| PACS is Picture Archiving and Communication Systems,also called Medical image information system,it together with HIS(Hospital Information System),LIS(Laboratory Information System)and EMRS(Equipment Maintenance Reporting System)etc.constitutes the application system of modern digital hospital.PACS system focuses on the collection,transmission,storage and diagnosis of digital medical image,and solves the problem of digital workflow in the Radiology Department and other medical images producing departments,And further solves the image processing,data mining and other advanced issues.The series core functions of PACS system,such as image acquisition,image transmission,image storage,diagnostic reports,and so on are based on an international standard DICOM(Digital Imaging and Communications in Medicine),At present,the scientific research based on DICOM standard has become a hot issue in the field of digital medical field.The DICOM standard has revolutionized the radiology process,and it changes the traditional examination process to the full digital workflow,and it makes the advanced application of medical image probable.DICOM data has a suffix.dcm,it indicates that this is an image data which follows the DICOM standard.A DICOM image data contains related image sequences and a header file,the header file contains image related semantics in accordance with the definition of the DICOM standard,such as the patient related information,the examination equipment related information,the related diagnosis and description information,etc..These information create a rich semantic environment for the corresponding image sequences,give the corresponding image sequence a full semantic logo,lay the foundation for the semantic mining of image sequence.PACS produces a lot of DICOM image data after years of use.These data includes related images in various medical disciplines,and these images carry the semantic information of various disciplines,so the DICOM database is a full medical disciplines diagnosis knowledge database.Based on the semantic characteristics of the database,it becomes an important object in digital medical management and research.How to organize and manage it scientifically and make it play its due role in medical treatment,scientific research and teaching,becomes a hot topic in the research of DICOM standards.The semantic Web technology can solve the problem of semantic reuse of DICOM data,which is based on description logic and ontology and other related technologies to describe the domain information and logical reasoning.At present a lot of research work is devoted to semantic Web related technologies.From the construction point of view,DICOM database contains a large number of diagnosis semantic information,in order to make the related application to access,process,reuse and share the DICOM database,the extraction of ontology and description logic of knowledge base become hot spots in the research field of DICOM standard.From the storage point of view,DICOM ontology and description logic knowledge base are huge,how to effectively store these resources becomes more and more important.It should be pointed out that there is imprecise and uncertain information in the application of PACS system,especially because the habits,synonyms,near synonyms are used in diagnostic language,the images carry more uncertainty and imprecision information.To express and reasoning the fuzzy knowledge exist widely in practical application,and let the semantic web has the ability to deal with fuzzy knowledge,currently there has been a lot of research work focusing on the fuzzy ontology extensions,homologous,fuzzy ontology extraction,storage and query,are also known as hot research issues.From the perspective of knowledge reuse,the goal of constructing the fuzzy DICOM ontology is to realize the intelligent query.Therefore,the semantic query extending technology and the query optimization technology based on fuzzy ontology also are important research directions.An earlier version of DICOM gives a definition of object IOD of the structured report,and the definition has been upgraded in the latest version 2015,made conform to the standard HL7.SR organizes the DICOM SR image data diagnostic report in a standard structure,and uses code to express diagnostic medical concepts.It solves the separation problem of traditional diagnosis report and image data,and makes DICOM image data carry more semantic information in the field of diagnostic medicine.At present,the research on the development and application of DICOM SR has become a hot research topic at home and abroad,however,the problems and challenges still exist.At present,the precise definition of SR does not express the actual application of fuzzy semantics,but also can not solve the user's fuzzy query.At home and abroad,there is not research on the application of fuzzy technology in DICOM SR 's extension and query.For these purposes,this disertation systematically studies the construction,storage and query of the fuzzy DICOM ontology,and the specific research contents include the following four aspects:(1)According to the characteristics of PACS system and DICOM standard,the technical path of DICOM standard fuzzy extension is analyzed.Firstly,based on the existing research work,we give the classical formal model of the 4 kinds of data description model in PACS system ontology evolution and DICOM standard fuzzy extension.,including the definition of PACS ER concept model,relational database model,XML model,OWL ontology model.And based on the fuzzy theory,the fuzzy extension of these 4 classical models is also carried out,and the formal definition of fuzzy logical extension of these 4 models is proposed.Finally,based on the mapping method of classical relational schema to Ontology,the fuzzy extension of the mapping method is given.which is used to realize the mapping from the fuzzy relational schema of PACS system to the fuzzy DICOM ontology.(2)The fuzzy semantic extension of DICOM standard is studied.The knowledge acquisition and representation methods of PACS system and DICOM standard are given.A basic DICOM ontology knowledge model is proposed,and the fuzzy knowledge representation and semantic extension of basic DICOM ontology are studied,which are based on the fuzzy set theory.The basic information model of fuzzy DICOM ontology is put forward,and the coding scheme,the relation type of fuzzy DICOM ontology,and the mapping method are studied.Finally,the development method of fuzzy DICOM ontology is given,and the OWL representation of class,attribute and attribute relation,attribute constraint and relation of fuzzy DICOM ontology in the development process is studied,and the method of verifying the logic of the ontology is given.Finally,the persistence method of fuzzy DICOM ontology is studied,and a general storage framework of fuzzy DICOM ontology is given.(3)In order to carry out intelligent query on the extended fuzzy DICOM standard model,the query and reasoning method of fuzzy logic is studied.The formal model of query language,query response,semantic reasoning and semantic matching of fuzzy description logic is studied based on intelligent query,and the corresponding examples are given.The FDLQ reasoning algorithm based on fuzzy logic is proposed,and the experimental results and analysis are given,which lays a technical foundation for the realization of the intelligent query of the fuzzy DICOM ontology.(4)Based on the fuzzy semantic extension of DICOM standard and the query reasoning method of fuzzy description logic,a semantic query processing method for fuzzy DICOM ontology is proposed.The basic process,formal technology and query expansion of semantic query are studied,and the intelligent query based on user preference is studied.The design of semantic query engine based on fuzzy DICOM ontology is given,and the optimization technique based on the query engine is studied.At last,the content of this chapter is applied to the semantic query of fuzzy DICOM ontology,and experiments are carried out accompany with the results.(5)Based on the definition of SR in the DICOM standard and the content of the study,this disertation puts a fuzzy structured report based on the fuzzy DICOM ontology FSR.First,the XML representation of the numerical and diagnostic in SR is studied,and then extend it to the XML representation of FSR.In the end,the general frame and function realization of the intelligent query system on FSR are given,and the application effect of the system is also evaluated.The research work of this paper constructs a more complete framework of fuzzy DICOM ontology intelligent query,and has already made a series of original research results.It lays a solid theoretical foundation for semantic interoperability between semantic Web and PACS system image databases,and also provides effective technical support for the implementation of fuzzy DICOM ontology management. |
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