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Medical Image Processing Server using DICOM.

Medical Image Processing Server using DICOM. Barberis, Sebastián (1), Graffigna, Juan Pablo (2), I soardi, Roberto (1) 1 – Escuela de Medicina Nuclear. Mendoza. Argentina. 2 – Universidad Nacional de San Juan. San Juan. Argentina. jgraffig@gateme.unsj.edu.ar. Problematic Situation.

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Medical Image Processing Server using DICOM.

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  1. Medical Image Processing Server using DICOM. Barberis, Sebastián (1), Graffigna, Juan Pablo (2), Isoardi, Roberto (1) 1 – Escuela de Medicina Nuclear. Mendoza. Argentina. 2 – Universidad Nacional de San Juan. San Juan. Argentina.jgraffig@gateme.unsj.edu.ar

  2. Problematic Situation • Algorithms developed by research groups present inconvenients that make difficult their validation and clinical implementation. • Highly trained medical and technical staff usually work in very demanding environments and cannot employ the developed tools. • For the validation, a selection of studies and its later processing is required. Actually, validations are performed manually.

  3. Objetive • The implementation of a centralized processing server that allows solving different needs in diagnosis and research. • The development of a DICOM system interact within a PACS. • Quickly associate research processing algorithms to clinical implementation, allowing their validation.

  4. Storage Server Diagnostic Workstation PACS Manager HIS / RIS Modalities Processing Server DICOM Printers Connecting to a PACS system Network Service Workstation

  5. Features • Communication of studies in clinical environments (DICOM). • Different algorithms of processing: • Intermodality/intrapatient registration for radiotherapy. • Intramodality/intrapatient registration for treatment monitoring. • Processing of single studies for diagnosis. • Others. • Easy administration and set-up • Automatic Function. • Multi-thread. • Stability against failures. • Development with GPL tools.

  6. Tools used • Support tools for design: • Notation diagrams in Unified Modeling Language UML. • Tool box BOUML® release 2.32 • Develop Enviroment and compiler: • Code::Blocks 8.02 • Compiler MinGW 3.4.5 • DICOM facilities: • CTN of Mallincrodt Institute of Radiology. • Database facilities. • MySQL 5.0 API for C. • Processing Algorithms • Research project.

  7. Implementation model - Application Data Flow

  8. Implementation of the DICOM standard • The whole communication and transfer of images with remote application entities is carried out using the DICOM network protocol using the TCP/IP protocol. The functions supported by the entities of the system are: • UL services supported are: A-ASSOCIATE, A-RELEASE, A-ABORT, A-P-ABORT and P-DATA

  9. Implementation of the DICOM standard • The reception Applications Entity in this system support a great number of storage service class (listed in its Conformance Statement) and the verification service class. • As the communication module only supports the storage and verification, the response to other request (as posts C-FIND or C-GET) is reject whit the corresponding response messages.

  10. Features database • 1) Contains the configuration parameters (available processing algorithms, conditions for them, assigned port, etc). • 2) Served for recording studies information (general and specific data). • Both sets of data are used to making decisions. • Decision-making system: SQL Query

  11. Thread use • Allows opening a listening port for each different processing algorithm (including their capacity of solve one o more association request). • Allows the separation of tasks and avoid problems that can halt its overall performance. The latter is important because the imaging techniques can be used in a development phase, causing instability in the process

  12. Test and application • This tool has been implemented in a Medical Imaging and Radiotherapy center, “Escuela de Medicina Nuclear, Mendoza, Argentina” including three image processing algorithms. • Quality control in computed tomography. • Flip process to prepare PET studies for Radiotherapy Planning. • Cropping and segmentation of MRI brain studies.

  13. Test and application Quality control in computed tomography Cropping and segmentation of MRI brain studies. Flip process to prepare PET studies for Radiotherapy Planning.

  14. Conclusions • This work has allowed the development of a Processing Server in accordance with DICOM standard. • It is possible to integrate new processing algorithms to clinical environments. • The application allows an automatic management of studies. The decision made determines which operation must be executed, which studies take part, and to whom the results must be sent. • The system can receive several studies, execute algorithms, or send results simultaneously using different processing threads. Operations, ports, conditions, etc., can be quickly modified by means of a SQL database.

  15. Conclusions • For the design and the development of the server, GPL software tools have exclusively been used. • A weakness of the system is the necessity of employing automatic algorithms that require no user intervention. Even though there is a tendency to this kind of techniques, there is no possibility to interact with the user during processing tasks. • Regarding the implementation of the system in a clinical environment, it is necessary to execute it for a prolonged time in order to evaluate the system and algorithms. It will allow to analyze the organizational changes.

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