CN110223760B - Medical image information acquisition and fusion method and system - Google Patents
Medical image information acquisition and fusion method and system Download PDFInfo
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- CN110223760B CN110223760B CN201910431730.XA CN201910431730A CN110223760B CN 110223760 B CN110223760 B CN 110223760B CN 201910431730 A CN201910431730 A CN 201910431730A CN 110223760 B CN110223760 B CN 110223760B
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H30/00—ICT specially adapted for the handling or processing of medical images
- G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Abstract
The invention provides a medical image information acquisition and fusion method and system, which can effectively improve the acquisition efficiency of medical image information by acquiring examination information of different examination categories and reasonably pushing the examination information in combination with statistical probability, can accurately improve the efficiency and accuracy of medical image examination and the alternative of treatment methods, and can provide a database for doctors to learn.
Description
Technical Field
The invention relates to the technical field of information processing and data sharing, in particular to a method and a system for acquiring and fusing medical image information.
Background
Today, medical institutions generate a large number of medical images each day, which contain a large amount of potential information. At present, medical institutions mainly rely on manual interpretation to analyze the medical images, the efficiency is low, and information which can be mined by human eyes and diagnosis experience of doctors is limited, so that the medical image resources cannot be fully utilized.
With the development of computer technology, medical image processing systems implemented by the computer technology have been widely used in the medical field. Doctors use medical image processing systems to observe the condition of a patient's tissue organ, etc., as an important reference in diagnosis, preoperative planning, and surgery. However, the current medical image auxiliary processing cannot classify the features of the medical images according to different parts of the human body and establish a medical reference model, so that the efficiency and accuracy of medical examination of a patient by a doctor cannot be improved.
In addition, at present, medical image resources are not shared among existing medical institutions, and if a patient cannot make a follow-up visit in a hospital for the first time or make a deeper examination for various reasons, and the patient does not carry the image data of the medical examination that has already been made with him/her, the patient is required to make new examinations.
For example, patent CN201811608562.9 discloses an intelligent medical system for storing and exchanging medical image information, which classifies medical image information of different parts by constructing different databases and exchanging image information, and can solve the problems that some medical image resources are not shared and patients need to be checked repeatedly, but the establishment of a medical evaluation model proposed in this patent provides reference for doctor diagnosis, and actually does not fundamentally and quickly solve the problem of how to improve the efficiency and accuracy of medical examination performed on patients by doctors. The above patent document is different from the technical solution of the present patent.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a system for acquiring and fusing medical image information, which can effectively improve the acquisition efficiency of the medical image information and can accurately improve the efficiency and accuracy of medical image examination and the alternative of a treatment method.
In order to achieve the purpose, the invention adopts the following technical scheme:
in one aspect, the invention provides a medical image information acquisition and fusion method, comprising the following steps:
s02: a first acquisition module in a first system acquires first examination information of a first patient, and the first examination information and the individual identity of the first patient are divided and stored in a first storage database module; the first checking information comprises first type identification information and first image information;
the first weight module carries out weight weighing processing on the first check information to obtain a first weight;
the first wireless module transmits the first medical information to the fusion system; the first medical information comprises the first type identification information, the first weight, a first image element corresponding to the first image information, and first path information corresponding to the first inspection information storage;
s04: a second acquisition module in the second system samples second examination information of other patients, and the second examination information and other identities of the other patients are divided and stored in a second storage database module; wherein the second examination information includes second type identification information, a second image, second diagnosis information, and second treatment countermeasure information;
the second weight module carries out weight weighing processing on the second check information to obtain a second weight;
the second wireless module transmits second medical information to the fusion system; the second medical information comprises the second type identification information, the second weight, a second image element corresponding to the second image information, and second path information corresponding to the second inspection information storage;
s06: the fusion system stores the second medical information to a fusion server;
s08: the fusion system receives the first medical information and stores the first medical information to the fusion server;
s10: and a matching module of the fusion system rapidly matches the alternative diagnosis information and the alternative treatment countermeasure information according to the first weight, the second weight, the first image element and the second image element, and pushes the alternative diagnosis information and the alternative treatment countermeasure information to the first system through a third wireless module.
Preferably, in the present invention, the first weight includes a first pathology quantitative value, a first diagnosis quantitative value, and a first treatment countermeasure quantitative value;
the second weight value comprises a second pathology quantitative value, a second diagnosis quantitative value and a second treatment strategy quantitative value.
Preferably, in step S02, in the present invention, the first weight module is connected to a first client, and the first client determines the first weight for the first check information; and the second weight module is connected to a second client, and the second client determines the second weight for the second check information.
Preferably, in the present invention, before the step S10, the following step S09 is further provided:
a detection module in the fusion system detects the first weight according to the first weight and the first image element;
step S091: when the first weight value meets the check value corresponding to the first image element, the matching module quickly matches the alternative diagnosis information and the alternative treatment strategy information according to the first weight value, the second weight value, the first image element and the second image element; proceeding to said step S10;
step S092: when the first weight value does not accord with the check value corresponding to the first image element, the check module determines a first correction weight value; the matching module is used for quickly matching the alternative diagnosis information and the alternative treatment strategy information according to the first correction weight, the second weight, the first image element and the second image element; the process proceeds to step S10.
Preferably, the present invention further includes step S12: when the first weight in the step S091 is greater than the second weight or the first corrected weight in the step S092 is greater than the second weight, the second weight is updated to obtain a latest second weight; and sending the latest second weight to a second system.
Preferably, in the present invention, in step S012, the following formula is specifically obtained:
Wherein, phi'2Represents the latest second weight, Φ1Represents the first weight, phi2Representing the second weight value in the first set of weights,n represents to obtain the second weight phi2The number of the second check information required;
and representing the first correction weight value.
Preferably, the present invention further includes step S14: and the first system sends the alternative diagnosis information and the alternative treatment strategy information to the first client.
Preferably, in the present invention, the first storage database module and the second storage database module both adopt a bidirectional classification storage mode for patient identity information and examination information.
On the other hand, the invention also provides a medical image information acquisition and fusion system corresponding to the medical image information acquisition and fusion method.
Compared with the prior art, the invention has the beneficial technical effects that:
1. by setting the patient identity information and the examination information in a bidirectional classified storage mode, the integration and unified management of patient cases are achieved, the unified management can be achieved on medical image information classification, and investigation and matching are facilitated; on one hand, sharing of patient cases in the whole network is achieved, and the cost of repeated examination is reduced; on one hand, the doctor can quickly know all cases of the patient, and the diagnosis and treatment of the patient by the doctor can be greatly improved; meanwhile, the statistics, the lookup and the matching efficiency of the medical image information can be improved.
2. By setting the weight value for the examination information, the unified, typicality and specificity of the pathology of the case can be managed, the high similarity matching can be carried out aiming at the pathology of the same case, the accuracy of recommending alternative diagnosis information and alternative treatment strategies can be improved, the treatment efficiency of doctors on the patient is also greatly improved, and meanwhile, the expenses of repeated treatment and misdiagnosis treatment of the patient are indirectly reduced; in addition, the system is convenient for doctors to pertinently research and discuss shared cases.
3. The system can be updated in real time, so that timely updating and maintaining can be guaranteed according to actual conditions, such as newly increased research parameters of cases, and comprehensiveness and pushing accuracy of the database are guaranteed.
Drawings
Fig. 1 is a flowchart of a medical image information collecting and fusing method provided by the present invention;
fig. 2 is a schematic diagram of a medical image information collecting and fusing system according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to fig. 1-2 of the specification.
Referring to fig. 1, a first system and a second system for distinguishing between hospitals and patients will be described, wherein the first system represents a medical imaging system of a target patient in a target hospital, and the second system represents a medical imaging system of a patient in another hospital or another patient in the target hospital relative to the target patient in the target hospital. The second system is the other system corresponding to the database.
First, when the first patient is examined in the first system
1. A first acquisition module in a first system acquires first examination information of a first patient, and the first examination information and the individual identity of the first patient are divided and stored in a first storage database module; the first checking information includes first type identification information and first image information.
Further, the personal identity may be, in particular, name, gender, age, identification number, medical insurance, and the like. The first image information may be X-ray examination information, ultrasonic examination information, CT examination information, or Magnetic Resonance Imaging (MRI) examination information; for the convenience of searching, the first image information may be added with information such as a check date identification number, an image sequence identification number, and an image identification number.
2. And the first weight module carries out weight weighing processing on the first check information to obtain a first weight.
Specifically, the first weight includes a first pathology quantization value, a first diagnosis quantization value, and a first treatment strategy quantization value. The setting of the weight value is to screen the alternative diagnosis information and the alternative treatment strategy which are more in line with the first examination information in the examination information, and the more accurate the setting of the weight value is, the more accurate the alternative diagnosis information and the alternative treatment strategy are.
Here, the pathological quantitative value represents that the feature of the medical image to be examined is digitalized and graded according to the condition of the patient; the diagnosis quantitative value represents a preliminary diagnosis result given by a doctor according to the illness state and the examination of a patient, and the element extraction and the digital grade quantification of the element are carried out on the diagnosis result; the treatment strategy quantitative value represents an actual treatment scheme for the patient condition given by a doctor, and element keywords, the drug dosage and the like in the actual treatment scheme are subjected to digital grade quantification. Quantification of these parameters is to facilitate subsequent reference to obtain more accurate alternative diagnostic information, alternative therapeutic strategies. Meanwhile, the second case quantitative value, the first diagnosis quantitative value, and the first treatment countermeasure quantitative value in the first system are the same as those shown here.
Furthermore, the first weight module is connected to a first client, the first client is mainly a doctor end, a doctor can determine the first weight according to the actual examination condition, and the first weight module can automatically set the first weight according to the first examination information and display the first weight at the first client, and the first client can modify and confirm the first weight.
3. A first wireless module in the first system transmits the first medical information to the fusion system; the first medical information comprises the first type identification information, the first weight, a first image element corresponding to the first image information, and first path information corresponding to the first inspection information storage; the first image element is to extract elements of the first image information in order to improve transmission efficiency while ensuring the integrity of the information, for example, information such as a scanning method, a CT value, a resolution value, CT matrix data, a volume effect, and an SNR can be extracted for the CT image information.
Second, other patients are examined in the first system or the second system
4. A second acquisition module in the second system samples second examination information of other patients, and the second examination information and other identities of the other patients are divided and stored in a second storage database module; wherein the second examination information includes second type identification information, a second image, second diagnosis information, and second treatment countermeasure information.
In addition, other identities of other patients may be name, gender, age, identification number, medical insurance, and so forth. The second image information may be X-ray examination information, ultrasonic examination information, CT examination information, or Magnetic Resonance Imaging (MRI) examination information; for the convenience of search, the second video information department adds information such as examination date identification number, image sequence identification number, and image identification number.
Here, other patients in the second system are preferentially screened for the detection information of patients of the same examination category.
5. And the second weight module carries out weight weighing processing on the second checking information to obtain a second weight.
Specifically, the second weight includes a second pathology quantization value, a second diagnosis quantization value, and a second treatment strategy quantization value. The second weight is set by counting and calculating a series of check information by a subsequent fusion system, and the second weight can be updated in real time according to the first weight provided by the first system by the fusion system. And the second weight is more accurate after big data statistics, the alternative diagnosis information and the alternative treatment strategy which are more in line with the first examination information can be screened from the examination information in the database, and the more accurate the statistics of the weight is, the more accurate the alternative diagnosis information and the alternative treatment strategy are.
Furthermore, the second weight model is connected to the second client, the second client also represents the doctor end of different operating systems, and the doctor end can check the second weight in the real-time second system, the image elements of each examination type, the corresponding diagnosis information, the treatment countermeasure information and the like in real time.
6. The second wireless module transmits second medical information to the fusion system; the second medical information includes the second type identification information, the second weight, a second image element corresponding to the second image information, and second path information corresponding to the second examination information.
It should be noted that the two processes of the first patient performing the examination in the first system and the other patients performing the examination in the first system or the second system do not have a definite time relationship in succession or in parallel, and the two processes are only written in steps for convenience of description. Wherein, for the examination events of different examination categories, while the first patient is examined in the first system, the examination of other patients in the first system or the second system can be performed before, simultaneously or after. However, for examination events of the same examination category, while a first patient is examined in the first system, other patients may be examined in the first system or the second system before. If the first patient is examined in the first system and other patients are examined in the first system or the second system at the same time aiming at the examination events of the same examination type, the second examination information is not updated synchronously.
Thirdly, the fusion system performs fusion operation
7. The fusion system stores the second medical information to a fusion server;
8. the fusion system receives the first medical information and stores the first medical information to the fusion server;
9. and a matching module of the fusion system rapidly matches the alternative diagnosis information and the alternative treatment countermeasure information according to the first weight, the second weight, the first image element and the second image element, and pushes the alternative diagnosis information and the alternative treatment countermeasure information to the first system through a third wireless module.
10. A detection module in the fusion system detects the first weight according to the first weight and the first image element;
when the first weight value meets the check value corresponding to the first image element, the matching module quickly matches the alternative diagnosis information and the alternative treatment strategy information according to the first weight value, the second weight value, the first image element and the second image element; entering the next step 11;
b. when the first weight value does not accord with the check value corresponding to the first image element, the check module determines a first correction weight value; the matching module is used for quickly matching the alternative diagnosis information and the alternative treatment strategy information according to the first correction weight, the second weight, the first image element and the second image element; proceed to the next step 11.
In addition, when the first weight in a is greater than the second weight or the first corrected weight in b is greater than the second weight, the second weight is updated to obtain a latest second weight; and sending the latest second weight to a second system.
In addition, the first correction weight is determined by the check module in the fusion system according to the first image element and the image elements of the same category stored in the fusion system.
Specifically, the latest second weight is obtained according to the following formula:
Wherein, phi'2Represents the latest second weight, Φ1Represents the first weight, phi2Representing the second weight value, N represents the second weight value phi2The number of the second check information required;
and representing the first correction weight value.
11. And the first system sends the alternative diagnosis information and the alternative treatment strategy information to the first client.
The first client can diagnose and treat the first patient according to the actual situation, the alternative diagnosis information and the alternative treatment strategy information.
In addition, the first storage database module and the second storage database module both adopt a two-way classification storage mode of patient identity information and examination information, can manage the unification, typicality and particularity of case pathology, can perform highly similar matching aiming at the same case pathology, and can improve the accuracy of recommending alternative diagnosis information and alternative treatment strategies.
And finally, the first client and the second client can perform data retrieval according to the retrieval factors, so that doctors can exchange and learn specific illness state experience.
On the other hand, the invention also provides a medical image information acquisition and fusion system corresponding to the medical image information acquisition and fusion method. Designing corresponding implementation modules on the basis of a known method to form an integral system is a common technical means in the field and is not described herein too much.
Finally, the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting, and other modifications or equivalent substitutions made by the technical solutions of the present invention by those of ordinary skill in the art should be covered within the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solutions of the present invention.
Claims (3)
1. A medical image information acquisition and fusion method is characterized in that:
s02: a first acquisition module in a first system acquires first examination information of a first patient, and the first examination information and the individual identity of the first patient are divided and stored in a first storage database module; the first checking information comprises first type identification information and first image information;
the first weight module carries out weight weighing processing on the first check information to obtain a first weight;
the first wireless module transmits the first medical information to the fusion system; the first medical information comprises the first type identification information, the first weight, a first image element corresponding to the first image information, and first path information corresponding to the first inspection information storage;
s04: a second acquisition module in the second system samples second examination information of other patients, and the second examination information and other identities of the other patients are divided and stored in a second storage database module; wherein the second examination information includes second type identification information, a second image, second diagnosis information, and second treatment countermeasure information;
the second weight module carries out weight weighing processing on the second check information to obtain a second weight;
the second wireless module transmits second medical information to the fusion system; the second medical information comprises the second type identification information, the second weight, a second image element corresponding to the second image information, and second path information corresponding to the second inspection information storage;
s06: the fusion system stores the second medical information to a fusion server;
s08: the fusion system receives the first medical information and stores the first medical information to the fusion server;
s09: a detection module in the fusion system detects the first weight according to the first weight and the first image element;
step S091: when the first weight value accords with the check value corresponding to the first image element, the matching module of the fusion system quickly matches out alternative diagnosis information and alternative treatment strategy information according to the first weight value, the second weight value, the first image element and the second image element; proceeding to step S10;
step S092: when the first weight value does not accord with the check value corresponding to the first image element, the check module determines a first correction weight value; the matching module of the fusion system rapidly matches the alternative diagnosis information and the alternative treatment strategy information according to the first correction weight, the second weight, the first image element and the second image element; proceeding to step S10;
s10: the matching module of the fusion system rapidly matches the alternative diagnosis information and the alternative treatment strategy information according to the first weight, the second weight, the first image element and the second image element, and pushes the alternative diagnosis information and the alternative treatment strategy information to the first system through a third wireless module;
the first weight comprises a first pathology quantized value, a first diagnosis quantized value and a first treatment strategy quantized value;
the second weight value comprises a second pathology quantitative value, a second diagnosis quantitative value and a second treatment strategy quantitative value;
the first storage database module and the second storage database module adopt a bidirectional classification storage mode of patient identity information and examination information;
s12: when the first weight in the step S091 is greater than the second weight or the first corrected weight in the step S092 is greater than the second weight, the second weight is updated to obtain a latest second weight; and sending the latest second weight to a second system;
in step S12, the following formula is specifically used:
Wherein, phi'2Represents the latest second weight, Φ1Represents the first weight, phi2Representing the second weight value, N represents the second weight value phi2The number of the second check information required;
and representing the first correction weight value.
2. The medical image information collecting and fusing method of claim 1, wherein:
in step S02, the first weight module is connected to a first client, and the first client determines the first weight for the first check information; and the second weight module is connected to a second client, and the second client determines the second weight for the second check information.
3. The medical image information collecting and fusing method of claim 1, wherein:
further, the method includes step S14: and the first system sends the alternative diagnosis information and the alternative treatment strategy information to the first client.
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| JP2017182244A (en) * | 2016-03-29 | 2017-10-05 | コニカミノルタ株式会社 | Medical information providing system |
| CN109473153A (en) * | 2018-10-30 | 2019-03-15 | 医渡云（北京）技术有限公司 | Processing method, device, medium and the electronic equipment of medical data |
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