CN117272393A - Method for checking medical images across hospitals by scanning codes in regional intranet - Google Patents
Method for checking medical images across hospitals by scanning codes in regional intranet Download PDFInfo
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Abstract
The invention discloses a method for referring to medical images across hospitals by regional intranet code scanning, which relates to the field of medical image sharing and comprises the following steps: firstly, a first inquiry request sent to a server side by scanning a first report form by a code scanning device of a first inquiry side is received; then, according to the first image single code, acquiring a first image original image corresponding to the first image single code from an intranet database at a server side; then, modifying a first unique identification code of the inquiring applicant into a non-sensitive area of the first image original picture and generating a second image subgraph corresponding to the first image original picture; and finally, according to the first query request, sending the second image sub-graph to the first query end. According to the invention, when a requester inquires the medical image, the system modifies the medical image to generate a new image slightly different from the original image, so that the source of the leaked requester of the image can be obtained in the later tracing, and the privacy security of the medical image data can be effectively improved.
Description
Technical Field
The invention relates to the field of medical data, in particular to a method for cross-hospital medical image review by regional intranet code scanning.
Background
At present, hospitals in various places are already built with Internet digital image services, and doctors and patients can directly browse image inspection data by scanning the two-dimensional codes on the report; so at present, when the patient goes to the hospital for a consultation, the traditional film images are not carried, and doctors look up the images through the Internet digital image service.
Although the convenience of the patient is improved to a certain extent, the privacy safety problem is brought to a certain extent, the medical image or the image is leaked from a certain channel, and the original image obtained by scanning codes in the prior art is consistent, so that the specific channel or individual leaked can not be tracked.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the present invention aims to provide a method for searching medical images across hospitals by scanning codes in an area, which aims to modify and mark the medical images to generate a new image slightly different from an original image when a requester searches the medical images, so that the source of a leaked requester of the image can be known in the later tracing, and the privacy security of medical image data can be improved to a certain extent. Particularly, when cross-hospital data transmission is carried out, the problem of liability division of the related medical data is solved and the safety of the medical data can be improved.
In order to achieve the above purpose, the invention provides a method for viewing medical images across hospitals by regional intranet scanning, which comprises the following steps:
step S1, a server receives a first query request sent to the server by scanning a first report by a code scanning device of the first query end; the first query request comprises a query requester and a first image list code of the first report list;
step S2, the server acquires a first image original picture corresponding to the first image single code from an intranet database of the server according to the first image single code;
step S3, the server obtains a non-sensitive area of the first image original picture according to the image type of the first image original picture; generating a first unique identification code corresponding to the ID of the query requester through hash operation according to the query requester; modifying the first unique identification code into the non-sensitive area and generating a second image subgraph corresponding to the first image original picture;
step S4, the server side sends the second image sub-graph to the first query side according to the first query request;
the operation flow of modifying the first unique identification code into the non-sensitive area and generating a second image sub-image corresponding to the first image original image comprises the following steps:
step S31, the non-sensitive area is obtained, partial or all areas of the non-sensitive area are divided according to the binary bit number length of the first unique identification code, and a non-sensitive subarea with the same binary bit number length as the first unique identification code is formed; wherein the number of detachable areas of the non-sensitive area is greater than the binary digit length of the first unique identification code;
step S32, determining gray scale offset of each non-sensitive subarea according to the value of 0 and the value of 1 on each bit of the first unique identification code; wherein, the value of 0 corresponds to the first gray level offset and the value of 1 corresponds to the second gray level offset;
step S33, judging whether the original average gray value of each non-sensitive subarea is larger than a first preset value, and modifying the gray value of each non-sensitive subarea to obtain the second image subgraph; and in response to the original average gray value being larger than the first preset value, positively shifting the gray of the non-sensitive subarea according to the gray offset, and otherwise, negatively shifting the gray of the non-sensitive subarea according to the gray offset.
In the technical scheme, the non-sensitive area of the original image of the first image is obtained, and the identification code information of the inquiring requester is modified on the non-sensitive area, so that the leakage source of the medical image can be traced later, and the data security of the medical image is improved; particularly, when cross-hospital data is leaked, the leaked responsibility units are effectively divided, and the data security is improved. Meanwhile, in the technical scheme, the non-sensitive area is divided into a plurality of sub-areas, and the unique identification code is modified into the medical image map in a gray level offset mode, so that the medical image is prevented from being modified too much, and the purpose of identifying the consulting requester can be achieved. Meanwhile, the sharpening effect of medical influence is improved, the fidelity is improved, the original higher gray value area is enhanced, the original lower gray value area is negatively offset, and the possibility of contrast distortion is reduced.
In a specific embodiment, the step S31 further includes:
step 311, acquiring the non-sensitive area, and dividing the non-sensitive sub-area in the non-sensitive area based on a boundary finding algorithm.
In the technical scheme, the non-sensitive subareas are divided by the boundary searching algorithm, so that sharpening processing in the subsequent gray level offset is facilitated, and the distortion problem caused by dividing the non-edges into different subareas to offset is reduced.
In one embodiment, the method comprises:
s5, the server side acquires the second image subgraph to be verified, extracts image characteristics of the second image subgraph in a sensitive area, and identifies the first image original image corresponding to the second image subgraph in the intranet database according to the image characteristics;
and S6, the server extracts each non-sensitive subarea and the corresponding gray level offset according to the first image original image and the second image subgraph, generates the first unique identification code, and matches the query requester in the intranet database according to the first unique identification code.
In the technical scheme, the query source of the image subgraph is obtained by comparing the image subgraph with the image original image, so that the traceability and the accountability problem during the leakage of the query are facilitated, and the safety of medical image data is effectively improved.
In a specific embodiment, the gray scale value of the first gray scale offset is 0-4, and the gray scale value of the second gray scale offset is 6-10.
In the technical scheme, the offset below 10 gray levels is set, so that the distortion of medical images is avoided.
In a specific embodiment, the non-sensitive area is a continuous area or a discontinuous area.
In a specific embodiment, in the step S32, the gray scale offset is an overall offset or a non-uniformity offset of the non-sensitive sub-area; wherein when the gray scale shift amount is a non-uniformity shift, an edge region of the non-sensitive sub-region tends to be non-shifted, and a center region of the non-sensitive sub-region tends to be shifted.
In the technical scheme, the offset is arranged in the central area of the non-sensitive subarea, so that the gray level smoothness between the subareas is improved, the pixel mutation of the subareas is avoided, and the possibility of directly seeing the subareas from an image subgraph through naked eyes for modification is reduced.
The invention has the beneficial effects that: 1. according to the invention, the non-sensitive area of the original image of the first image is obtained, and the identification code information of the inquiring requester is modified on the non-sensitive area, so that the leakage source of the medical image can be traced later, and the data security of the medical image is improved; particularly, when cross-hospital data is leaked, the leaked responsibility units are effectively divided, and the data security is improved. Meanwhile, in the invention, the non-sensitive area is divided into a plurality of subareas, and the unique identification code is modified into the medical image map in the form of gray level offset, so that on one hand, the medical image is prevented from being modified too much, and on the other hand, the purpose of identifying the consulting requester can be achieved. Meanwhile, the sharpening effect of medical influence is improved, the fidelity is improved, the original higher gray value area is enhanced, the original lower gray value area is negatively offset, and the possibility of contrast distortion is reduced. 2. In the invention, the query source of the image subgraph is obtained by comparing the image subgraph with the image original image, so that the traceability and the accountability problem during the leakage of query are facilitated, and the safety of medical image data is effectively improved.
Drawings
FIG. 1 is a flow chart of a method for referring to medical images across hospitals by regional intranet scanning codes according to an embodiment of the present invention;
fig. 2 is a flow chart of a specific modification method of non-sensitive subareas of a cross-hospital reference medical image by regional intranet scanning according to an embodiment of the present invention.
Detailed Description
The invention discloses a method for cross-hospital medical image review by regional intranet code scanning, and a person skilled in the art can refer to the content of the text and properly improve the technical details. It is expressly noted that all such similar substitutions and modifications will be apparent to those skilled in the art, and are deemed to be included in the present invention. While the methods and applications of this invention have been described in terms of preferred embodiments, it will be apparent to those skilled in the relevant art that variations and modifications can be made in the methods and applications described herein, and in the practice and application of the techniques of this invention, without departing from the spirit or scope of the invention.
Therefore, an embodiment of the present invention provides a method for scanning codes across regional intranets and referring to medical images in hospitals, as shown in fig. 1-2, the method includes:
step S1, a server receives a first query request sent to the server by scanning a first report by a code scanning device of the first query end; the first query request comprises a query requester and a first image list code of the first report list;
step S2, the server acquires a first image original picture corresponding to the first image single code from an intranet database of the server according to the first image single code;
step S3, the server obtains a non-sensitive area of the first image original picture according to the image type of the first image original picture; generating a first unique identification code corresponding to the ID of the query requester through hash operation according to the query requester; modifying the first unique identification code into the non-sensitive area and generating a second image subgraph corresponding to the first image original picture;
in practice, the first unique identification code may be generated by directly performing a hash algorithm according to the query requester, or may be generated by performing a hash algorithm according to the ID of the query requester; and, the relevant matching data may be stored in an intranet database after generation;
furthermore, the non-sensitive areas of different medical images may be different; for example, chest radiography images, bone orthopaedics images, etc., the image area required to be photographed in a specific medical diagnosis process can be determined as a sensitive area, and other areas can be correspondingly set as non-sensitive areas;
step S4, the server side sends the second image sub-graph to the first query side according to the first query request;
the operation flow of modifying the first unique identification code into the non-sensitive area and generating a second image sub-image corresponding to the first image original image comprises the following steps:
step S31, the non-sensitive area is obtained, partial or all areas of the non-sensitive area are divided according to the binary bit number length of the first unique identification code, and a non-sensitive subarea with the same binary bit number length as the first unique identification code is formed; wherein the number of detachable areas of the non-sensitive area is greater than the binary digit length of the first unique identification code;
typically, the first unique identification code may be 32 bits, 64 bits, or 128 bits; the resolution of the medical influence is higher, and each non-sensitive subarea can adopt a single pixel point or 10 multiplied by 10 pixel points as a subarea; the heterologous region can also be used as a non-sensitive subregion; in addition, the whole non-sensitive area can be directly made of a plurality of rows of continuous pixels, or can be arranged in a blocking way;
step S32, determining gray scale offset of each non-sensitive subarea according to the value of 0 and the value of 1 on each bit of the first unique identification code; wherein, the value of 0 corresponds to the first gray level offset and the value of 1 corresponds to the second gray level offset; the offset is determined first, and whether the offset is positive offset or negative offset is determined in the following step S33;
step S33, judging whether the original average gray value of each non-sensitive subarea is larger than a first preset value, and modifying the gray value of each non-sensitive subarea to obtain the second image subgraph; and in response to the original average gray value being larger than the first preset value, positively shifting the gray of the non-sensitive subarea according to the gray offset, and otherwise, negatively shifting the gray of the non-sensitive subarea according to the gray offset.
In this embodiment, the step S31 further includes:
step 311, acquiring the non-sensitive area, and dividing the non-sensitive sub-area in the non-sensitive area based on a boundary finding algorithm.
It should be noted that, when the number of the non-sensitive sub-regions is insufficient after the boundary is divided, the non-sensitive sub-regions after the boundary is divided may be directly divided twice so as to meet the bit number requirement of the first unique identification code.
In this embodiment, the method includes:
s5, the server side acquires the second image subgraph to be verified, extracts image characteristics of the second image subgraph in a sensitive area, and identifies the first image original image corresponding to the second image subgraph in the intranet database according to the image characteristics;
in addition, in a specific example, the corresponding first influence original graph can be directly queried on the intranet server through the report number on the second influence subgraph, which is not limited in practice by the present invention.
And S6, the server extracts each non-sensitive subarea and the corresponding gray level offset according to the first image original image and the second image subgraph, generates the first unique identification code, and matches the query requester in the intranet database according to the first unique identification code.
In this embodiment, the gray scale value of the first gray scale offset is 0-4, and the gray scale value of the second gray scale offset is 6-10.
Optionally, the non-sensitive area is a continuous area or a discontinuous area.
Optionally, in the step S32, the gray scale offset is an overall offset or a non-uniformity offset of the non-sensitive sub-area; wherein when the gray scale shift amount is a non-uniformity shift, an edge region of the non-sensitive sub-region tends to be non-shifted, and a center region of the non-sensitive sub-region tends to be shifted. In practice, the present invention does not limit whether the gray scale offset is an integral offset or an offset is performed on a portion of the pixel points in the sub-area according to actual needs.
According to the embodiment, the non-sensitive area of the original image of the first image is obtained, and the identification code information of the inquiring requester is modified on the non-sensitive area, so that the leakage source of the medical image can be traced later, and the data security of the medical image is improved; particularly, when cross-hospital data is leaked, the leaked responsibility units are effectively divided, and the data security is improved. Meanwhile, in the embodiment, the non-sensitive area is divided into a plurality of sub-areas, and the unique identification code is modified into the medical image map in the form of gray level offset, so that on one hand, the medical image is prevented from being modified too much, and on the other hand, the purpose of identifying the consulting requester can be achieved. Meanwhile, the sharpening effect of medical influence is improved, the fidelity is improved, the original higher gray value area is enhanced, the original lower gray value area is negatively offset, and the possibility of contrast distortion is reduced. In addition, in the embodiment, the query source of the image subgraph is obtained by comparing the image subgraph with the image original image, so that the traceability and accountability problems during leakage query are facilitated, and the safety of medical image data is effectively improved.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely illustrative of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (6)
1. A method for viewing medical images across hospitals by regional intranet scanning, the method comprising:
step S1, a server receives a first query request sent to the server by scanning a first report by a code scanning device of the first query end; the first query request comprises a query requester and a first image list code of the first report list;
step S2, the server acquires a first image original picture corresponding to the first image single code from an intranet database of the server according to the first image single code;
step S3, the server obtains a non-sensitive area of the first image original picture according to the image type of the first image original picture; generating a first unique identification code corresponding to the ID of the query requester through hash operation according to the query requester; modifying the first unique identification code into the non-sensitive area and generating a second image subgraph corresponding to the first image original picture;
step S4, the server side sends the second image sub-graph to the first query side according to the first query request;
the operation flow of modifying the first unique identification code into the non-sensitive area and generating a second image sub-image corresponding to the first image original image comprises the following steps:
step S31, the non-sensitive area is obtained, partial or all areas of the non-sensitive area are divided according to the binary bit number length of the first unique identification code, and a non-sensitive subarea with the same binary bit number length as the first unique identification code is formed; wherein the number of detachable areas of the non-sensitive area is greater than the binary digit length of the first unique identification code;
step S32, determining gray scale offset of each non-sensitive subarea according to the value of 0 and the value of 1 on each bit of the first unique identification code; wherein, the value of 0 corresponds to the first gray level offset and the value of 1 corresponds to the second gray level offset;
step S33, judging whether the original average gray value of each non-sensitive subarea is larger than a first preset value, and modifying the gray value of each non-sensitive subarea to obtain the second image subgraph; and in response to the original average gray value being larger than the first preset value, positively shifting the gray of the non-sensitive subarea according to the gray offset, and otherwise, negatively shifting the gray of the non-sensitive subarea according to the gray offset.
2. The method for referring to medical images across hospitals by regional intranet scanning as set forth in claim 1, wherein the step S31 further includes:
step 311, acquiring the non-sensitive area, and dividing the non-sensitive sub-area in the non-sensitive area based on a boundary finding algorithm.
3. A method of viewing medical images across hospitals in a regional intranet scan as defined in claim 1, said method comprising:
s5, the server side acquires the second image subgraph to be verified, extracts image characteristics of the second image subgraph in a sensitive area, and identifies the first image original image corresponding to the second image subgraph in the intranet database according to the image characteristics;
and S6, the server extracts each non-sensitive subarea and the corresponding gray level offset according to the first image original image and the second image subgraph, generates the first unique identification code, and matches the query requester in the intranet database according to the first unique identification code.
4. The method for referring to medical images across hospitals by regional intranet scanning of claim 1, wherein the gray scale value of the first gray scale offset is 0-4, and the gray scale value of the second gray scale offset is 6-10.
5. The method for referring to medical images across hospitals by regional intranet scanning as in claim 1, wherein the non-sensitive area is a continuous area or a discontinuous area.
6. The method for referring to medical images across hospitals by regional intranet scanning as set forth in claim 1, wherein in the step S32, the gray level shift is an overall shift or a non-uniformity shift of the non-sensitive subregion; wherein when the gray scale shift amount is a non-uniformity shift, an edge region of the non-sensitive sub-region tends to be non-shifted, and a center region of the non-sensitive sub-region tends to be shifted.
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