Full data recording method and system for breast cancer patient
By dividing breast cancer patient diagnosis and treatment data into multiple parts and using check codes hidden in the horizontal axis, altered image data is generated, solving the problem of data leakage being difficult to trace, and realizing the security and accountability of data sharing.
Patent Information
- Application Number
- CN202511622508.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-07
- Publication Date
- 2026-01-20
AI Technical Summary
When medical entities share breast cancer patient diagnosis and treatment data, data leaks are difficult to trace, the leaking entity cannot be identified, and responsibility is difficult to assign.
The diagnostic and treatment data is divided into diagnostic and treatment time series parameters, basic diagnostic and treatment data, and diagnostic and treatment image data. An offset diagnostic and treatment time series coordinate set is generated and a check code is implicitly contained in the horizontal coordinate. Altered image data is generated and synthesized into diagnostic and treatment data to be shared.
It enables data traceability, allowing for the rapid identification of those responsible for data breaches and ensuring the security of data sharing.
Smart Images
Figure CN121366686A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application belongs to the technical field of medical data records, and particularly relates to a breast cancer patient's full data record method and system. BACKGROUND
[0002] The breast cancer patient's full data record is a systematic collection of information that comprehensively reflects the entire process from diagnosis to treatment and follow-up of the patient. It usually includes the following core parts: first, basic information such as the patient's age, gender, occupation, etc.; second, the diagnosis and treatment process, which details the diagnosis date, surgical method, postoperative pathological results (such as tumor size, lymph node metastasis, hormone receptor status, etc.), and subsequent chemotherapy, radiotherapy, endocrine therapy or targeted therapy regimen and start and end time; third, follow-up and outcome, including regular review results, disease recurrence or metastasis, and patient survival status and time, etc. These data together constitute the key basis for evaluating efficacy, analyzing prognosis and guiding individualized treatment.
[0003] In the research process of the disease, multiple medical subjects share the patient diagnosis and treatment data saved by each other, and the medical subjects authorize each other, only the authorized person can access the corresponding patient diagnosis and treatment data, but after the medical subject obtains the corresponding patient diagnosis and treatment data, the data leakage is prone to occur, the subject of data leakage cannot be confirmed, and the responsibility division is difficult. SUMMARY
[0004] The purpose of the present application is to provide a breast cancer patient's full data record method, which aims to solve the problem of data leakage after the medical subject obtains the corresponding patient diagnosis and treatment data, the subject of data leakage cannot be confirmed, and the responsibility division is difficult.
[0005] The present application is implemented as follows: a breast cancer patient's full data record method, the method comprising: obtaining patient diagnosis and treatment data, dividing it into multiple diagnosis and treatment time sequence data based on the diagnosis and treatment stage, each diagnosis and treatment time sequence data containing all diagnosis and treatment information of the current stage; dividing the diagnosis and treatment time sequence data into diagnosis and treatment time sequence parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and constructing a set of corresponding diagnosis and treatment time sequence coordinates according to all diagnosis and treatment time sequence parameters; calling a preset check code, disassembling the check code, and fusing it to the abscissa of the coordinates in the diagnosis and treatment time sequence coordinate set to generate an offset diagnosis and treatment time sequence coordinate set; generating a modified string based on the check code, modifying the diagnosis and treatment image according to the modified string, outputting the modified image data, and synthesizing the to-be-shared diagnosis and treatment data according to the basic diagnosis and treatment data, the offset diagnosis and treatment time sequence coordinate set and the modified image data.
[0006] Preferably, the step of dividing the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data and diagnosis and treatment image data, constructing a set of corresponding diagnosis and treatment time series coordinate sets according to all diagnosis and treatment time series parameters, specifically comprises: The diagnosis and treatment time series data is analyzed, and the diagnosis and treatment parameters with continuity are extracted, which are recorded with time as the horizontal axis to obtain the diagnosis and treatment time series parameters; All images contained in the diagnosis and treatment time series data are extracted and included in the diagnosis and treatment image data; The time value of the diagnosis and treatment time series parameters is extracted as the horizontal coordinate value, and the corresponding diagnosis and treatment parameters are taken as the vertical coordinate value, and the diagnosis and treatment time series coordinate set is constructed.
[0007] Preferably, the step of calling the preset check code, disassembling the check code, and fusing it into the horizontal coordinate of the coordinate in the diagnosis and treatment time series coordinate set to generate the offset diagnosis and treatment time series coordinate set, specifically comprises: The preset check code is called and disassembled into offset characters of a preset length, and the offset characters are used to determine the horizontal coordinate offset of the diagnosis and treatment time series coordinate; The diagnosis and treatment time series coordinates are classified based on the type of diagnosis and treatment parameters, and a plurality of types of diagnosis and treatment coordinate sets are divided; Each time a set of diagnosis and treatment coordinate sets is called, the offset amount of the horizontal coordinate of each coordinate in the set is determined based on the offset character, and the offset diagnosis and treatment time series coordinate set is generated.
[0008] Preferably, the step of generating a modified string based on the check code, modifying the diagnosis and treatment image based on the modified string, outputting the modified image data, and synthesizing the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time series coordinate set and the modified image data, specifically comprises: The check code is converted into a binary character to obtain a modified string, a pixel modification mapping relationship is constructed, and the pixel modification value corresponding to the modified string is determined according to the pixel modification mapping relationship; The diagnosis and treatment image is extracted one by one, and the pixels in the diagnosis and treatment image are modified pixel by pixel based on the continuous pixel modification value to obtain the modified image data; The offset diagnosis and treatment time series coordinate set is called to fill the basic diagnosis and treatment data, and the modified image data is merged into the set to obtain the diagnosis and treatment data to be shared.
[0009] Preferably, different check codes are used for different data sharing parties.
[0010] Another object of the present application is a breast cancer patient's full data recording system, the system comprises: The data acquisition module is configured to acquire patient diagnosis and treatment data, divide the diagnosis and treatment data into a plurality of diagnosis and treatment time sequence data based on diagnosis and treatment stages, and each diagnosis and treatment time sequence data contains all diagnosis and treatment information of the current stage. The data division module is configured to divide the diagnosis and treatment time sequence data into diagnosis and treatment time sequence parameters, basic diagnosis and treatment data, and diagnosis and treatment image data, and construct a set of corresponding diagnosis and treatment time sequence coordinate sets according to all diagnosis and treatment time sequence parameters. The coordinate offset module is configured to call a preset check code, disassemble the check code, fuse the check code to the abscissa of the coordinates in the diagnosis and treatment time sequence coordinate set, and generate an offset diagnosis and treatment time sequence coordinate set. The data modification module is configured to generate a modified string based on the check code, modify the diagnosis and treatment image according to the modified string, output modified image data, and synthesize the diagnosis and treatment data to be shared according to the basic diagnosis and treatment data, the offset diagnosis and treatment time sequence coordinate set, and the modified image data.
[0011] Preferably, the data division module comprises: The time sequence parameter extraction unit is configured to analyze the diagnosis and treatment time sequence data, extract diagnosis and treatment parameters with continuity therein, record the diagnosis and treatment parameters with time as the abscissa, and obtain diagnosis and treatment time sequence parameters. The image data extraction unit is configured to extract all images contained in the diagnosis and treatment time sequence data and include the images in the diagnosis and treatment image data. The time sequence coordinate construction unit is configured to extract the time value of the diagnosis and treatment time sequence parameters as the abscissa coordinate value, extract the corresponding diagnosis and treatment parameters as the ordinate coordinate value, and construct a diagnosis and treatment time sequence coordinate set.
[0012] Preferably, the coordinate offset module comprises: The string disassembly unit is configured to call a preset check code, disassemble the check code into offset characters of a preset length, and use the offset characters to determine the abscissa offset of the diagnosis and treatment time sequence coordinates. The coordinate classification unit is configured to classify the diagnosis and treatment time sequence coordinates based on the types of the diagnosis and treatment parameters, and divide the diagnosis and treatment coordinates into a plurality of types. The data offset unit is configured to call a set of diagnosis and treatment coordinates each time, determine the abscissa offset of each coordinate in the set based on the offset characters, and generate an offset diagnosis and treatment time sequence coordinate set.
[0013] Preferably, the data modification module comprises: The mapping relationship construction unit is configured to convert the check code into a binary character to obtain a modified string, construct a pixel modification mapping relationship, and determine a pixel modification value corresponding to the modified string according to the pixel modification mapping relationship. The image processing unit is configured to extract the diagnosis and treatment images one by one, modify the pixels in the diagnosis and treatment images pixel by pixel based on the continuous pixel modification values, and obtain modified image data. The data sharing unit is used to fill the basic diagnosis and treatment data with the offset diagnosis and treatment time sequence coordinate set, and merge the modified image data into the basic diagnosis and treatment data, so as to obtain the diagnosis and treatment data to be shared.
[0014] Preferably, different check codes are used for different data sharing parties.
[0015] The breast cancer patient full data recording method provided by the application can realize the data traceability effect, can quickly determine the identity of the data leaker, and ensures the safety of data sharing. BRIEF DESCRIPTION OF DRAWINGS
[0016] Figure 1 A flowchart of the breast cancer patient full data recording method provided by the embodiment of the application is provided. Figure 2 A flowchart of the step of dividing the diagnosis and treatment time sequence data into diagnosis and treatment time sequence parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and constructing a group of corresponding diagnosis and treatment time sequence coordinate sets according to all diagnosis and treatment time sequence parameters is provided. Figure 3 A flowchart of the step of calling the preset check code, disassembling the check code, fusing the check code into the abscissa of the coordinates in the diagnosis and treatment time sequence coordinate set, and generating the offset diagnosis and treatment time sequence coordinate set is provided. Figure 4 A flowchart of the step of generating a modified string based on the check code, performing modification processing on the diagnosis and treatment image according to the modified string, outputting the modified image data, and synthesizing the diagnosis and treatment data to be shared is provided. Figure 5 An architecture diagram of the breast cancer patient full data recording system provided by the embodiment of the application is provided. Figure 6 An architecture diagram of the data division module provided by the embodiment of the application is provided. Figure 7 An architecture diagram of the coordinate offset module provided by the embodiment of the application is provided. Figure 8 An architecture diagram of the data modification module provided by the embodiment of the application is provided. DETAILED DESCRIPTION
[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0018] like Figure 1 The diagram shown is a flowchart of a method for recording full data of breast cancer patients according to an embodiment of the present invention. The method includes: S100: Acquire patient treatment data and divide it into multiple treatment time series data based on the treatment stage. Each treatment time series data contains all treatment information for the current stage.
[0019] In this step, patient treatment data is acquired. All data generated throughout the entire treatment cycle of breast cancer patients is recorded. During the treatment process, different treatment stages will generate data for that period. That is, after the patient's data for a treatment stage is completed, treatment data belonging to that stage will be generated. Treatment data includes the patient's vital signs parameters at the current stage, such as blood pressure, heart rate, and weight; pathological characteristic parameters, such as histological type, tumor size, lymph node status, and histological grade; and treatment plan, such as treatment method, radiotherapy dosage, radiotherapy portion, and radiotherapy time. Each data point has a corresponding time, that is, the time when the data was generated.
[0020] S200 divides the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data, and diagnosis and treatment image data, and constructs a set of corresponding diagnosis and treatment time series coordinates based on all the diagnosis and treatment time series parameters.
[0021] In this step, the treatment time-series data is divided into treatment time-series parameters, basic treatment data, and treatment image data. The treatment time-series data is extracted, and for continuous data, it is divided into treatment time-series parameters, such as continuous weight monitoring results, heart rate monitoring results, weight detection results, tumor size, and radiotherapy dosage. Basic treatment data refers to data unrelated to time, such as descriptive information about the patient's condition and descriptive text about the surgical plan. Treatment image data refers to images generated during the treatment process, including chest CT images, ultrasound images, and mammogram images. Continuous parameters are extracted to construct treatment time-series parameters. Each treatment parameter is recorded in chronological order to generate a set of treatment time-series coordinates. All treatment time-series coordinates are then combined to obtain a set of treatment time-series coordinates.
[0022] S300 retrieves the preset check code, decomposes the check code, and merges it into the horizontal coordinate of the coordinate in the diagnosis and treatment time sequence coordinate set to generate an offset diagnosis and treatment time sequence coordinate set.
[0023] In this step, the preset check code is called, which is used to determine the identity of the medical subject to be shared this time, that is, each medical subject is assigned a unique check code, and the shared diagnosis and treatment data contains the above check code. If there is data leakage or illegal data sharing later, the identity of the data leaker can be determined according to the check code contained in the data, which plays a role in tracing. The check code is disassembled, and the abscissa of the coordinate in the diagnosis and treatment time sequence coordinate set is fine-tuned according to the check code, so as to implicitly contain the check code in the abscissa, so as to obtain the offset diagnosis and treatment time sequence coordinate set.
[0024] S400, generating a modified string based on the check code, modifying the diagnosis and treatment image according to the modified string, outputting the modified image data, and synthesizing the to-be-shared diagnosis and treatment data based on the basic diagnosis and treatment data, the offset diagnosis and treatment time sequence coordinate set and the modified image data.
[0025] In this step, a modified string is generated based on the check code, and the pixels in the diagnosis and treatment image are adjusted pixel by pixel. When adjusting, the characters in the modified string are read in turn, and then the pixels in the diagnosis and treatment image are read in turn. The modification method of the corresponding pixel is determined according to the character. The modification method is to adjust the value of one channel in the RGB color of the pixel. Accordingly, all diagnosis and treatment images are modified to obtain modified image data. The basic diagnosis and treatment data to be shared this time, the offset diagnosis and treatment time sequence coordinate set and the modified image data are fused together to obtain the to-be-shared diagnosis and treatment data. In the subsequent sharing process, the to-be-shared diagnosis and treatment data is sent to the corresponding medical subject. For the medical subject, the built-in check code cannot be perceived, and it does not affect the normal use of the data. Once data leakage occurs, the identity of the medical subject who leaks can be quickly located by extracting the check code.
[0026] As shown in Figure 2 As a preferred embodiment of the present application, the diagnosis and treatment time sequence data is divided into diagnosis and treatment time sequence parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and the step of constructing a set of corresponding diagnosis and treatment time sequence coordinate sets according to all diagnosis and treatment time sequence parameters specifically includes: S201, analyzing the diagnosis and treatment time sequence data, and extracting the diagnosis and treatment parameters with continuity, which are recorded with time as the abscissa to obtain the diagnosis and treatment time sequence parameters.
[0027] In this step, the diagnosis and treatment time series data is analyzed, and the continuity parameters are extracted, such as body weight, blood pressure, heart rate, tumor size and radiation dose, etc. The above diagnosis and treatment parameters are recorded in time sequence, such as the body weight at A1 time is a1, the body weight at A2 time is a2, the body weight at A3 time is a3, etc. Thus, all diagnosis and treatment time series parameters corresponding to this type of diagnosis and treatment parameters are obtained, that is, all time body weight is divided into a category, and all time tumor size data is divided into a category. The values of the diagnosis and treatment parameters and the corresponding data acquisition time are recorded.
[0028] S202, extract all images contained in the diagnosis and treatment time series data, and include them in the diagnosis and treatment image data.
[0029] S203, extract the time value of the diagnosis and treatment time series parameter, and take it as the horizontal coordinate value. The corresponding diagnosis and treatment parameter is taken as the vertical coordinate value, and the diagnosis and treatment time series coordinate set is constructed.
[0030] In this step, all images contained in the diagnosis and treatment time series data are extracted. When extracting the image, the background part of the image is identified. Specifically, the proportion of pure white pixels in the image is counted. When the proportion of pure white pixels is greater than a preset proportion, such as 50%, the image is discarded and not included in the diagnosis and treatment image data. Then, the diagnosis and treatment time series parameters are extracted one by one. For example, for a type of diagnosis and treatment time series parameter, tumor size, time is represented as T, and tumor size is represented as S. The corresponding diagnosis and treatment time series coordinate is represented as (T, S). This coordinate represents that at T time, the measured tumor size is S. If the tumor size is measured ten times, the number of diagnosis and treatment time series coordinates is 10 groups, that is, the number of diagnosis and treatment time series coordinates corresponding to the diagnosis and treatment parameter is 10. Similarly, the diagnosis and treatment time series coordinates corresponding to all other diagnosis and treatment parameters are determined, and all diagnosis and treatment time series coordinates are stored together to obtain the diagnosis and treatment time series coordinate set.
[0031] As shown in Figure 3 As a preferred embodiment of the present application, the step of calling the preset check code, disassembling the check code and merging it into the horizontal coordinate of the coordinate in the diagnosis and treatment time series coordinate set to generate the offset diagnosis and treatment time series coordinate set, specifically includes: S301, call the preset check code, and disassemble it into offset characters of a preset length. The offset character is used to determine the horizontal coordinate offset of the diagnosis and treatment time series coordinate.
[0032] In this step, the preset check code is called. The check code is a series of decimal strings, such as 2025821789, which contains 10 offset characters. The number of offset characters determines the offset of the corresponding horizontal coordinate.
[0033] S302, classify the diagnosis and treatment time series coordinates based on the type of diagnosis and treatment parameters, and divide to obtain multiple types of diagnosis and treatment coordinate sets.
[0034] In this step, the diagnosis and treatment time sequence coordinates are classified based on the type of diagnosis and treatment parameters, classified according to the diagnosis and treatment parameters, and all diagnosis and treatment time sequence coordinates corresponding to the diagnosis and treatment parameters are extracted and divided into a diagnosis and treatment coordinate set. The diagnosis and treatment coordinate set is used as a whole for subsequent offset.
[0035] S303, each time a group of diagnosis and treatment coordinate sets are called, the offset of the horizontal coordinate of each coordinate in the group is determined based on the offset character, and an offset diagnosis and treatment time sequence coordinate set is generated.
[0036] In this step, each time a group of diagnosis and treatment coordinate sets are called, the smallest time unit of the group of diagnosis and treatment coordinate sets is determined, such as minutes or seconds, and the corresponding offset unit is the same. The time sequence diagnosis and treatment coordinates in the diagnosis and treatment coordinate set are retrieved one by one, the horizontal coordinates are extracted, and an offset character is extracted in order. The offset amount is determined according to the offset character. For example, if the offset character is 5, it means that the offset needs to be 5 offset units. For example, if the horizontal coordinate is 10 hours 50 minutes 35 seconds, the offset horizontal coordinate is 10 hours 50 minutes 40 seconds. In order to reduce the offset amount, the character range of the check code can be limited, such as between 0 and 3. The check code can also be directly set to a binary string, so the offset amount is 0 or 1. After offset, the offset diagnosis and treatment time sequence coordinates are obtained. After all the coordinates of a diagnosis and treatment coordinate set are offset, the offset diagnosis and treatment time sequence coordinate set corresponding to the corresponding diagnosis and treatment parameter is obtained, and all the coordinates are processed accordingly.
[0037] As shown in Figure 4 As a preferred embodiment of the present application, the step of generating a modified string based on the check code, modifying the diagnosis image according to the modified string, and outputting the modified image data, and synthesizing the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time sequence coordinate set and the modified image data, specifically includes: S401, convert the check code to a binary character to obtain a modified string, and construct a pixel modification mapping relationship to determine the pixel modification value corresponding to the modified string.
[0038] In this step, the check code is converted to a binary character. If the check code directly uses a binary character, no conversion is needed. The modified string is obtained. The binary character contains 0 and 1. When modifying, a pixel modification mapping relationship is constructed. For example, 0 corresponds to reducing the R channel value of the RGB color of the pixel by 1, and 1 means increasing the R channel value by 1.
[0039] S402, extract the diagnosis image one by one, and modify the pixels in the diagnosis image pixel by pixel based on the continuous pixel modification value to obtain the modified image data.
[0040] In this step, each diagnostic image is extracted, and the checksum is repeatedly spliced to obtain continuous pixel alteration values, such as 10101001010010101... Pixels in the diagnostic images are retrieved one by one, and the corresponding color channel value of the pixel is changed according to its pixel alteration value. For example, the R channel value is reduced from 201 to 200. The altered image has very little color change and does not affect its normal use. After processing all diagnostic images, the altered image data is obtained.
[0041] S403, retrieve the offset diagnosis and treatment time series coordinate set to fill the basic diagnosis and treatment data, and merge the altered image data into it to obtain the diagnosis and treatment data to be shared.
[0042] In this step, the set of offset diagnosis and treatment time series coordinates is retrieved to populate the basic diagnosis and treatment data. Each offset diagnosis and treatment time series coordinate is retrieved, and the corresponding time value is inserted into the corresponding position in the basic diagnosis and treatment data. Similarly, the altered image is retrieved and inserted into the basic diagnosis and treatment data to obtain a complete set of shared diagnosis and treatment data, so as to facilitate the subsequent sharing and traceability of the data.
[0043] like Figure 5 As shown, this invention provides a comprehensive data recording system for breast cancer patients, the system comprising: The data acquisition module 100 is used to acquire patient diagnosis and treatment data, and divides it into multiple diagnosis and treatment time series data based on the diagnosis and treatment stage. Each diagnosis and treatment time series data contains all diagnosis and treatment information of the current stage.
[0044] In this system, the data acquisition module 100 acquires patient treatment data and records all data generated during the entire treatment cycle of breast cancer patients. During the treatment process, different treatment stages will generate data for that period. That is, after the patient's data for a treatment stage ends, treatment data belonging to that stage will be generated. Treatment data includes the patient's vital signs parameters at the current stage, such as blood pressure, heart rate, and weight; pathological characteristic parameters, such as histological type, tumor size, lymph node status, and histological grade; and treatment plan, such as treatment method, radiotherapy dosage, radiotherapy portion, and radiotherapy time. Each piece of data has a corresponding time, that is, the time when the data was generated.
[0045] The data partitioning module 200 is used to divide the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and to construct a set of corresponding diagnosis and treatment time series coordinates based on all the diagnosis and treatment time series parameters.
[0046] In the system, the data division module 200 divides the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data, and diagnosis and treatment image data, extracts the diagnosis and treatment time series data, and divides the continuous data into diagnosis and treatment time series parameters, such as continuous body weight monitoring results, heart rate monitoring results, body weight detection results, tumor size, radiotherapy measurement, etc. The basic diagnosis and treatment data are data unrelated to time, such as description information of the patient's state and description text of the surgical plan. The diagnosis and treatment image data are images generated during the diagnosis and treatment process, including chest CT images, ultrasound images, and breast X-ray detection images. The continuous parameters are extracted to construct diagnosis and treatment time series parameters, and each diagnosis and treatment parameter is recorded in chronological order to generate a set of diagnosis and treatment time series coordinates. All diagnosis and treatment time series coordinates are combined to obtain a diagnosis and treatment time series coordinate set.
[0047] The coordinate offset module 300 is configured to call a preset check code, disassemble the check code, and fuse the check code into the abscissa of the coordinates in the diagnosis and treatment time series coordinate set to generate an offset diagnosis and treatment time series coordinate set.
[0048] In the system, the coordinate offset module 300 calls a preset check code. The check code is used to determine the identity of the medical subject to be shared this time. Each medical subject is assigned a unique check code, and the diagnosis and treatment data shared by the medical subject contains the check code. If there is data leakage or illegal sharing of data in the future, the identity of the data leaker can be determined according to the check code contained in the data, which plays a role in tracing the source. The check code is disassembled, and the abscissa of the coordinates in the diagnosis and treatment time series coordinate set is fine-tuned according to the check code, so that the check code is hidden in the abscissa, and an offset diagnosis and treatment time series coordinate set is obtained.
[0049] The data modification module 400 is configured to generate a modified string based on the check code, modify the diagnosis and treatment image according to the modified string, output modified image data, and synthesize the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time series coordinate set, and the modified image data.
[0050] In the system, the data modification module 400 generates a modified string based on the check code, and adjusts pixels in the diagnosis and treatment image pixel by pixel according to the modified string. When adjusting, the characters in the modified string are read in sequence, and then the pixels in the diagnosis and treatment image are read in sequence. The modification method of the corresponding pixel is determined according to the character. The modification method is to adjust the value of one channel in the RGB color of the pixel. Accordingly, all diagnosis and treatment images are modified to obtain modified image data. The base diagnosis and treatment data, the offset diagnosis and treatment time sequence coordinate set and the modified image data to be shared are fused together to obtain the diagnosis and treatment data to be shared. In the subsequent sharing process, the diagnosis and treatment data to be shared is sent to the corresponding medical subject. For the medical subject, the built-in check code cannot be perceived, and does not affect the normal use of the data. Once data leakage occurs, the identity of the medical subject where the leakage occurs can be quickly located by extracting the check code.
[0051] As shown in Figure 6 , as a preferred embodiment of the present application, the data division module 200 comprises: The time sequence parameter extraction unit 201 is used for analyzing the diagnosis and treatment time sequence data, extracting the diagnosis and treatment parameters with continuity therein, recording the diagnosis and treatment parameters with time as the horizontal axis, and obtaining the diagnosis and treatment time sequence parameters.
[0052] In the module, the time sequence parameter extraction unit 201 analyzes the diagnosis and treatment time sequence data, extracts the continuity parameters therein, extracts parameters such as body weight, blood pressure, heart rate, tumor size and radiation dose, and takes them as diagnosis and treatment parameters. The above diagnosis and treatment parameters are recorded in time sequence, such as body weight a1 at A1 time, body weight a2 at A2 time, body weight a3 at A3 time, etc. Thus, all diagnosis and treatment time sequence parameters corresponding to this type of diagnosis and treatment parameters are obtained, i.e. all time body weight is divided into a category, all time tumor size data is divided into a category, and the values of the diagnosis and treatment parameters and the corresponding data acquisition time are recorded.
[0053] The image data extraction unit 202 is used for extracting all images contained in the diagnosis and treatment time sequence data and including them in the diagnosis and treatment image data.
[0054] The time sequence coordinate construction unit 203 is used for extracting the time value of the diagnosis and treatment time sequence parameters as the horizontal axis coordinate value, taking the corresponding diagnosis and treatment parameters as the vertical axis coordinate value, and constructing the diagnosis and treatment time sequence coordinate set.
[0055] In the module, all images contained in the diagnosis and treatment time sequence data are extracted, and when the images are extracted, the background part of the image is identified. Specifically, the proportion of pure white pixels in the image is counted, and when the proportion of pure white pixels is greater than a preset proportion, such as 50%, the image is discarded and not included in the diagnosis and treatment image data. Subsequently, diagnosis and treatment time sequence parameters are extracted one by one. For example, for a type of diagnosis and treatment time sequence parameter, tumor size, time is represented as T, and tumor size is represented as S. The corresponding diagnosis and treatment time sequence coordinates are represented as (T, S). The coordinates represent that at time T, the measured tumor size is S. If the tumor size is measured ten times, the number of diagnosis and treatment time sequence coordinates is 10 groups, that is, the number of diagnosis and treatment time sequence coordinates corresponding to the diagnosis and treatment parameter is 10. Similarly, determine the diagnosis and treatment time sequence coordinates corresponding to all other diagnosis and treatment parameters. Store all diagnosis and treatment time sequence coordinates together to obtain a diagnosis and treatment time sequence coordinate set.
[0056] As shown in Figure 7 , as a preferred embodiment of the present application, the coordinate offset module 300 comprises: The string disassembling unit 301 is configured to call a preset check code and disassemble it into offset characters of a preset length. The offset characters are used to determine the horizontal coordinate offset of the diagnosis and treatment time sequence coordinates.
[0057] In this module, the string disassembling unit 301 calls a preset check code, which is a series of decimal strings, such as 2025821789, which contains 10 offset characters. The number of offset characters determines the offset of the corresponding horizontal coordinate.
[0058] The coordinate classification unit 302 is configured to classify the diagnosis and treatment time sequence coordinates based on the type of diagnosis and treatment parameters, and divide to obtain a plurality of types of diagnosis and treatment coordinate sets.
[0059] In this module, the coordinate classification unit 302 classifies the diagnosis and treatment time sequence coordinates based on the type of diagnosis and treatment parameters. All diagnosis and treatment time sequence coordinates corresponding to the diagnosis and treatment parameters are extracted and divided into a diagnosis and treatment coordinate set. Subsequently, the diagnosis and treatment coordinate set is offset as a whole.
[0060] The data offset unit 303 is configured to call a group of diagnosis and treatment coordinate sets each time, determine the horizontal coordinate offset of each coordinate based on the offset character, and generate an offset diagnosis and treatment time sequence coordinate set.
[0061] In the module, the data offset unit 303 calls a set of diagnosis and treatment coordinate set each time, determines the minimum time unit of the set of diagnosis and treatment coordinate set, such as minute or second, and the corresponding offset unit is the same, calls the time sequence diagnosis and treatment coordinates in the diagnosis and treatment coordinate set one by one, extracts the abscissa, extracts an offset character in order, determines the offset according to the offset character, such as the offset character is 5, which means that the offset is 5 offset units this time, such as the abscissa is 10 hours 50 minutes 35 seconds, and the abscissa after the offset is 10 hours 50 minutes 40 seconds. In order to reduce the offset, the character range of the check code can be limited, such as between 0-3, or the check code can be directly set to a binary string, so that the offset is 0 or 1. After the offset, the offset diagnosis time sequence coordinate set is obtained, and all the coordinates are processed according to the corresponding offset diagnosis time sequence coordinate set.
[0062] As shown in Figure 8 , as a preferred embodiment of the present application, the data transformation module 400 comprises: The mapping relationship construction unit 401 is used for converting the check code into a binary character to obtain a transformation string, constructing a pixel transformation mapping relationship, and determining the pixel transformation value corresponding to the transformation string according to the pixel transformation mapping relationship.
[0063] In the module, the mapping relationship construction unit 401 converts the check code into a binary character, and if the check code directly uses a binary character, no conversion is needed. The binary character contains 0 and 1, so when transforming, a pixel transformation mapping relationship is constructed, such as 0 corresponding to reducing the R channel value of the RGB color of the pixel by 1, and 1 representing increasing the R channel value by 1.
[0064] The image processing unit 402 is used for extracting diagnosis and treatment images one by one, performing pixel-by-pixel transformation processing on the pixels in the diagnosis and treatment images based on the continuous pixel transformation values, and obtaining transformed image data.
[0065] In the module, the image processing unit 402 extracts diagnosis and treatment images one by one, repeatedly splices the check code to obtain continuous pixel transformation values, such as 10101001010010101……, and calls the pixels in the diagnosis and treatment images one by one. According to the corresponding pixel transformation value, the corresponding color channel value of the pixel is changed, such as reducing the R channel value from 201 to 200. The color change of the transformed image is very low after the change, which does not affect its normal use. After processing all the diagnosis and treatment images, the transformed image data is obtained.
[0066] The data sharing unit 403 is used for calling the offset diagnosis time sequence coordinate set to fill the basic diagnosis and treatment data, and merging the transformed image data into it to obtain the diagnosis and treatment data to be shared.
[0067] In the module, the data sharing unit 403 calls the offset diagnosis and treatment time sequence coordinate set to fill the basic diagnosis and treatment data, calls each offset diagnosis and treatment time sequence coordinate, inserts the time value corresponding to the numerical value into the corresponding position of the basic diagnosis and treatment data, and similarly, calls the modified image and inserts it into the basic diagnosis and treatment data to obtain a complete shared diagnosis and treatment data, so as to facilitate subsequent sharing and tracing of the data.
[0068] The above only describes the preferred embodiments of the present application and is not used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims
1. A method of recording all data of a breast cancer patient, characterized by, The method comprises: acquiring patient diagnosis and treatment data, dividing the diagnosis and treatment data into multiple diagnosis and treatment time series data based on diagnosis and treatment stages, each diagnosis and treatment time series data containing all diagnosis and treatment information of the current stage; dividing the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and constructing a set of corresponding diagnosis and treatment time series coordinates according to all diagnosis and treatment time series parameters; calling a preset check code, disassembling the check code, fusing the check code into the abscissa of the coordinates in the diagnosis and treatment time series coordinate set, and generating an offset diagnosis and treatment time series coordinate set; generating a modified string based on the check code, modifying the diagnosis and treatment image according to the modified string, outputting modified image data, and synthesizing the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time series coordinate set and the modified image data.
2. The method for recording full data of breast cancer patients according to claim 1, characterized in that, The step of dividing the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data and diagnosis and treatment image data, and constructing a set of corresponding diagnosis and treatment time series coordinates according to all diagnosis and treatment time series parameters, specifically comprises: analyzing the diagnosis and treatment time series data, extracting diagnosis and treatment parameters with continuity therefrom, recording the diagnosis and treatment parameters with time as the horizontal axis to obtain diagnosis and treatment time series parameters; extracting all images contained in the diagnosis and treatment time series data and including them in the diagnosis and treatment image data; extracting the time value of the diagnosis and treatment time series parameters as the horizontal axis coordinate value, and the corresponding diagnosis and treatment parameters as the vertical axis coordinate value to construct the diagnosis and treatment time series coordinate set.
3. The method of claim 1, wherein the data is obtained from a plurality of sources. The step of calling a preset check code, disassembling the check code, fusing the check code into the abscissa of the coordinates in the diagnosis and treatment time series coordinate set, and generating an offset diagnosis and treatment time series coordinate set, specifically comprises: calling a preset check code, disassembling the check code into offset characters of a preset length, and the offset characters are used to determine the abscissa offset of the diagnosis and treatment time series coordinates; classifying the diagnosis and treatment time series coordinates based on the types of the diagnosis and treatment parameters to divide the diagnosis and treatment coordinates into multiple types; each time a set of diagnosis and treatment coordinates is called, the offset of the abscissa of each coordinate in the set is determined based on the offset characters to generate an offset diagnosis and treatment time series coordinate set.
4. The method of claim 1, wherein the breast cancer patient's full data record is characterized by, The step of generating a modified string based on the check code, modifying the diagnosis and treatment image according to the modified string, outputting modified image data, and synthesizing the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time series coordinate set and the modified image data, specifically comprises: converting the check code into a binary character to obtain a modified string, constructing a pixel modification mapping relationship, and determining the pixel modification value corresponding to the modified string according to the pixel modification mapping relationship; extracting the diagnosis and treatment image one by one, performing pixel-by-pixel modification processing on the pixels in the diagnosis and treatment image based on the continuous pixel modification value to obtain modified image data; calling the offset diagnosis and treatment time series coordinate set to fill the basic diagnosis and treatment data, and merging the modified image data to obtain the diagnosis and treatment data to be shared.
5. The method of claim 1, wherein the breast cancer patient's full data record is characterized by, Different check codes are used for different data sharing parties.
6. A total data recording system for breast cancer patients, characterized by The system comprises: a data acquisition module for acquiring patient diagnosis and treatment data, dividing the diagnosis and treatment data into multiple diagnosis and treatment time series data based on diagnosis and treatment stages, each diagnosis and treatment time series data containing all diagnosis and treatment information of the current stage; The data division module is configured to divide the diagnosis and treatment time series data into diagnosis and treatment time series parameters, basic diagnosis and treatment data, and diagnosis and treatment image data, and construct a set of corresponding diagnosis and treatment time series coordinate sets according to all diagnosis and treatment time series parameters. The coordinate offset module is configured to call a preset check code, disassemble the check code, fuse the check code to the abscissa of the coordinates in the diagnosis and treatment time series coordinate sets, and generate offset diagnosis and treatment time series coordinate sets. The data modification module is configured to generate a modified string based on the check code, perform modification processing on the diagnosis and treatment image according to the modified string, output modified image data, and synthesize the diagnosis and treatment data to be shared based on the basic diagnosis and treatment data, the offset diagnosis and treatment time series coordinate sets, and the modified image data.
7. The complete data record system of a breast cancer patient according to claim 6, characterized in that, The data division module includes: The time series parameter extraction unit is configured to analyze the diagnosis and treatment time series data, extract diagnosis and treatment parameters with continuity, record the diagnosis and treatment parameters with time as the horizontal axis, and obtain diagnosis and treatment time series parameters. The image data extraction unit is configured to extract all images contained in the diagnosis and treatment time series data and include the images in the diagnosis and treatment image data. The time series coordinate construction unit is configured to extract the time value of the diagnosis and treatment time series parameters, use the time value as the horizontal axis coordinate value, use the corresponding diagnosis and treatment parameters as the vertical axis coordinate value, and construct diagnosis and treatment time series coordinate sets.
8. The complete data record system of a breast cancer patient according to claim 6, characterized in that, The coordinate offset module includes: The string disassembly unit is configured to call a preset check code, disassemble the check code into offset characters of a preset length, and use the offset characters to determine the abscissa offset of the diagnosis and treatment time series coordinates. The coordinate classification unit is configured to classify the diagnosis and treatment time series coordinates based on the types of the diagnosis and treatment parameters, and divide the diagnosis and treatment coordinates into multiple types of diagnosis and treatment coordinate sets. The data offset unit is configured to call a set of diagnosis and treatment coordinate sets each time, determine the abscissa offset of each coordinate in the diagnosis and treatment coordinate sets based on the offset characters, and generate offset diagnosis and treatment time series coordinate sets.
9. The complete data record system of a breast cancer patient according to claim 6, characterized in that, The data modification module includes: The mapping relationship construction unit is configured to convert the check code into a binary character to obtain a modified string, construct a pixel modification mapping relationship, and determine the pixel modification value corresponding to the modified string according to the pixel modification mapping relationship. The image processing unit is configured to extract diagnosis and treatment images one by one, perform pixel-by-pixel modification processing on the pixels in the diagnosis and treatment images based on continuous pixel modification values, and obtain modified image data. The data sharing unit is configured to call the offset diagnosis and treatment time series coordinate sets to fill the basic diagnosis and treatment data, and merge the modified image data into the offset diagnosis and treatment time series coordinate sets to obtain diagnosis and treatment data to be shared.
10. The complete data record system of breast cancer patients according to claim 6, characterized in that, Different check codes are used for different data sharing parties.