Method and system for compressing and transmitting image data of chest electrical impedance imager

Abstract

The invention relates to the technical field of image data compression, in particular to a chest electrical impedance imager image data compression transmission method and system, and the method comprises the steps: starting a chest electrical impedance imager, obtaining an initial chest electrical impedance image, obtaining a target chest electrical impedance image, obtaining a chest electrical impedance data set, and carrying out the denoising operation of the chest electrical impedance data set, the method comprises the following steps: obtaining a denoised chest electrical impedance data set, sequentially extracting a group of denoised chest electrical impedance data from the denoised chest electrical impedance data set, and performing the following operations on the extracted denoised chest electrical impedance data: obtaining a data packet, and compressing the data packet by using a chip to obtain a simplified data packet set; analyzing the simplified data packet set based on a user port to obtain a decoded data packet set, obtaining a chest electrical impedance image according to the decoded data packet set, and completing chest electrical impedance imager image data compression and transmission based on the chest electrical impedance image. The method can improve the compression rate and guarantee the lossless performance of data transmission.

Description

Technical Field

[0001] The present invention relates to the technical field of image data compression, and in particular to a chest electrical impedance tomography image data compression and transmission method, system, electronic equipment and computer-readable storage medium. Background Art

[0002] Chest impedance torography refers to a device that uses non-invasive, radiation-free bedside monitoring technology. It is mainly used to monitor the ventilation and perfusion conditions of the lungs in real time. It reconstructs the impedance distribution of the lungs by injecting weak current into the human chest surface and collecting voltage signals, combined with parameterized level set imaging methods.

[0003] Traditional image compression methods mainly include lossless compression and lossy compression. Lossless compression mainly achieves compression by removing redundant data, but the compression rate is low. Lossy compression mainly achieves a higher compression rate by discarding some unimportant image information, but it may have a certain impact on image quality. Both compression methods lack specificity and lack real-time performance. Therefore, how to improve the compression rate and ensure the losslessness of data transmission is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present invention provides a chest electrical impedance tomography image data compression and transmission method and a computer-readable storage medium, the main purpose of which is to improve the compression rate and ensure the losslessness of data transmission, thereby improving product performance and user experience.

[0005] To achieve the above object, the present invention provides a chest electrical impedance tomography image data compression and transmission method, comprising:

[0006] receiving an image data compression instruction, starting a pre-built chest electrical impedance imager according to the image data compression instruction, acquiring an initial chest electrical impedance image according to the started chest electrical impedance imager, and performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map;

[0007] Acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map;

[0008] Acquiring a chest electrical impedance data set using a plurality of preset detection time periods and a target chest electrical impedance image;

[0009] Performing a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data;

[0010] A set of denoised chest electrical impedance data is extracted from the denoised chest electrical impedance data set in turn, and the following operations are performed on the extracted denoised chest electrical impedance data:

[0011] Acquiring a data packet according to the denoised chest electrical impedance data, and compressing the data packet using a pre-built chip to obtain a streamlined data packet;

[0012] Aggregating simplified data packets to obtain a simplified data packet set, parsing the simplified data packet set based on a pre-built user port to obtain a decoded data packet set;

[0013] A chest electrical impedance image is acquired according to the decoded data packet set, and compression and transmission of chest electrical impedance imager image data are completed based on the chest electrical impedance image.

[0014] Optionally, compressing the data packet by using the pre-built chip to obtain a simplified data packet includes:

[0015] Reading a reference frame from a data packet, wherein the data packet includes a plurality of unit frames, and the reference frame is the earliest unit frame in the data packet;

[0016] Acquire a reference matrix according to the reference frame, and acquire an initial adjacent matrix based on a preset detection frame rate and the reference matrix, wherein the initial adjacent matrix is ​​a matrix corresponding to a next unit frame adjacent to the reference matrix in time, and all element positions in the adjacent matrix correspond one-to-one to all element positions in the reference matrix;

[0017] The adjacent elements are extracted from the adjacent matrix in sequence, and the following operations are performed on the extracted adjacent elements:

[0018] Obtaining the element sites of the adjacent elements in the adjacent matrix to obtain the target sites, extracting the corresponding element sites from the reference matrix based on the target sites to obtain the historical comparison sites, and extracting the elements in the reference matrix based on the historical comparison sites to obtain the reference elements;

[0019] If the adjacent elements are not the same as the reference elements, difference data are constructed using the adjacent elements and the target site, and the difference data is filled into the pre-constructed blank difference text. After confirming that the adjacent elements in the adjacent matrix are all extracted, the filled difference text is obtained, and a compressed frame is obtained based on the filled difference text, wherein the filled difference text is the blank difference text after all the difference data in the adjacent matrix are filled, and the compressed frame includes a compressed frame header and one or more difference data, and the difference data includes two-byte row information, two-byte column information and four-byte difference value;

[0020] Taking the adjacent matrix as the reference matrix, returning to the step of obtaining the initial adjacent matrix based on the preset detection frame rate and the reference matrix until the unit frame in the data packet is extracted;

[0021] The reference frames and the compressed frames are aggregated in order of time from first to last to obtain a streamlined data packet.

[0022] Optionally, the parsing of the simplified data packet set based on the pre-built user port to obtain the decoded data packet set includes:

[0023] Extract a reduced data packet from the reduced data packet set in turn, and perform the following operations on each extracted reduced data packet:

[0024] Receiving a simplified data packet based on a user port, and reading a reference frame in the simplified data packet;

[0025] Extract compressed frames from the streamlined data packets in sequence, and perform the following operations on the extracted compressed frames:

[0026] Read the four-byte data of the compressed frame header to obtain the number of bytes of the compressed frame, and convert the number of bytes of the compressed frame into an integer format to obtain the length of the compressed frame;

[0027] Perform one or more difference data divisions on the compressed frame length to obtain one or more difference data block sets, wherein the difference data corresponds to the difference data block set one by one, and the difference data block set includes a plurality of difference data blocks, and the plurality of difference data blocks are respectively row numbers, column numbers and difference values;

[0028] The following operations are performed on one or more difference data block sets:

[0029] Extracting row numbers and column numbers from the difference data block set, extracting a reference reference point from a reference matrix corresponding to the difference data based on the row numbers and column numbers, and replacing a reference element of the reference reference point with a difference value in the difference data block to obtain an updated reference frame;

[0030] Summarize and integrate the updated reference frames to obtain new reference frames corresponding to one or more sets of difference data blocks;

[0031] The new reference frames are summarized to obtain a new reference frame set corresponding to the simplified data packet set, and the new reference frame set is confirmed as a decoding data packet set, wherein the simplified data packets correspond to the new reference frames one by one.

[0032] Optionally, performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map includes:

[0033] The initial chest electrical impedance image is meshed to obtain a mesh image, and the boundary of the mesh image is identified by using a pre-built edge detection algorithm to obtain an image boundary contour;

[0034] Constructing a reference coordinate system according to the grid image, wherein the center point of the initial chest electrical impedance image is the origin, the horizontal right direction of the initial chest electrical impedance image is the X-axis, and the vertical direction to the X-axis is the Y-axis;

[0035] Obtain four quadrants of the reference coordinate system, wherein the four quadrants include: an upper right area of ​​the origin as the first quadrant, an upper left area of ​​the origin as the second quadrant, a lower left area of ​​the origin as the third quadrant, and a lower right area of ​​the origin as the fourth quadrant;

[0036] Extract a target quadrant from the four quadrants in turn, and perform the following operations on the extracted target quadrants:

[0037] Acquire an image boundary coordinate set of a target quadrant based on the reference coordinate system, the image boundary contour, and the grid atlas;

[0038] Calculate the distance between each image boundary coordinate and the origin in the image boundary coordinate set to obtain a distance set, and extract the maximum distance from the distance set;

[0039] Summarize the maximum distances to obtain a maximum distance set, and extract the maximum distance value from the maximum distance set;

[0040] A segmentation threshold is set according to the maximum distance value, and the initial chest electrical impedance image is segmented using the segmentation threshold to obtain a chest electrical impedance segmentation map.

[0041] Optionally, respectively calculating the distance between each image boundary coordinate in the image boundary coordinate set and the origin to obtain a distance set includes:

[0042] Extract one image boundary coordinate from the image boundary coordinate set in turn, and perform the following operations on each of the extracted image boundary coordinates:

[0043] The distance between the image boundary coordinates and the origin is calculated using the pre-built Euclidean formula, where the Euclidean formula is as follows:

[0044]

[0045] Among them, d m Indicates the distance between the mth image boundary coordinate and the origin, x m Represents the horizontal coordinate of the mth image boundary coordinate, y m The ordinate of the mth image boundary coordinate, where m represents the index of the image boundary coordinate and n represents the total number of image boundary coordinates;

[0046] Sum up the distances between the image boundary coordinates and the origin to get a distance set.

[0047] Optionally, performing a denoising operation on the chest electrical impedance dataset to obtain a denoised chest electrical impedance dataset comprises:

[0048] Using the pre-constructed wavelet denoising, a denoising operation is performed on each chest electrical impedance data set in the chest electrical impedance data set to obtain an initial denoised data set;

[0049] Obtaining the original power of the chest electrical impedance dataset and obtaining the denoised power of the initial denoised dataset;

[0050] Calculate the signal-to-noise ratio of the original power and the denoised power;

[0051] If it is confirmed that the signal-to-noise ratio is less than the preset signal-to-noise ratio threshold, return to the step of performing a denoising operation on each chest electrical impedance data in the chest electrical impedance data set using the pre-constructed wavelet denoising until the signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio threshold, thereby obtaining a denoised chest electrical impedance data set.

[0052] Optionally, calculating the signal-to-noise ratio of the original power and the denoised power includes:

[0053] The signal-to-noise ratio of the original power to the denoised power is calculated using a pre-built signal-to-noise ratio formula, where the signal-to-noise ratio formula is as follows:

[0054]

[0055] Where X represents the signal-to-noise ratio, log 10 represents the logarithm with base 10, x i represents the i-th chest electrical impedance data, represents the i-th initial denoised data, N represents the total number in the chest electrical impedance data set, i represents the index of the chest electrical impedance data, P1 represents the original power, and P2 represents the denoised power.

[0056] Optionally, acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map includes:

[0057] Get the image size of the chest electrical impedance segmentation map and the image size range;

[0058] Determine whether the image size is within the image size range;

[0059] If it is confirmed that the image size is not within the image size range, the process returns to the step of performing threshold segmentation on the initial chest electrical impedance image until the image size is within the image size range, thereby obtaining a target chest electrical impedance image.

[0060] Optionally, obtaining the image size interval includes:

[0061] Obtain multiple historical detection time periods and historical chest electrical impedance image sets;

[0062] A historical detection time period is extracted from the multiple historical detection time periods in sequence, and the following operations are performed on each of the extracted historical detection time periods:

[0063] Using the historical detection time period to detect the historical chest electrical impedance image set, a historical image size group is obtained, wherein the historical image size group includes: widths and heights of multiple historical image sizes;

[0064] Summarize the historical image size groups to obtain a historical image size group set;

[0065] Calculate the size average of each historical image size group in the historical image size group set to obtain a size average group;

[0066] The maximum width average, maximum height average, minimum width average and minimum height average are extracted from the size average group, and the image size range is confirmed by the maximum width average, maximum height average, minimum width average and minimum height average.

[0067] To achieve the above object, the present invention also provides a chest electrical impedance tomography image data compression and transmission system, comprising:

[0068] A chest image acquisition module is used to receive an image data compression instruction, start a pre-built chest electrical impedance imager according to the image data compression instruction, obtain an initial chest electrical impedance image according to the started chest electrical impedance imager, perform threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map, and obtain a target chest electrical impedance image based on the chest electrical impedance segmentation map;

[0069] a data set generation module, used to obtain a chest electrical impedance data set by using a plurality of preset detection time periods and a target chest electrical impedance image, and to perform a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection time period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes a plurality of groups of chest electrical impedance data;

[0070] The data packet compression module is used to extract a set of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn, and perform the following operations on the extracted denoised chest electrical impedance data: obtain a data packet according to the denoised chest electrical impedance data, compress the data packet using a pre-built chip to obtain a simplified data packet, summarize the simplified data packets to obtain a simplified data packet set, and parse the simplified data packet set based on a pre-built user port to obtain a decoded data packet set;

[0071] The image reconstruction module is used to obtain a chest electrical impedance image according to the decoded data packet set, and complete the compression and transmission of chest electrical impedance imager image data based on the chest electrical impedance image.

[0072] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0073] A memory storing at least one instruction;

[0074] The processor executes the instructions stored in the memory to implement the above-mentioned chest electrical impedance imaging image data compression and transmission method.

[0075] In order to solve the above problem, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned chest electrical impedance imaging image data compression and transmission method.

[0076] The present invention is to solve the problem described in the background technology. The present invention receives an image data compression instruction, starts a pre-built chest impedance imager according to the image data compression instruction, obtains an initial chest impedance image according to the started chest impedance imager, and performs threshold segmentation on the initial chest impedance image to obtain a chest impedance segmentation map. The imager of the present invention starts immediately after receiving the instruction, which reduces the startup time and improves work efficiency. At the same time, the background and noise can be removed by threshold segmentation, the area of ​​interest is highlighted, and the clarity and analyzability of the image are improved. A target chest impedance image is obtained based on the chest impedance segmentation map. The present invention ensures that the image size of the chest impedance segmentation map meets the image size of the image. The image size interval can improve the accuracy and consistency of the target chest electrical impedance image, ensure the reliability and effectiveness of subsequent processing, use the preset multiple detection time periods and the target chest electrical impedance image to obtain a chest electrical impedance data set, perform a denoising operation on the chest electrical impedance data set, and obtain a denoised chest electrical impedance data set, wherein one detection time period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data. The present invention can obtain more data points through multi-time period detection, improve the representativeness and reliability of the data, remove noise interference, and improve the signal-to-noise ratio of the data, and extract a group of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn. The present invention processes the data by grouping, thereby improving the parallelism and efficiency of processing, facilitating management and analysis, obtaining a data packet according to the denoised chest electrical impedance data, and compressing the data packet by using a pre-built chip to obtain a streamlined data packet. The present invention compresses the data packet by using a chip, adopts a reference frame-compression frame structure, packages and compresses the chest electrical impedance imager image data, uses a relatively low complexity, and achieves an extremely high compression ratio. The streamlined data packets are aggregated to obtain a streamlined data packet set, and the streamlined data packet set is parsed based on a pre-built user port to obtain a decoded data packet set. The present invention obtains a decoded data packet set by using the aggregated data. The packet set is easy to manage and transmit, which improves the organization and integrity of the data. By parsing and simplifying the data packet set based on the user port, the system can accurately reconstruct the original chest electrical impedance image data, ensure the integrity and accuracy of the data, and provide reliable support for clinical diagnosis. The chest electrical impedance image is obtained according to the decoded data packet set, and the chest electrical impedance imager image data compression transmission is completed based on the chest electrical impedance image. The present invention can not only be used for product optimization in the data transmission process, but also can be applied to data storage, improve product performance, optimize user experience, reduce memory and performance occupancy, save the hardware cost of the chest electrical impedance imager, and create more benefits for enterprises and units. Therefore, the present invention can improve the compression rate and ensure the losslessness of data transmission, and improve product performance and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 A schematic diagram of a flow chart of a chest electrical impedance tomography image data compression and transmission method provided by an embodiment of the present invention;

[0078] Figure 2 A functional module diagram of a chest electrical impedance tomography image data compression and transmission system provided by an embodiment of the present invention;

[0079] Figure 3 A schematic structural diagram of an electronic device for implementing the chest electrical impedance tomography image data compression and transmission method provided in an embodiment of the present invention.

[0080] Figure 4 A schematic structural diagram of a chest electrical impedance image for implementing the chest electrical impedance imager image data compression and transmission method provided in an embodiment of the present invention.

[0081] Figure 5 A schematic diagram of the structure of difference data for implementing the chest electrical impedance tomography image data compression and transmission method provided by an embodiment of the present invention.

[0082] Figure 6 A schematic diagram of the structure of a compressed frame for implementing the chest electrical impedance tomography image data compression and transmission method provided by an embodiment of the present invention.

[0083] Figure 7 A schematic diagram of the structure of a data packet for implementing the chest electrical impedance tomography image data compression and transmission method provided in an embodiment of the present invention.

[0084] Description of reference numerals:

[0085] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0086] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0087] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0088] The embodiment of the present application provides a method for compressing and transmitting image data of a chest electrical impedance imager. The execution subject of the method for compressing and transmitting image data of a chest electrical impedance imager includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for compressing and transmitting image data of a chest electrical impedance imager can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0089] Reference Figure 1 FIG. 1 is a flow chart of a method for compressing and transmitting chest electrical impedance imaging image data provided by an embodiment of the present invention. In this embodiment, the method for compressing and transmitting chest electrical impedance imaging image data includes:

[0090] S1. Receive an image data compression instruction, start a pre-built chest impedance imager according to the image data compression instruction, obtain an initial chest impedance image according to the started chest impedance imager, and perform threshold segmentation on the initial chest impedance image to obtain a chest impedance segmentation map.

[0091] It should be explained that the image data compression instruction is a computer instruction used to start the compression process of image data, the purpose of which is to reduce the size of the image file for more efficient storage or transmission while maintaining the image quality as much as possible. The initial chest electrical impedance image refers to the original electrical impedance distribution image obtained by the reconstruction algorithm after the chest electrical impedance imager is started and collects data.

[0092] For example, Xiao Zhang is a radiologist in a hospital. They recently introduced a new chest impedance imager to non-invasively monitor the patient's lung condition. The chest impedance imager generates high-resolution images, but these image files are very large, and are difficult to store and transmit. Therefore, Xiao Zhang issued an instruction to compress the image, which is the image data compression instruction.

[0093] It is understandable that the step of obtaining the initial chest electrical impedance image according to the activated chest electrical impedance imager is: using the activated chest electrical impedance imager, applying a weak current to the chest skin, measuring the voltage change of the corresponding part, calculating the electrical impedance value according to the measured voltage signal and current signal, and reconstructing the electrical impedance distribution image inside the chest according to these electrical impedance values ​​in combination with a specific imaging algorithm. The electrical impedance distribution image is the initial chest electrical impedance image. The step of obtaining the initial chest electrical impedance image according to the activated chest electrical impedance imager described in the embodiment of the present invention is a prior art and will not be repeated again.

[0094] In detail, the threshold segmentation of the initial chest electrical impedance image to obtain the chest electrical impedance segmentation map includes:

[0095] The initial chest electrical impedance image is meshed to obtain a mesh image, and the boundary of the mesh image is identified by using a pre-built edge detection algorithm to obtain an image boundary contour;

[0096] Constructing a reference coordinate system according to the grid image, wherein the center point of the initial chest electrical impedance image is the origin, the horizontal right direction of the initial chest electrical impedance image is the X-axis, and the vertical direction to the X-axis is the Y-axis;

[0097] Obtain four quadrants of the reference coordinate system, wherein the four quadrants include: an upper right area of ​​the origin as the first quadrant, an upper left area of ​​the origin as the second quadrant, a lower left area of ​​the origin as the third quadrant, and a lower right area of ​​the origin as the fourth quadrant;

[0098] Extract a target quadrant from the four quadrants in turn, and perform the following operations on the extracted target quadrants:

[0099] Acquire an image boundary coordinate set of a target quadrant based on the reference coordinate system, the image boundary contour, and the grid atlas;

[0100] Calculate the distance between each image boundary coordinate and the origin in the image boundary coordinate set to obtain a distance set, and extract the maximum distance from the distance set;

[0101] Summarize the maximum distances to obtain a maximum distance set, and extract the maximum distance value from the maximum distance set;

[0102] A segmentation threshold is set according to the maximum distance value, and the initial chest electrical impedance image is segmented using the segmentation threshold to obtain a chest electrical impedance segmentation map.

[0103] It should be explained that the grid image refers to the image obtained by gridding the initial chest electrical impedance image. The edge detection algorithm refers to an image processing technology used to identify the boundaries of the grid image. The image boundary contour refers to the boundary contour of the image obtained by applying the edge detection algorithm to the grid image. The reference coordinate system refers to a two-dimensional coordinate system established with the center point of the initial chest electrical impedance image as the origin, the horizontal rightward X-axis, and the vertical upward Y-axis. The target quadrant refers to the quadrant extracted from the four quadrants for processing.

[0104] Importantly, the image boundary coordinate set refers to a set of pixel coordinates on the boundary extracted according to the image boundary contour within the selected target quadrant. The distance set refers to a distance set obtained by calculating the distance from each coordinate point in the image boundary coordinate set to the origin. The maximum distance refers to finding the maximum distance value from the distance set. The maximum distance set refers to a set that summarizes the maximum distances in all quadrants. The maximum distance value refers to finding the maximum distance value from the maximum distance set, which is used to set the segmentation threshold. The segmentation threshold refers to a threshold set according to the maximum distance value. The chest electrical impedance segmentation map refers to segmenting the initial chest electrical impedance image using the set segmentation threshold, and the resulting image only contains the target area of ​​interest.

[0105] In detail, the distance between each image boundary coordinate in the image boundary coordinate set and the origin is calculated to obtain a distance set, including:

[0106] Extract one image boundary coordinate from the image boundary coordinate set in turn, and perform the following operations on each of the extracted image boundary coordinates:

[0107] The distance between the image boundary coordinates and the origin is calculated using the pre-built Euclidean formula, where the Euclidean formula is as follows:

[0108]

[0109] Among them, d m Indicates the distance between the mth image boundary coordinate and the origin, x m Represents the horizontal coordinate of the mth image boundary coordinate, y m The ordinate of the mth image boundary coordinate, where m represents the index of the image boundary coordinate and n represents the total number of image boundary coordinates;

[0110] Sum up the distances between the image boundary coordinates and the origin to get a distance set.

[0111] It should be explained that the Euclidean formula refers to a mathematical formula used to calculate the straight-line distance between two points in a two-dimensional or three-dimensional space. The Euclidean formula described in the embodiment of the present invention is a formula used to calculate the distance between the image boundary coordinates and the origin.

[0112] S2. Acquire a target chest electrical impedance image based on the chest electrical impedance segmentation map.

[0113] In detail, acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map includes:

[0114] Get the image size of the chest electrical impedance segmentation map and the image size range;

[0115] Determine whether the image size is within the image size range;

[0116] If it is confirmed that the image size is not within the image size range, the process returns to the step of performing threshold segmentation on the initial chest electrical impedance image until the image size is within the image size range, thereby obtaining a target chest electrical impedance image.

[0117] It should be explained that the target chest electrical impedance image refers to a chest electrical impedance segmentation map that meets specific size requirements and is finally obtained through multiple adjustment and optimization steps. The step of obtaining the image size of the chest electrical impedance segmentation map is: after importing the chest electrical impedance segmentation map into the image processing software, the image size is obtained.

[0118] Furthermore, the obtaining of the image size interval includes:

[0119] Obtain multiple historical detection time periods and historical chest electrical impedance image sets;

[0120] A historical detection time period is extracted from the multiple historical detection time periods in sequence, and the following operations are performed on each of the extracted historical detection time periods:

[0121] Using the historical detection time period to detect the historical chest electrical impedance image set, a historical image size group is obtained, wherein the historical image size group includes: widths and heights of multiple historical image sizes;

[0122] Summarize the historical image size groups to obtain a historical image size group set;

[0123] Calculate the size average of each historical image size group in the historical image size group set to obtain a size average group;

[0124] The maximum width average, maximum height average, minimum width average and minimum height average are extracted from the size average group, and the image size range is confirmed by the maximum width average, maximum height average, minimum width average and minimum height average.

[0125] It should be explained that multiple historical detection time periods refer to multiple chest electrical impedance image detections performed in different time periods. The historical chest electrical impedance image set refers to the set of chest electrical impedance images generated by each detection in multiple historical detection time periods. The historical image size group refers to the set of image sizes obtained for all chest electrical impedance images in a certain historical detection time period. The historical image size group set refers to the set formed by summarizing the historical image size groups of all historical detection time periods. The size average value refers to the calculation of the average width and average height of all image sizes for a certain historical image size group. The size average value set refers to the set formed by summarizing the size average values ​​of all historical detection time periods.

[0126] For example, at 9:00 a.m. on January 1, 2023, Xiao Zhang obtains historical image size group C as [(512,512), (480,480), (500,500)], and at 9:00 a.m. on January 2, 2023, he obtains historical image size group D as [(520,520), (530,530), (510,510)]. The average width and height of historical image size group C are calculated to obtain [(497.33,497 .33)], calculate the average width and height of historical image size group D, and get [(520,520)], summarize historical image size group C and historical image size group D, and get the size average group [(497.33,497.33),(520,520)], extract the maximum width average, maximum height average, minimum width average and minimum height average from the size average group, and get the image size range of [497.33,520].

[0127] S3. Acquire a chest electrical impedance data set using a plurality of preset detection time periods and a target chest electrical impedance image.

[0128] It should be explained that the preset multiple detection time periods refer to a set of time periods preset before chest electrical impedance image detection. The chest electrical impedance data set refers to a set of all chest electrical impedance images and related data acquired within the preset multiple detection time periods.

[0129] S4. Perform a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data.

[0130] In detail, performing a denoising operation on the chest electrical impedance dataset to obtain a denoised chest electrical impedance dataset includes:

[0131] Using the pre-constructed wavelet denoising, a denoising operation is performed on each chest electrical impedance data set in the chest electrical impedance data set to obtain an initial denoised data set;

[0132] Obtaining the original power of the chest electrical impedance dataset and obtaining the denoised power of the initial denoised dataset;

[0133] Calculate the signal-to-noise ratio of the original power and the denoised power;

[0134] If it is confirmed that the signal-to-noise ratio is less than the preset signal-to-noise ratio threshold, return to the step of performing a denoising operation on each chest electrical impedance data in the chest electrical impedance data set using the pre-constructed wavelet denoising until the signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio threshold, thereby obtaining a denoised chest electrical impedance data set.

[0135] It should be explained that wavelet denoising refers to a signal processing technology used to recover the original signal from a signal interfered by noise. It is based on wavelet transform, and removes noise by decomposing the signal into a series of wavelet coefficients and then processing these coefficients. The wavelet denoising described in the embodiment of the present invention is used to process the data in the chest electrical impedance dataset to remove the noise components therein. The initial denoised dataset refers to a dataset of preliminary denoising results obtained after performing a wavelet denoising operation on each data in the chest electrical impedance dataset. The signal-to-noise ratio threshold refers to a preset standard value used to evaluate the effect of the denoising operation. The denoised chest electrical impedance dataset refers to a chest electrical impedance dataset that has been processed by wavelet denoising and whose signal-to-noise ratio reaches or exceeds the preset threshold.

[0136] In detail, the calculating of the signal-to-noise ratio of the original power and the denoised power includes:

[0137] The signal-to-noise ratio of the original power to the denoised power is calculated using a pre-built signal-to-noise ratio formula, where the signal-to-noise ratio formula is as follows:

[0138]

[0139] Where X represents the signal-to-noise ratio, log 10 represents the logarithm with base 10, x i represents the i-th chest electrical impedance data, represents the i-th initial denoised data, N represents the total number in the chest electrical impedance data set, i represents the index of the chest electrical impedance data, P1 represents the original power, and P2 represents the denoised power.

[0140] It should be explained that the original power refers to the power of the original data in the chest electrical impedance dataset that has not been subjected to any denoising process. The denoised power refers to the power of the denoised data obtained after the denoising process is performed on the data in the chest electrical impedance dataset.

[0141] S5. Extract a set of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn, and perform the following operations on the extracted denoised chest electrical impedance data: obtain a data packet according to the denoised chest electrical impedance data, and compress the data packet using a pre-built chip to obtain a streamlined data packet.

[0142] In detail, the method of compressing a data packet using a pre-built chip to obtain a simplified data packet includes:

[0143] Reading a reference frame from a data packet, wherein the data packet includes a plurality of unit frames, and the reference frame is the earliest unit frame in the data packet;

[0144] Acquire a reference matrix according to the reference frame, and acquire an initial adjacent matrix based on a preset detection frame rate and the reference matrix, wherein the initial adjacent matrix is ​​a matrix corresponding to a next unit frame adjacent to the reference matrix in time, and all element positions in the adjacent matrix correspond one-to-one to all element positions in the reference matrix;

[0145] The adjacent elements are extracted from the adjacent matrix in sequence, and the following operations are performed on the extracted adjacent elements:

[0146] Obtaining the element sites of the adjacent elements in the adjacent matrix to obtain the target sites, extracting the corresponding element sites from the reference matrix based on the target sites to obtain the historical comparison sites, and extracting the elements in the reference matrix based on the historical comparison sites to obtain the reference elements;

[0147] If the adjacent elements are not the same as the reference elements, difference data are constructed using the adjacent elements and the target site, and the difference data is filled into the pre-constructed blank difference text. After confirming that the adjacent elements in the adjacent matrix are all extracted, the filled difference text is obtained, and a compressed frame is obtained based on the filled difference text, wherein the filled difference text is the blank difference text after all the difference data in the adjacent matrix are filled, and the compressed frame includes a compressed frame header and one or more difference data, and the difference data includes two-byte row information, two-byte column information and four-byte difference value;

[0148] Taking the adjacent matrix as the reference matrix, returning to the step of obtaining the initial adjacent matrix based on the preset detection frame rate and the reference matrix until the unit frame in the data packet is extracted;

[0149] The reference frames and the compressed frames are aggregated in order of time from first to last to obtain a streamlined data packet.

[0150] It should be explained that the chip refers to a hardware device used to process and compress data. The reference frame refers to the earliest unit frame in the data packet. The reference matrix is ​​the complete data matrix in the data packet. The detection frame rate refers to the number of frames collected and processed per second. The initial adjacent matrix refers to the matrix formed by the unit frame extracted at the next time point of the reference frame. The adjacent element refers to each element in the adjacent matrix. The target site refers to the position of the adjacent element in the adjacent matrix. The historical comparison site refers to the position in the reference matrix corresponding to the target site. The reference element refers to the element at the position corresponding to the target site extracted from the reference matrix. Difference data refers to the difference information recorded when the adjacent element is different from the reference element, including row information, column information and difference value. The difference data can be referred to. Figure 5 .

[0151] Importantly, a blank difference text is an initially empty text that is used to record all difference data. A padded difference text is a text obtained by padded all difference data into the blank difference text. A compressed frame is a frame that contains a compressed frame header and one or more difference data. Figure 6 .

[0152] S6. Summarize the simplified data packets to obtain a simplified data packet set.

[0153] It should be explained that a simplified data packet refers to a data packet obtained by compressing a data packet. The compressed data packet only retains the key difference information and removes redundant data, thereby reducing the amount of data and facilitating storage and transmission. A simplified data packet set refers to a set of multiple simplified data packets, which can be referred to as Figure 7 .

[0154] S7. Parse the simplified data packet set based on the pre-built user port to obtain a decoded data packet set.

[0155] In detail, the simplified data packet set is parsed based on the pre-built user port to obtain a decoded data packet set, including:

[0156] Extract a reduced data packet from the reduced data packet set in turn, and perform the following operations on each extracted reduced data packet:

[0157] Receiving a simplified data packet based on a user port, and reading a reference frame in the simplified data packet;

[0158] Extract compressed frames from the streamlined data packets in sequence, and perform the following operations on the extracted compressed frames:

[0159] Read the four-byte data of the compressed frame header to obtain the number of bytes of the compressed frame, and convert the number of bytes of the compressed frame into an integer format to obtain the length of the compressed frame;

[0160] Perform one or more difference data divisions on the compressed frame length to obtain one or more difference data block sets, wherein the difference data corresponds to the difference data block set one by one, and the difference data block set includes a plurality of difference data blocks, and the plurality of difference data blocks are respectively row numbers, column numbers and difference values;

[0161] The following operations are performed on one or more difference data block sets:

[0162] Extracting row numbers and column numbers from the difference data block set, extracting a reference reference point from a reference matrix corresponding to the difference data based on the row numbers and column numbers, and replacing a reference element of the reference reference point with a difference value in the difference data block to obtain an updated reference frame;

[0163] Summarize and integrate the updated reference frames to obtain new reference frames corresponding to one or more sets of difference data blocks;

[0164] The new reference frames are summarized to obtain a new reference frame set corresponding to the simplified data packet set, and the new reference frame set is confirmed as a decoding data packet set, wherein the simplified data packets correspond to the new reference frames one by one.

[0165] It should be explained that the user port refers to the interface for receiving and processing simplified data packets. The number of bytes of a compressed frame refers to the number of bytes contained in a compressed frame. The length of a compressed frame refers to the value after converting the number of bytes of a compressed frame from a byte format to an integer format. A difference data block set refers to a set of multiple difference data blocks, each difference data block corresponding to a difference data in a compressed frame. A reference reference position refers to a specific position determined in a reference matrix according to a row number and a column number. An updated reference frame refers to a new matrix obtained by updating the element values ​​at corresponding positions based on the reference matrix and the information in the difference data block set. A new reference frame refers to the final updated reference frame obtained after processing all difference data block sets. A new reference frame set refers to a set of new reference frames corresponding to all simplified data packets.

[0166] Importantly, the step of aggregating and integrating the updated reference frames is to aggregate all the processed updated reference frames and ensure that each updated reference frame is merged together in the correct order and position.

[0167] For example, the reference matrix is Difference data block 1 has row number 1, column number 1, and difference value 5. Difference data block 2 has row number 3, column number 3, and difference value 2. Based on difference data block 1 and difference data block 2, a difference data block set is obtained. The row number and column number are extracted from the difference data block set. Based on the row number and column number, the reference reference positions (1, 1) and (3, 3) are extracted from the reference matrix. The reference elements 4 and 9 of the reference reference positions are replaced with the difference values ​​5 and 2 in the difference data block set to obtain an updated reference frame.

[0168]

[0169] S8. Acquire a chest electrical impedance image according to the decoded data packet set.

[0170] It should be explained that the decoded data packet set refers to a simplified data packet set after being parsed by the user port. The step of obtaining the chest electrical impedance image according to the decoded data packet set is as follows: each data packet in the decoded data packet set needs to be parsed, the chest electrical impedance data contained therein is extracted, the data is reassembled into a complete chest electrical impedance data sequence according to the information in the data packet, and the chest electrical impedance image can be reconstructed using the reassembled chest electrical impedance data through a specific image reconstruction algorithm.

[0171] S9. Complete compression and transmission of chest impedance imaging image data based on the chest impedance image.

[0172] It should be explained that the steps of completing the compression and transmission of chest impedance imager image data based on chest impedance image are: using the complete process of chest impedance imager from image acquisition, data processing, compression to data transmission, emphasizing the use of compression technology to reduce the amount of data, and finally completing the recovery and display of the image through transmission and decoding, completing the compression and transmission of chest impedance imager image data, and the chest impedance image can be referred to Figure 4 .

[0173] The present invention is to solve the problem described in the background technology. The present invention receives an image data compression instruction, starts a pre-built chest impedance imager according to the image data compression instruction, obtains an initial chest impedance image according to the started chest impedance imager, and performs threshold segmentation on the initial chest impedance image to obtain a chest impedance segmentation map. The imager of the present invention starts immediately after receiving the instruction, which reduces the startup time and improves work efficiency. At the same time, the background and noise can be removed by threshold segmentation, the area of ​​interest is highlighted, and the clarity and analyzability of the image are improved. A target chest impedance image is obtained based on the chest impedance segmentation map. The present invention ensures that the image size of the chest impedance segmentation map meets the image size of the image. The image size interval can improve the accuracy and consistency of the target chest electrical impedance image, ensure the reliability and effectiveness of subsequent processing, use the preset multiple detection time periods and the target chest electrical impedance image to obtain a chest electrical impedance data set, perform a denoising operation on the chest electrical impedance data set, and obtain a denoised chest electrical impedance data set, wherein one detection time period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data. The present invention can obtain more data points through multi-time period detection, improve the representativeness and reliability of the data, remove noise interference, and improve the signal-to-noise ratio of the data, and extract a group of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn. The present invention processes the data by grouping, thereby improving the parallelism and efficiency of processing, facilitating management and analysis, obtaining a data packet according to the denoised chest electrical impedance data, and compressing the data packet by using a pre-built chip to obtain a streamlined data packet. The present invention compresses the data packet by using a chip, adopts a reference frame-compression frame structure, packages and compresses the chest electrical impedance imager image data, uses a relatively low complexity, and achieves an extremely high compression ratio. The streamlined data packets are aggregated to obtain a streamlined data packet set, and the streamlined data packet set is parsed based on a pre-built user port to obtain a decoded data packet set. The present invention obtains a decoded data packet set by using the aggregated data. The packet set is easy to manage and transmit, which improves the organization and integrity of the data. By parsing and simplifying the data packet set based on the user port, the system can accurately reconstruct the original chest electrical impedance image data, ensure the integrity and accuracy of the data, and provide reliable support for clinical diagnosis. The chest electrical impedance image is obtained according to the decoded data packet set, and the chest electrical impedance imager image data compression transmission is completed based on the chest electrical impedance image. The present invention can not only be used for product optimization in the data transmission process, but also can be applied to data storage, improve product performance, optimize user experience, reduce memory and performance occupancy, save the hardware cost of the chest electrical impedance imager, and create more benefits for enterprises and units. Therefore, the present invention can improve the compression rate and ensure the losslessness of data transmission, and improve product performance and user experience.

[0174] like Figure 2, which is a functional module diagram of a chest electrical impedance tomography image data compression and transmission system provided by an embodiment of the present invention.

[0175] The chest electrical impedance imager image data compression and transmission system 100 of the present invention can be installed in an electronic device. According to the functions to be implemented, the chest electrical impedance imager image data compression and transmission system 100 may include a chest image acquisition module 101, a data set generation module 102, a data packet compression module 103 and an image reconstruction module 104. The module of the present invention may also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device;

[0176] The chest image acquisition module 101 is used to receive an image data compression instruction, start a pre-built chest electrical impedance imager according to the image data compression instruction, obtain an initial chest electrical impedance image according to the started chest electrical impedance imager, perform threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map, and obtain a target chest electrical impedance image based on the chest electrical impedance segmentation map;

[0177] The data set generation module 102 is used to obtain a chest electrical impedance data set by using a plurality of preset detection time periods and a target chest electrical impedance image, and to perform a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection time period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes a plurality of groups of chest electrical impedance data;

[0178] The data packet compression module 103 is used to extract a set of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn, and perform the following operations on the extracted denoised chest electrical impedance data: obtain a data packet according to the denoised chest electrical impedance data, compress the data packet using a pre-built chip to obtain a simplified data packet, summarize the simplified data packets to obtain a simplified data packet set, and parse the simplified data packet set based on a pre-built user port to obtain a decoded data packet set;

[0179] The image reconstruction module 104 is used to obtain a chest electrical impedance image according to the decoded data packet set, and complete the compression and transmission of chest electrical impedance imager image data based on the chest electrical impedance image.

[0180] In detail, each module in the chest electrical impedance imaging image data compression transmission system 100 of the embodiment of the present invention is used in the same manner as described above. Figure 1 The chest electrical impedance tomography image data compression and transmission method described in the present invention is the same technical means and can produce the same technical effects, which will not be repeated here.

[0181] like Figure 3 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a method for compressing and transmitting chest electrical impedance tomography image data provided by an embodiment of the present invention.

[0182] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a chest electrical impedance tomography image data compression and transmission method program.

[0183] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 also includes an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the chest electrical impedance imaging image data compression and transmission method program, but also can be used to temporarily store data that has been output or is to be output.

[0184] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as chest electrical impedance imaging image data compression and transmission method programs, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0185] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0186] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0187] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0188] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0189] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0190] The chest electrical impedance imaging device image data compression and transmission method program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0191] receiving an image data compression instruction, starting a pre-built chest electrical impedance imager according to the image data compression instruction, acquiring an initial chest electrical impedance image according to the started chest electrical impedance imager, and performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map;

[0192] Acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map;

[0193] Acquiring a chest electrical impedance data set using a plurality of preset detection time periods and a target chest electrical impedance image;

[0194] Performing a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data;

[0195] A set of denoised chest electrical impedance data is extracted from the denoised chest electrical impedance data set in turn, and the following operations are performed on the extracted denoised chest electrical impedance data:

[0196] Acquiring a data packet according to the denoised chest electrical impedance data, and compressing the data packet using a pre-built chip to obtain a streamlined data packet;

[0197] Aggregating simplified data packets to obtain a simplified data packet set, parsing the simplified data packet set based on a pre-built user port to obtain a decoded data packet set;

[0198] A chest electrical impedance image is acquired according to the decoded data packet set, and compression and transmission of chest electrical impedance imager image data are completed based on the chest electrical impedance image.

[0199] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0200] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0201] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0202] receiving an image data compression instruction, starting a pre-built chest electrical impedance imager according to the image data compression instruction, acquiring an initial chest electrical impedance image according to the started chest electrical impedance imager, and performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map;

[0203] Acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map;

[0204] Acquiring a chest electrical impedance data set using a plurality of preset detection time periods and a target chest electrical impedance image;

[0205] Performing a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data;

[0206] A set of denoised chest electrical impedance data is extracted from the denoised chest electrical impedance data set in turn, and the following operations are performed on the extracted denoised chest electrical impedance data:

[0207] Acquiring a data packet according to the denoised chest electrical impedance data, and compressing the data packet using a pre-built chip to obtain a streamlined data packet;

[0208] Aggregating simplified data packets to obtain a simplified data packet set, parsing the simplified data packet set based on a pre-built user port to obtain a decoded data packet set;

[0209] A chest electrical impedance image is acquired according to the decoded data packet set, and compression and transmission of chest electrical impedance imager image data are completed based on the chest electrical impedance image.

[0210] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only illustrative, and actual implementation may have other division methods.

[0211] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0212] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0213] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0214] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A chest electrical impedance tomography image data compression and transmission method, characterized in that: The method comprises: receiving an image data compression instruction, starting a pre-built chest electrical impedance imager according to the image data compression instruction, acquiring an initial chest electrical impedance image according to the started chest electrical impedance imager, and performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map; Acquire a target chest electrical impedance image based on the chest electrical impedance segmentation map; Acquiring a chest electrical impedance data set using a plurality of preset detection time periods and a target chest electrical impedance image; Performing a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes multiple groups of chest electrical impedance data; A set of denoised chest electrical impedance data is extracted from the denoised chest electrical impedance data set in turn, and the following operations are performed on the extracted denoised chest electrical impedance data: Acquiring a data packet according to the denoised chest electrical impedance data, and compressing the data packet using a pre-built chip to obtain a streamlined data packet; Aggregating simplified data packets to obtain a simplified data packet set, parsing the simplified data packet set based on a pre-built user port to obtain a decoded data packet set; A chest electrical impedance image is acquired according to the decoded data packet set, and compression and transmission of chest electrical impedance imager image data are completed based on the chest electrical impedance image.

2. The chest electrical impedance tomography image data compression and transmission method according to claim 1, characterized in that: The method of compressing the data packet by using the pre-built chip to obtain a simplified data packet includes: Reading a reference frame from a data packet, wherein the data packet includes a plurality of unit frames, and the reference frame is the earliest unit frame in the data packet; Acquire a reference matrix according to the reference frame, and acquire an initial adjacent matrix based on a preset detection frame rate and the reference matrix, wherein the initial adjacent matrix is ​​a matrix corresponding to a next unit frame adjacent to the reference matrix in time, and all element positions in the adjacent matrix correspond one-to-one to all element positions in the reference matrix; The adjacent elements are extracted from the adjacent matrix in sequence, and the following operations are performed on the extracted adjacent elements: Obtaining the element sites of the adjacent elements in the adjacent matrix to obtain the target sites, extracting the corresponding element sites from the reference matrix based on the target sites to obtain the historical comparison sites, and extracting the elements in the reference matrix based on the historical comparison sites to obtain the reference elements; If the adjacent elements are not the same as the reference elements, difference data are constructed using the adjacent elements and the target site, and the difference data is filled into the pre-constructed blank difference text. After confirming that the adjacent elements in the adjacent matrix are all extracted, the filled difference text is obtained, and a compressed frame is obtained based on the filled difference text, wherein the filled difference text is the blank difference text after all the difference data in the adjacent matrix are filled, and the compressed frame includes a compressed frame header and one or more difference data, and the difference data includes two-byte row information, two-byte column information and four-byte difference value; Taking the adjacent matrix as the reference matrix, returning to the step of obtaining the initial adjacent matrix based on the preset detection frame rate and the reference matrix until the unit frame in the data packet is extracted; The reference frames and the compressed frames are aggregated in order of time from first to last to obtain a streamlined data packet.

3. The chest electrical impedance tomography image data compression and transmission method according to claim 2, characterized in that: The method of parsing and simplifying the data packet set based on the pre-built user port to obtain a decoded data packet set includes: Extract a reduced data packet from the reduced data packet set in turn, and perform the following operations on each extracted reduced data packet: Receiving a simplified data packet based on a user port, and reading a reference frame in the simplified data packet; Extract compressed frames from the streamlined data packets in sequence, and perform the following operations on the extracted compressed frames: Read the four-byte data of the compressed frame header to obtain the number of bytes of the compressed frame, and convert the number of bytes of the compressed frame into an integer format to obtain the length of the compressed frame; Perform one or more difference data divisions on the compressed frame length to obtain one or more difference data block sets, wherein the difference data corresponds to the difference data block set one by one, and the difference data block set includes a plurality of difference data blocks, and the plurality of difference data blocks are respectively row numbers, column numbers and difference values; The following operations are performed on one or more difference data block sets: Extracting row numbers and column numbers from the difference data block set, extracting a reference reference point from a reference matrix corresponding to the difference data based on the row numbers and column numbers, and replacing a reference element of the reference reference point with a difference value in the difference data block to obtain an updated reference frame; Summarize and integrate the updated reference frames to obtain new reference frames corresponding to one or more sets of difference data blocks; The new reference frames are summarized to obtain a new reference frame set corresponding to the simplified data packet set, and the new reference frame set is confirmed as a decoding data packet set, wherein the simplified data packets correspond to the new reference frames one by one.

4. The chest electrical impedance tomography image data compression and transmission method according to claim 3, characterized in that: The step of performing threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map comprises: The initial chest electrical impedance image is meshed to obtain a mesh image, and the boundary of the mesh image is identified by using a pre-built edge detection algorithm to obtain an image boundary contour; Constructing a reference coordinate system according to the grid image, wherein the center point of the initial chest electrical impedance image is the origin, the horizontal right direction of the initial chest electrical impedance image is the X-axis, and the vertical direction to the X-axis is the Y-axis; Obtain four quadrants of the reference coordinate system, wherein the four quadrants include: an upper right area of ​​the origin as the first quadrant, an upper left area of ​​the origin as the second quadrant, a lower left area of ​​the origin as the third quadrant, and a lower right area of ​​the origin as the fourth quadrant; Extract a target quadrant from the four quadrants in turn, and perform the following operations on the extracted target quadrants: Acquire an image boundary coordinate set of a target quadrant based on the reference coordinate system, the image boundary contour, and the grid atlas; Calculate the distance between each image boundary coordinate and the origin in the image boundary coordinate set to obtain a distance set, and extract the maximum distance from the distance set; Summarize the maximum distances to obtain a maximum distance set, and extract the maximum distance value from the maximum distance set; A segmentation threshold is set according to the maximum distance value, and the initial chest electrical impedance image is segmented using the segmentation threshold to obtain a chest electrical impedance segmentation map.

5. The chest electrical impedance tomography image data compression and transmission method according to claim 4, characterized in that: The distance between each image boundary coordinate in the image boundary coordinate set and the origin is calculated respectively to obtain a distance set, including: Extract one image boundary coordinate from the image boundary coordinate set in turn, and perform the following operations on each of the extracted image boundary coordinates: The distance between the image boundary coordinates and the origin is calculated using the pre-built Euclidean formula, where the Euclidean formula is as follows: Among them, d m Indicates the distance between the mth image boundary coordinate and the origin, x m Represents the horizontal coordinate of the mth image boundary coordinate, y m The ordinate of the mth image boundary coordinate, where m represents the index of the image boundary coordinate and n represents the total number of image boundary coordinates; Sum up the distances between the image boundary coordinates and the origin to get a distance set.

6. The chest electrical impedance tomography image data compression and transmission method according to claim 5, characterized in that: The performing a denoising operation on the chest electrical impedance dataset to obtain a denoised chest electrical impedance dataset comprises: Using the pre-constructed wavelet denoising, a denoising operation is performed on each chest electrical impedance data set in the chest electrical impedance data set to obtain an initial denoised data set; Obtaining the original power of the chest electrical impedance dataset and obtaining the denoised power of the initial denoised dataset; Calculate the signal-to-noise ratio of the original power and the denoised power; If it is confirmed that the signal-to-noise ratio is less than the preset signal-to-noise ratio threshold, return to the step of performing a denoising operation on each chest electrical impedance data in the chest electrical impedance data set using the pre-constructed wavelet denoising until the signal-to-noise ratio is greater than or equal to the preset signal-to-noise ratio threshold, thereby obtaining a denoised chest electrical impedance data set.

7. The chest electrical impedance tomography image data compression and transmission method according to claim 6, characterized in that: The calculating the signal-to-noise ratio of the original power and the denoised power includes: The signal-to-noise ratio of the original power to the denoised power is calculated using a pre-built signal-to-noise ratio formula, where the signal-to-noise ratio formula is as follows: Where X represents the signal-to-noise ratio, log 10 represents the logarithm with base 10, x i represents the i-th chest electrical impedance data, represents the i-th initial denoised data, N represents the total number in the chest electrical impedance data set, i represents the index of the chest electrical impedance data, P1 represents the original power, and P2 represents the denoised power.

8. The chest electrical impedance tomography image data compression and transmission method according to claim 7, characterized in that: The step of acquiring a target chest electrical impedance image based on the chest electrical impedance segmentation map comprises: Get the image size of the chest electrical impedance segmentation map and the image size range; Determine whether the image size is within the image size range; If it is confirmed that the image size is not within the image size range, the process returns to the step of performing threshold segmentation on the initial chest electrical impedance image until the image size is within the image size range, thereby obtaining a target chest electrical impedance image.

9. The chest electrical impedance tomography image data compression and transmission method according to claim 8, characterized in that: The obtaining of the image size range includes: Obtain multiple historical detection time periods and historical chest electrical impedance image sets; A historical detection time period is extracted from the multiple historical detection time periods in sequence, and the following operations are performed on each of the extracted historical detection time periods: Using the historical detection time period to detect the historical chest electrical impedance image set, a historical image size group is obtained, wherein the historical image size group includes: widths and heights of multiple historical image sizes; Summarize the historical image size groups to obtain a historical image size group set; Calculate the size average of each historical image size group in the historical image size group set to obtain a size average group; The maximum width average, maximum height average, minimum width average and minimum height average are extracted from the size average group, and the image size range is confirmed by the maximum width average, maximum height average, minimum width average and minimum height average.

10. A chest electrical impedance tomography image data compression and transmission system, characterized in that: The system comprises: A chest image acquisition module is used to receive an image data compression instruction, start a pre-built chest electrical impedance imager according to the image data compression instruction, obtain an initial chest electrical impedance image according to the started chest electrical impedance imager, perform threshold segmentation on the initial chest electrical impedance image to obtain a chest electrical impedance segmentation map, and obtain a target chest electrical impedance image based on the chest electrical impedance segmentation map; a data set generation module, used to obtain a chest electrical impedance data set by using a plurality of preset detection time periods and a target chest electrical impedance image, and to perform a denoising operation on the chest electrical impedance data set to obtain a denoised chest electrical impedance data set, wherein one detection time period corresponds to a group of 50 frames of denoised chest electrical impedance data, and the chest electrical impedance data set includes a plurality of groups of chest electrical impedance data; The data packet compression module is used to extract a set of denoised chest electrical impedance data from the denoised chest electrical impedance data set in turn, and perform the following operations on the extracted denoised chest electrical impedance data: obtain a data packet according to the denoised chest electrical impedance data, compress the data packet using a pre-built chip to obtain a simplified data packet, summarize the simplified data packets to obtain a simplified data packet set, and parse the simplified data packet set based on a pre-built user port to obtain a decoded data packet set; The image reconstruction module is used to obtain a chest electrical impedance image according to the decoded data packet set, and complete the compression and transmission of chest electrical impedance imager image data based on the chest electrical impedance image.

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