB to obtain clear and accurate intestinal image information.

[0018] Preferably, the central processing module obtains the intestinal length through the built-in image processing module and the distance measurement module; the image processing module receives the original image data from the image acquisition module, performs image enhancement processing, uses a deep learning algorithm to improve the contrast and clarity of the image, highlights the detailed features of the inner wall of the intestine, uses an image noise reduction algorithm to remove the noise interference generated during the shooting process, extracts features from the processed image, marks the landmark feature points in the intestine, and transmits the processed image to the distance calculation module; the distance calculation module calculates the movement distance of the capsule between adjacent shooting moments through a distance calculation model based on the image feature points extracted by the image processing module and the time interval between adjacent image shootings, determines the displacement of the feature points in the adjacent images, calculates the actual movement distance based on the time interval, accumulates the distance data, obtains a preliminary intestinal length measurement value, and transmits the result to the data storage module.

[0019] Preferably, the distance calculation module determines the displacement of the feature points in the adjacent images based on the image feature points extracted by the image processing module, calculates the actual moving distance in combination with the time interval, and accumulates the distance data to preliminarily obtain the intestinal length measurement value, specifically:

[0020] For the adjacent i-th frame and i+1-th frame image, the pixel coordinates of the same feature point in the two frames are determined by the feature matching algorithm (x i ,y i ) and (x i+1 ,y i+1 ), calculate the pixel displacement Δp of the feature point in the image i , the formula is: Combine the time interval Δt between adjacent image captures i , calculate the actual movement distance of the capsule between adjacent shooting moments, the formula is: where k d is the distance conversion coefficient, γ is the correction coefficient of the effect of intestinal peristalsis on capsule movement, and the moving distance d between each adjacent shooting time is obtained. i Then, by adding the formula Obtaining preliminary intestinal length measurements where n p is the total number of images taken.

[0021] Preferably, the central processing module also includes a result analysis module; the result analysis module receives the preliminary intestinal length measurement value of the distance calculation module, compares and analyzes it with the standard intestinal length database and the patient's medical database, and evaluates whether the measurement result is within the normal range in combination with the individual patient's age, gender, height, weight and medical database information. If the measurement value is abnormal, the image data and movement distance data are analyzed, the capsule posture is adjusted for a second shot, and the result of the second shot is analyzed to see if it is within the normal range, and the two shooting results are compared to ensure that the intestinal length is accurate.

[0022] A method for measuring intestinal length, comprising:

[0023] S1, identifying the intestine through the intestine recognition module, and sending a start signal to the central processing module when the preset conditions of the intestinal environment characteristics are met;

[0024] S2, after the central processing module receives the start signal, the control module sets the shooting interval time, and the image acquisition module shoots the intestinal image according to the interval time;

[0025] S3, the storage module receives and stores the image captured by the image acquisition module, and transmits it to the central processing module. The central processing module performs image enhancement, noise reduction and feature extraction processing on the image through the image processing module, and then transmits the processed image and feature data to the distance calculation module;

[0026] S4, the distance calculation module combines the feature points extracted by the image processing module and the time interval between adjacent image shootings to calculate and accumulate the capsule movement distance to obtain a preliminary intestinal length measurement value, which is transmitted to the result analysis module of the central processing module;

[0027] S5. The result analysis module of the central processing module compares and analyzes the preliminary intestinal length measurement value with the relevant database. If the measurement value is abnormal, the capsule posture is adjusted to take a second shot and the result is analyzed again to ensure the accuracy of the intestinal length measurement.

[0028] Compared with the prior art, the technical solution of this application has the following technical effects:

[0029] The present invention solves the technical problem of how to accurately identify whether a capsule is in the intestine by setting a texture module and a shell sensor module in the intestine recognition module, using the texture module to analyze images to obtain inner wall features, the chemical sensor module to obtain the pH of the intestine, and the pressure sensor module to obtain data based on the peristaltic pressure fluctuations of the intestine. This avoids invalid shooting in a non-intestinal environment, reduces data processing volume and energy consumption, improves the pertinence and effectiveness of image acquisition, ensures the reliability of measurement results, avoids deviations in measurement results due to misjudgment of the capsule position, and provides more accurate data support for clinical diagnosis.

[0030] After receiving the control instruction from the central processing module, the control module of the present invention sets the shooting interval time, thus solving the problem that the shooting interval time is difficult to dynamically adjust according to the actual intestinal peristalsis. The traditional method uses a fixed shooting interval, which cannot adapt to the changes in intestinal peristalsis and easily causes missing or redundant image information. The present application can shorten the shooting interval when the intestinal peristalsis amplitude is large and the frequency is high, so as to capture intestinal changes in time; and extend the shooting interval when the peristalsis amplitude is small and the frequency is low, so as to save energy and storage space. Through this dynamic adjustment, it is ensured that sufficient and effective intestinal images can be obtained under different intestinal peristalsis states, which not only improves the quality of image acquisition, but also improves the utilization rate of data, which helps to more accurately analyze intestinal conditions and measure intestinal length.

[0031] The anti-shake stabilization module in the image acquisition module of the present application monitors the capsule posture change data in real time, performs real-time calculation through the intestinal posture prediction model, and generates a posture control signal to adjust the lens shooting angle based on the calculation result; the photosensitive module calculates the intestinal sensitivity value according to the intestinal illumination prediction model and fine-tunes the capsule luminescence, which solves the problem of blurred and unclear image shooting caused by the capsule rolling in the intestine and changes in illumination. It is difficult to guarantee image quality in traditional image acquisition methods when facing complex environments in the intestine. This technology can keep the lens aimed at the target shooting area, compensate for the shaking of the capsule, and ensure that clear and accurate intestinal image information can be obtained under different lighting conditions. These high-quality images provide a reliable basis for subsequent image processing, feature point extraction and distance calculation, which helps to improve the accuracy of intestinal length measurement, avoid measurement errors caused by image quality problems, and provide doctors with clearer and more accurate intestinal image data for diagnosis.

[0032] The result analysis module in the central processing module of the present application compares and analyzes the preliminary intestinal length measurement value obtained by the distance calculation module with the standard intestinal length database and the patient-doctor database, evaluates the measurement result in combination with the patient's individual information, and adjusts the capsule posture for a second shot and re-analysis if it is abnormal. This technical solution solves the problem that a single measurement result is inaccurate and cannot be comprehensively judged in combination with the patient's individual situation. Traditional measurement methods often only give measurement values ​​and lack comprehensive evaluation and verification of the results. Through comparative analysis, this technology can more accurately judge whether the measurement results are normal and detect abnormalities in a timely manner. Secondary shooting and re-analysis further ensure the accuracy of the measurement and reduce the risk of misdiagnosis and missed diagnosis. Doctors can formulate more reasonable treatment plans based on more accurate intestinal length measurement results, improve the accuracy of disease diagnosis and treatment, and provide more reliable protection for patients' health.

[0033] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application so that it can be implemented in accordance with the contents of the specification, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following is a detailed description of the preferred embodiments of the present application in conjunction with the accompanying drawings as follows.

[0034] Based on the detailed description of the specific embodiments of the present application in combination with the accompanying drawings below, those skilled in the art will become more aware of the above and other objects, advantages and features of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings without creative work. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale.

[0036] Figure 1 A structural diagram of a capsule device for measuring intestinal length;

[0037] Figure 2 It is a flow chart of the intestinal recognition module system of the capsule device;

[0038] Figure 3 A flow chart of a method for measuring intestinal length. DETAILED DESCRIPTION

[0039] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, rather than all of the embodiments. In the following description, specific details such as specific configuration and components are provided only to help fully understand the embodiments of the present application. Therefore, it should be clear to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, for clarity and brevity, the description of known functions and structures is omitted in the embodiment.

[0040] It should be understood that the references to "one embodiment" or "this embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present application. Therefore, the references to "one embodiment" or "this embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0041] In addition, the present application may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplicity and clarity, and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0042] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" in this article describes another type of association object relationship, indicating that there can be two relationships. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the previous and next associated objects are in an "or" relationship.

[0043] The term "at least one" in this article is merely a description of the association relationship of associated objects, indicating that there may be three relationships. For example, at least one of A and B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0044] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusions.

[0045] Example 1

[0046] This embodiment mainly describes a capsule device for measuring intestinal length. Figure 1 As shown, it includes an intestinal recognition module, an image acquisition module, a control module, a storage module, a central processing module and a battery module;

[0047] The intestinal recognition module recognizes the intestine and sends a recognition instruction to the central processing module;

[0048] After receiving the recognition instruction, the central processing module sends a shooting instruction and a control instruction to the image acquisition module and the control module; the control module receives the control instruction to set the shooting interval time, and the image acquisition module receives the shooting instruction and shoots the intestinal image according to the interval time set by the control module;

[0049] The storage module stores the images taken by the image acquisition module and transmits them to the central processing module;

[0050] The central processing module obtains the intestinal length through the built-in image processing module and distance measurement module;

[0051] The battery module is powered by connecting the modules.

[0052] Further, if Figure 2 As shown, the intestinal recognition module includes a texture module and a shell sensor module; the texture module analyzes the image collected by the image acquisition module, obtains the inner wall characteristics to form the first recognition data; the shell sensor module includes a chemical sensor module and a pressure sensor module, the chemical sensor module obtains the intestinal pH to form the second recognition data; the pressure sensor module obtains the pressure change around the capsule and combines it with the pressure fluctuation caused by intestinal peristalsis to form the third recognition data; if the first recognition data, the second recognition data and the third recognition data all meet the preset conditions of the intestinal environment characteristics, a start signal is sent to the image acquisition module, and a stop signal is sent if no recognition is found.

[0053] Furthermore, after receiving the control instruction sent by the central processing module, the control module calculates the shooting interval time T through the intestinal peristalsis state data collected in real time by the shell sensor module, including the peristalsis frequency f and the peristalsis amplitude A. The formula is: Among them, T 0 is the initial basic shooting interval, k is the clinical trial constant; when the intestinal peristalsis amplitude A is larger and the frequency f is higher, the shooting interval T will be shortened; conversely, when the intestinal peristalsis amplitude is smaller and the frequency is lower, the shooting interval T will be appropriately extended, and the shooting interval is dynamically adjusted according to the real-time status of intestinal peristalsis.

[0054] Furthermore, the image acquisition module includes an anti-shake stabilization module and a photosensitive module: the anti-shake stabilization module monitors the capsule's posture change data in real time, solves the capsule's posture change data in real time through the intestinal posture prediction model, generates a posture control signal according to the posture solution result, adjusts the lens shooting angle, and compensates for the shaking of the capsule, so that the lens is always aimed at the target shooting area; the photosensitive module calculates the intestinal sensitivity value according to the intestinal lighting prediction model, based on the current light intensity and the predicted lighting changes, and fine-tunes the capsule luminance according to the intestinal sensitivity value to obtain clear and accurate intestinal image information.

[0055] Furthermore, the intestinal posture prediction model calculates the capsule posture change data in real time and generates posture control signals, specifically:

[0056] Get the capsule's attitude change data, including the capsule's real-time angular velocity vector With the linear acceleration vector The intestinal posture prediction model is used to calculate the capsule posture change in real time. The formula is: in is the predicted attitude angle vector at the next moment t, is the current attitude angle vector, Δt is the time interval, k is the acceleration influence coefficient, and the calculated By comparing the preset stable posture angle vector Generate attitude deviation vector The formula is: By generating a posture deviation vector Then get the attitude control signal vector The formula is: Where K p , K i , K d They are the attitude proportion, integral, and differential coefficients respectively, and the attitude control signal vector Drive the lens angle adjustment, adjust the lens shooting angle, compensate for the shaking of the capsule, and make the lens always aim at the target shooting area.

[0057] Furthermore, the photosensitive module calculates the intestinal photosensitivity value through the intestinal illumination prediction model, fine-tunes the capsule luminance, and obtains intestinal image information, specifically:

[0058] Get the current light intensity I in the intestine c , combined with historical light data and intestinal peristalsis law, the light changes in the short term in the future are predicted. The formula is: Among them I p To predict the light intensity, w i is the historical light change ΔI i The corresponding weight coefficient, n is the number of historical illumination data for reference, based on the current illumination intensity Ic and the predicted illumination intensity I p , calculate the intestinal sensitivity value, the formula is: Among them, ISO is the sensitivity value, K is the sensitivity coefficient, L is the preset ideal image brightness value, and α is the factor affecting the light change. The calculated intestinal sensitivity value ISO is compared with the preset sensitivity range to calculate the deviation sensitivity value ΔISO. The formula is: ΔISO = ISO-ISO s , where ISO s To preset the sensitivity, the adjustment amount ΔB of the capsule luminance is obtained through the deviation sensitivity value ΔISO. The formula is: ΔB=β·ΔISO, where β is the luminance adjustment coefficient. The capsule luminance is fine-tuned according to ΔB to obtain clear and accurate intestinal image information.

[0059] Furthermore, the central processing module obtains the intestinal length through the built-in image processing module and the distance measurement module; the image processing module receives the original image data from the image acquisition module, performs image enhancement processing, uses a deep learning algorithm to improve the contrast and clarity of the image, highlights the detailed features of the inner wall of the intestine, uses an image noise reduction algorithm to remove the noise interference generated during the shooting process, extracts features from the processed image, marks the landmark feature points in the intestine, and transmits the processed image to the distance calculation module; the distance calculation module calculates the movement distance of the capsule between adjacent shooting moments through a distance calculation model based on the image feature points extracted by the image processing module and the time interval between adjacent image shootings, determines the displacement of the feature points in adjacent images, calculates the actual movement distance based on the time interval, accumulates the distance data, obtains a preliminary intestinal length measurement value, and transmits the result to the data storage module.

[0060] Furthermore, the distance calculation module determines the displacement of the feature points in the adjacent images based on the image feature points extracted by the image processing module, calculates the actual moving distance in combination with the time interval, and accumulates the distance data to preliminarily obtain the intestinal length measurement value, which is specifically:

[0061] For the adjacent i-th frame and i+1-th frame image, the pixel coordinates of the same feature point in the two frames are determined by the feature matching algorithm (x i ,y i ) and (x i+1 ,y i+1 ), calculate the pixel displacement Δp of the feature point in the image i , the formula is: Combine the time interval Δt between adjacent image captures i , calculate the actual movement distance of the capsule between adjacent shooting moments, the formula is: where k d is the distance conversion coefficient, γ is the correction coefficient of the effect of intestinal peristalsis on capsule movement, and the moving distance d between each adjacent shooting time is obtained. i Then, by adding the formula Obtaining preliminary intestinal length measurements where n p is the total number of images taken.

[0062] Furthermore, the central processing module also includes a result analysis module; the result analysis module receives the preliminary intestinal length measurement value of the distance calculation module, compares and analyzes it with the standard intestinal length database and the patient's medical database, and evaluates whether the measurement result is within the normal range in combination with the patient's individual age, gender, height, weight and medical database information. If the measurement value is abnormal, the image data and movement distance data are analyzed, the capsule posture is adjusted for a second shot, and the result of the second shot is analyzed to see if it is within the normal range, and the two shooting results are compared to ensure that the intestinal length is accurate.

[0063] This embodiment describes in detail that the present application uses an intestinal recognition module to accurately determine whether the capsule is in the intestine, avoid invalid shooting, and improve the targeted data collection; the control module adjusts the shooting interval in real time according to intestinal peristalsis to ensure the acquisition of valid images; the anti-shake stabilization of the image acquisition module and the collaboration of the photosensitive module overcome the problems of capsule movement and lighting to obtain clear intestinal images; the central processing module integrates image processing, distance calculation and result analysis functions, which can not only accurately calculate the intestinal length, but also evaluate the measurement results in combination with the patient's individual information. In the event of an abnormality, a second shot is taken to ensure accuracy, which effectively solves the shortcomings of traditional measurement methods as a whole, improves the accuracy and reliability of intestinal length measurement, and provides more accurate data support for the diagnosis and treatment of intestinal diseases.

[0064] Based on Example 1, this example describes in detail how the intestinal recognition module recognizes and sends a start signal to the image acquisition module, and sends a stop signal if no recognition is made, specifically:

[0065] The intestinal recognition module includes a texture module and a shell sensor module; the texture module analyzes the image collected by the image acquisition module to obtain the inner wall features to form the first recognition data;

[0066] After the texture module receives the image collected by the image acquisition module, it grayscales the image, converts the color image into a grayscale image, and uses the local binary pattern algorithm to extract the texture features of the image; for each pixel in the image, the pixel values ​​in the neighborhood centered on it are compared with the central pixel value to generate a binary code, and the LBP histogram H of the entire image is calculated. LBP , we can get the texture distribution characteristics of the image and calculate the feature vector The formula is: Each vector is composed of different interval statistics of LBP histogram, where w f is the weight coefficient determined according to the differentiation of intestinal wall characteristics in different intervals, n f is the number of intervals of the LBP histogram, and the feature vector as first identification data;

[0067] The shell sensor module includes a chemical sensor module and a pressure sensor module. The chemical sensor module obtains the pH value of the intestine to form the second identification data. The chemical sensor module has a built-in high-precision pH sensor that can measure the pH value in the intestine in real time. c , the measurement errors of chemical sensors and the dynamic changes in the intestinal environment, calculate the corrected pH value r , the formula is: pH r =α pH pH m +(1-α pH )·pH b , where α pH is the correction factor, pH b pH is the base pH value m In order to measure the pH value in the intestine in real time, the corrected pH value r As a key parameter, combined with the rate of change of pH, ΔpH, the formula Constructing pH feature vector Where ΔpH is the change in pH within a certain time interval, and the pH characteristic vector The second identification data reflects the chemical environment characteristics in the intestine;

[0068] The pressure sensor module obtains the pressure change around the capsule and combines it with the pressure fluctuation caused by intestinal peristalsis to form the third identification data; the pressure sensor module monitors the pressure value P around the capsule in real time. m Since intestinal peristalsis will produce periodic pressure fluctuations, in order to extract the pressure characteristics related to intestinal peristalsis, the pressure data is filtered to remove high-frequency noise and interference signals to obtain a smoothed pressure curve. The mean pressure is calculated by performing time domain analysis on the pressure curve. Peak P p and the fluctuation period T w , get the pressure feature vector is third party identification data;

[0069] Determine whether the preset conditions of intestinal environment characteristics are met, respectively, the first identification data Second identification data and third party identification data Set preset threshold range and By formula A judgment is made, where S is the judgment result signal. When S=1, it indicates that the first recognition data, the second recognition data and the third recognition data all meet the preset conditions of the intestinal environment characteristics, and a start signal is sent to the image acquisition module; when S=0, the intestinal environment is not recognized, and a stop signal is sent.

[0070] This implementation describes in detail that the texture module, chemical sensor module and pressure sensor module are used to obtain the inner wall characteristics, pH and pressure changes to form identification data, and a start or stop signal is sent based on the comparison of these data with preset conditions, ensuring that the image acquisition module is only turned on in the intestinal environment, avoiding invalid work, improving acquisition efficiency and specificity, and ensuring that subsequent measurements are more accurate and effective.

[0071] Example 2

[0072] This embodiment describes in detail a method for measuring intestinal length. Figure 3 As shown, including:

[0073] S1, identifying the intestine through the intestine recognition module, and sending a start signal to the central processing module when the preset conditions of the intestinal environment characteristics are met;

[0074] S2, after the central processing module receives the start signal, the control module sets the shooting interval time, and the image acquisition module shoots the intestinal image according to the interval time;

[0075] S3, the storage module receives and stores the image captured by the image acquisition module, and transmits it to the central processing module. The central processing module performs image enhancement, noise reduction and feature extraction processing on the image through the image processing module, and then transmits the processed image and feature data to the distance calculation module;

[0076] S4, the distance calculation module combines the feature points extracted by the image processing module and the time interval between adjacent image shootings to calculate and accumulate the capsule movement distance to obtain a preliminary intestinal length measurement value, which is transmitted to the result analysis module of the central processing module;

[0077] S5. The result analysis module of the central processing module compares and analyzes the preliminary intestinal length measurement value with the relevant database. If the measurement value is abnormal, the capsule posture is adjusted to take a second shot and the result is analyzed again to ensure the accuracy of the intestinal length measurement.

[0078] After receiving the start signal from the intestinal recognition module, the central processing module of S2 quickly sends instructions to the control module. After receiving the instructions, the control module will refer to various data collected in real time by the outer shell sensor module, including intestinal peristalsis frequency, peristalsis amplitude, and pressure changes in the intestine. Based on these data, the control module will intelligently set the shooting interval. For example, when the intestinal peristalsis is more active, in order to capture the situation in the intestine more comprehensively and carefully, the control module will appropriately shorten the shooting interval; on the contrary, if the intestinal peristalsis is relatively slow, the control module will extend the shooting interval to balance the amount of data collection and energy consumption;

[0079] After receiving the shooting interval set by the control module, the image acquisition module starts to shoot intestinal images in an orderly manner according to the time interval. During the shooting process, the anti-shake stabilization module and the photosensitive module in the image acquisition module work together. The anti-shake stabilization module monitors the posture changes of the capsule in real time to ensure the stability of the lens and avoid blurring of the shooting picture due to the rolling and movement of the capsule in the intestine; the photosensitive module automatically adjusts the sensitivity and luminance according to the changes in the light intensity in the intestine to ensure that the captured intestinal images are clear and accurate, providing high-quality image data for subsequent analysis and processing.

[0080] After the image acquisition module completes the shooting, the storage module of S3 immediately receives the captured intestinal images and stores them. The storage module uses efficient storage algorithms and large-capacity storage media to ensure that the image data can be stored safely and stably without data loss or damage. After the storage is completed, the storage module quickly transmits the image to the central processing module;

[0081] After receiving the image, the image processing module in the central processing module performs image enhancement processing on the image to improve the contrast and clarity of the image, making the subtle structure and features of the intestinal wall more obvious, and uses the image noise reduction algorithm to remove the noise interference generated during the shooting process to improve the image quality; after completing the image enhancement and noise reduction, the image processing module will extract features from the processed image. It will identify and mark the landmark feature points in the intestine, such as intestinal folds, vascular bifurcation points, and other parts with obvious features. After completing these operations, the image processing module transmits the processed image and the extracted feature data to the distance calculation module, providing key data support for calculating the capsule movement distance and measuring the length of the intestine.

[0082] After receiving the processed images and feature data from the image processing module, the distance calculation module of S4 analyzes the feature points extracted from the adjacent images to determine the position change of the same feature point in different images, such as finding the coordinate position of the same intestinal fold feature point in different images in two adjacent frames of images; combined with the time interval between the shooting of adjacent images, the distance calculation module can calculate the movement distance of the capsule during this period of time. This calculation process is based on the precise analysis of the displacement of the feature points, and fully considers the movement trajectory and speed change of the capsule in the intestine. After calculating the movement distance between each adjacent shooting moment, the distance calculation module will accumulate these distance data. By continuously accumulating these movement distance data, the distance calculation module finally obtains the preliminary intestinal length measurement value. This preliminary measurement value is an important basis for subsequent precise analysis. It reflects the approximate distance that the capsule moves in the intestine and provides a preliminary basis for judging the intestinal length. After completing the calculation, the distance calculation module transmits the preliminary intestinal length measurement value to the result analysis module of the central processing module for analysis and verification.

[0083] This embodiment describes in detail a method for measuring intestinal length. Through the collaborative work of multiple modules, images are collected after accurate identification of the intestinal environment. The processing and analysis of the images can accurately calculate the movement distance of the capsule, and then obtain a preliminary measurement value. In the event of an abnormality, a second shot is taken and compared and analyzed, which effectively solves the problem of inaccurate measurement, provides doctors with accurate intestinal length data, and assists in the diagnosis and treatment of intestinal diseases.

[0084] The above are only preferred embodiments of the present invention, which do not limit the scope of protection of the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any changes, modifications, replacements, integrations and parameter changes to these embodiments within the spirit and principles of the present invention through conventional substitutions or without departing from the principles and spirit of the present invention fall within the scope of protection of the present invention.

Claims

1. A capsule device for measuring intestinal length, characterized in that: It includes an intestinal recognition module, an image acquisition module, a storage module, a control module, a central processing module and a battery module; The intestinal tract recognition module recognizes the intestinal tract and sends a recognition instruction to the central processing module; After receiving the recognition instruction, the central processing module sends a shooting instruction and a control instruction to the image acquisition module and the control module; the control module receives the control instruction to set the shooting interval time, and the image acquisition module receives the shooting instruction and shoots the intestinal image according to the interval time set by the control module; The storage module receives the image captured by the image acquisition module, stores it, and transmits it to the central processing module; The central processing module calculates and obtains the intestinal length through the built-in image processing module and distance measurement module; The battery module is powered by connecting the modules.

2. A capsule device for measuring intestinal length according to claim 1, characterized in that: The intestinal recognition module includes a texture module and a shell sensor module; the texture module analyzes the image collected by the image acquisition module, obtains the inner wall characteristics to form the first recognition data; the shell sensor module includes a chemical sensor module and a pressure sensor module, the chemical sensor module obtains the intestinal pH to form the second recognition data; the pressure sensor module obtains the pressure change around the capsule and combines it with the pressure fluctuation caused by intestinal peristalsis to form the third recognition data; when the first recognition data, the second recognition data and the third recognition data all meet the preset conditions of the intestinal environment characteristics, a start signal is sent to the image acquisition module, and a stop signal is sent if no recognition is achieved.

3. The capsule device for measuring intestinal length according to claim 1, characterized in that: After receiving the control instruction sent by the central processing module, the control module calculates the shooting interval time T through the intestinal peristalsis state data collected in real time by the shell sensor module, including the peristalsis frequency f and the peristalsis amplitude A. The formula is: Among them, T0 is the initial set basic shooting interval time, k is the clinical trial constant; when the intestinal peristalsis amplitude A is larger and the frequency f is higher, the shooting interval time T will be shortened; conversely, when the intestinal peristalsis amplitude is smaller and the frequency is lower, the shooting interval time T will be appropriately extended, and the shooting interval time will be dynamically adjusted according to the real-time status of intestinal peristalsis.

4. The capsule device for measuring intestinal length according to claim 1, characterized in that: The image acquisition module includes an anti-shake stabilization module and a photosensitive module: the anti-shake stabilization module monitors the posture change data of the capsule in real time, performs real-time calculation of the posture change data of the capsule through the intestinal posture prediction model, generates a posture control signal according to the posture calculation result, adjusts the lens shooting angle, compensates for the shaking of the capsule, and makes the lens always aim at the target shooting area; The photosensitive module calculates the intestinal sensitivity value based on the current light intensity and predicted light changes through the intestinal light prediction model, and fine-tunes the capsule luminance based on the intestinal sensitivity value to obtain clear and accurate intestinal image information.

5. The capsule device for measuring intestinal length according to claim 4, characterized in that: The intestinal posture prediction model calculates the capsule posture change data in real time and generates a posture control signal, specifically: Get the capsule's attitude change data, including the capsule's real-time angular velocity vector With the linear acceleration vector The intestinal posture prediction model is used to calculate the capsule posture change in real time. The formula is: in is the predicted attitude angle vector at the next moment t, is the current attitude angle vector, Δt is the time interval, k is the acceleration influence coefficient, and the calculated By comparing the preset stable posture angle vector Generate attitude deviation vector The formula is: By generating a posture deviation vector Then get the attitude control signal vector The formula is: Where K p , K i , K d They are the attitude proportion, integral, and differential coefficients respectively, and the attitude control signal vector Drive the lens angle adjustment, adjust the lens shooting angle, compensate for the shaking of the capsule, and make the lens always aim at the target shooting area.

6. The capsule device for measuring intestinal length according to claim 4, characterized in that: The photosensitive module calculates the intestinal photosensitivity value through the intestinal illumination prediction model, fine-tunes the capsule luminance, and obtains intestinal image information, specifically: Get the current light intensity I in the intestine c , combined with historical light data and intestinal peristalsis law, the light changes in the short term in the future are predicted. The formula is: Among them I p To predict the light intensity, w i is the historical light change ΔI i The corresponding weight coefficient, n is the number of historical illumination data referenced, according to the current illumination intensity I c and the predicted light intensity I p , calculate the intestinal sensitivity value, the formula is: Among them, ISO is the sensitivity value, K is the sensitivity coefficient, L is the preset ideal image brightness value, and α is the factor affecting the light change. The calculated intestinal sensitivity value ISO is compared with the preset sensitivity range to calculate the deviation sensitivity value ΔISO. The formula is: ΔISO = ISO-ISO s , where ISO s To preset the sensitivity, the adjustment amount ΔB of the capsule luminance is obtained through the deviation sensitivity value ΔISO. The formula is: ΔB=β·ΔISO, where β is the luminance adjustment coefficient. The capsule luminance is fine-tuned according to ΔB to obtain clear and accurate intestinal image information.

7. The capsule device for measuring intestinal length according to claim 1, characterized in that: The central processing module obtains the intestinal length through the built-in image processing module and the distance measurement module; the image processing module receives the original image data of the image acquisition module, performs image enhancement processing, uses a deep learning algorithm to improve the contrast and clarity of the image, highlights the detailed features of the intestinal wall, uses an image noise reduction algorithm to remove the noise interference generated during the shooting process, extracts features from the processed image, marks the landmark feature points in the intestine, and transmits the processed image to the distance calculation module; the distance calculation module calculates the movement distance of the capsule between adjacent shooting moments through a distance calculation model based on the image feature points extracted by the image processing module and the time interval between adjacent image shootings, determines the displacement of the feature points in the adjacent images, calculates the actual movement distance based on the time interval, accumulates the distance data, obtains a preliminary intestinal length measurement value, and transmits the result to the data storage module.

8. The capsule device for measuring intestinal length according to claim 7, characterized in that: The distance calculation module determines the displacement of the feature points in the adjacent images based on the image feature points extracted by the image processing module, calculates the actual moving distance in combination with the time interval, and accumulates the distance data to preliminarily obtain the intestinal length measurement value, specifically: For the adjacent i-th frame and i+1-th frame image, the pixel coordinates of the same feature point in the two frames are determined by the feature matching algorithm (x i ,y i ) and (x i+1 ,y i+1 ), calculate the pixel displacement Δp of the feature point in the image i , the formula is: Combine the time interval Δt between adjacent image captures i , calculate the actual movement distance of the capsule between adjacent shooting moments, the formula is: where k d is the distance conversion coefficient, γ is the correction coefficient of the effect of intestinal peristalsis on capsule movement, and the moving distance d between each adjacent shooting time is obtained. i Then, by adding the formula Obtaining preliminary intestinal length measurements Where n p is the total number of images taken.

9. The capsule device for measuring intestinal length according to claim 7, characterized in that: The central processing module also includes a result analysis module; the result analysis module receives the preliminary intestinal length measurement value of the distance calculation module, compares and analyzes it with the standard intestinal length database and the patient's medical database, and evaluates whether the measurement result is within the normal range in combination with the patient's individual age, gender, height, weight and medical database information. If the measurement value is abnormal, the image data and movement distance data are analyzed, the capsule posture is adjusted for a second shot, and the result of the second shot is analyzed to see if it is within the normal range, and the two shooting results are compared to ensure that the intestinal length is accurate.

10. A method for measuring intestinal length, characterized in that: include: S1, identifying the intestine through the intestine recognition module, and sending a start signal to the central processing module when the preset conditions of the intestinal environment characteristics are met; S2, after the central processing module receives the start signal, the control module sets the shooting interval time, and the image acquisition module shoots the intestinal image according to the interval time; S3, the storage module receives and stores the image captured by the image acquisition module, and transmits it to the central processing module. The central processing module performs image enhancement, noise reduction and feature extraction processing on the image through the image processing module, and then transmits the processed image and feature data to the distance calculation module; S4, the distance calculation module combines the feature points extracted by the image processing module and the time interval between adjacent image shootings to calculate and accumulate the capsule movement distance to obtain a preliminary intestinal length measurement value, which is transmitted to the result analysis module of the central processing module; S5. The result analysis module of the central processing module compares and analyzes the preliminary intestinal length measurement value with the relevant database. If the measurement value is abnormal, the capsule posture is adjusted to take a second shot and the result is analyzed again to ensure the accuracy of the intestinal length measurement.

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