Maria de la Iglesia - CEIB: a R&D services in bioimaging oriented to integration of environments with her on cloud computing
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The document discusses the Valencia Health Agency's bioimaging project aimed at centralizing medical imaging management through initiatives like the Valencia Biobank of Medical Imaging. It emphasizes the collection and validation of imaging data to support research and enhance patient care by integrating findings into electronic health records (EHR). The project focuses on developing tools for image processing, validation, and decision support, ultimately aiming to improve clinical outcomes and provide superior bioimaging services.
Maria de la Iglesia - CEIB: a R&D services in bioimaging oriented to integration of environments with her on cloud computing
- 2. INTRODUCTION • Introduction • Current status of bioimaging in the AVS (Valencia Health Agency) • CEIB Objectives • Project Overview • System parts • R&D • Conclusions
- 4. CURRENT STATUS OF AVS BIOIMAGE PROJECT Proof of Concept of Centralized Medical Imaging Management (GIMC)
- 5. CURRENT STATUS OF AVS BIOIMAGE PROJECT PACS DEPARTAMENTALES Servicios DICOM Q/R Acceso WADO Bus SOA GIMC
- 6. CURRENT STATUS OF AVS BIOIMAGING PROJECT
- 7. CEIB Reference Centre to provide excellence in bioimaging from a common repository Cardiology
- 8. CEIB Reference Centre to provide excellence in bioimaging from a common repository Neurology
- 9. CEIB Reference Centre to provide excellence in bioimaging from a common repository Angiography
- 10. CEIB WORKING LINES Use of an image biobank for R & D and transferring specialized knowledge to the patient's electronic medical/health record (EHR) o Development of an outstanding “search engine” through cataloged and indexed biobank for information management. o Information validation and quality control o Image Post-processing o Systems Decision Support Imaging
- 11. CEIB GOALS Development of an outstanding “search engine” through cataloged and indexed biobank for information management o Search for images, control cohort, discoveries, clinical trials, etc. o Knowledge of the population by means of image quantitative markers o Structuring radiological examinations from EHR through DICOM SR standard.
- 12. CEIB GOALS Information validation and quality control oValidation at the level of studies (protocols, alerts) oValidation at the level of data (standardization) oQuality control regarding to radiation doses by considering both patients and studies
- 13. CEIB GOALS Image Post-processing o Centralizing image post-processing in clinical trials o Validation of new techniques of processing and obtaining quantitative marks o Development of tools for image processing o Development, standardization and validation of Image Biomarkers
- 14. CEIB GOALS Computing Supported / Aided Decision through Bioimage o Creation of virtual net-communities for users with common interests o Participation in international projects (Connectome) o Design and implementation of tools for the development of Computing Aided Decision of medical systems
- 15. SYSTEM OVERVIEW. CURRENT INFRASTRUCTURE SYSTEM AREA: ALSIS PLATFORM, HITACHI COMMUNICATION AREA: ARTERIAS CEIB LAB HOSPITAL PACS HITACHI Bus SOA Arterias Lab CEIB ALSIS
- 16. SYSTEM COMPONENTS GIMC Search Engine (SE) Anonymizer (ANOM) DICOM Morphing BET
- 17. SYSTEM OVERVIEW EHR CLOUD CEIB R & D GIMC BIKE GEBID
- 18. SYSTEM COMPONENTS R & D BIOIMAGE CLINICAL TRIAL MANAGER SYSTEM (GEBID)
- 19. SYSTEM COMPONENTS R & D BIOIMAGE CLINICAL TRIAL MANAGER SYSTEM (GEBID)
- 20. SYSTEM COMPONENTS R & D BIOIMAGE CLINICAL TRIAL MANAGER SYSTEM (GEBID)
- 21. SYSTEM COMPONENTS R & D BIOIMAGE CLINICAL TRIAL MANAGER SYSTEM (GEBID)
- 22. SYSTEM COMPONENTS BIOIMAGING KNOWLEDGE ENGINE (BIKE) Techniques
- 23. BIKE-OLOGIES Bike- Bike- Bike- Bike-Cardio Bike-Vascular Orthopaedics NeuroImaging Datamining Morphological Quantification of Diagnosis of Detection of analysis of Radiation Exposure cardiac function osteoporosis epileptogenic focus aneurysms Spine disease Dopamine Electrophysiology Virtual treatment diagnosis and transmission Quality Control planning treatment planning quantification BIKE-OLOGIAS BioImage Knowledge Engine
- 24. SYSTEM COMPONENTS BIKE-Postprocessing Angel Alberic. Cuantificación Quirón
- 25. SYSTEM COMPONENTS BIKE-Postprocessing: Computational Models Martí Bonmatí L, et al. Biomarcadores de imagen, imagen cuantitativa y bioingeniería. Radiología. 2011
- 26. SYSTEM COMPONENTS BIKE-Imaging: Quantification and Biomarkers
- 27. Martí Bonmatí L, et al. Biomarcadores de SYSTEM COMPONENTS imagen, imagen cuantitativa y bioingeniería. Radiología. 2011 BIKE-Imaging: Feature Extraction
- 29. R&D. WE HAVE A DREAM Return the R & D through the EHR by the transmission of knowledge to the patient
- 30. R&D Return on R & D to the EHR by the transmission of knowledge to the patient
- 31. R&D Return on R & D to the EHR by the transmission of knowledge to the patient
- 32. Title: CEIB Experience: A R&D cloud services in bioimaging oriented to integration of environments with EHR Abstract: Purpose: The EHR of the Valencia Health Service (Spain) offers highly specialized solutions. The purpose of this work is to present the centralization of “Valencia Biobank of Medical Imaging” (GIMC). This project will allow R&D support for the scientific community through the implementation of logical services based in Open Source technologies. Methods and Materials: Centralized storage image systems are a milestone in the strategic framework of the AVS. That is why obtained images from the entire population, are a sample of great value that will form the basis of knowledge for the future science. The defined architecture includes a Search Engine, a platform to support the management of clinical trials with biomedical imaging (GEBID) and a Bioimaging Knowledge Engine (BIKE). Results: Both CEIB and GIMC provide an ideal data source for analyzing the acquired image data. In particular, the following actions are prepared: development and validation of an Image Bank, a Decision Support Systems, an Imaging Biomarkers platform, Virtual Communities as users’ networks and Image Processing Tools libraries. Conclusion: As a result of the data management from the Biobank and the development of Cloud services-CEIB, digital medical imaging and computer processing, several biomarker parameters and quality innovations will be develop and shown. This initiative will allow the “Valencia Biobank of Medical Imaging” to achieve excellence in care and experimental medicine in the field of Bioimaging. The main final objective of this process is that the results of R&D will be transferred to the patient, providing value-added elements to their EHR.in bioimaging oriented to integration of environments with EHR THANKS FOR YOUR ATTENTION
Editor's Notes
- #2: C – E - I – B : CENTRE OF EXCELENCE FOR BIOMEDICAL IMAGING, IN SPANISH CEIB-AVS
- #3: I WILL DIVIDE MY PRESENTATION IN THIS TOPICS I WILL TAK ABOUT
- #4: IN THE PAST THE RADIOLGIST ANALIZED THE X-RAY IMAGE TAKING A LOOK NOWADAYS THE PACS AND DIAGNOSTIC STATION ARE THE TOOLS THAT THESE PROFESIONALS ARE USING AND OF COURSE THE EVOLUTION OF BIOIMAGING IS FOCUSED TO COMPUTATIONAL MODELS AND THE IMAGE BIOMARKERS.
- #5: THE ARQUITECTURE OF THE SYSTEM CONSISTS OF….
- #6: AS YOU CAN SEE
- #7: THIS IMAGE REPOSITORY SUPORTS ALL IMAGES THAT ARE PRODUCED BY VALENCIAN HOSPITALS THIS REPOSITORY WILL OFFER SERVICES FOR DIFERENT APLICATIONS VIA STANDARD WADO (WEB ACCESS DICOM OBJECT)
- #8: CEIB IS AIMED TO BE A RE…
- #10: AND SO ON
- #11: I SHOW YOU A BRIEF SUMMARY OF THE WORKING LINES
- #12: IF WE FOCUS IN THE FIRST POINT OUR MAIN GOALS ARE 1 2 3
- #13: THE SECOND GOAL LEAD AS TO THE NEXT TOPICS
- #14: THE NEXT GOAL IS RELATED TO IMAGE POST-PORCESING THROUGH
- #15: THE NEXT GOAL IS COMPUTING SUPPORTED…
- #18: THE ARQUITECTURE OF OUR SYSTEM WILL CONSIS IN THE FUTURE OF A CLOUD CEIB R&D THAT IS COMPOSED BY GEBID AND BIKE
- #19: IS BASED IN XNAT FRAMEWORK WHICH ALLOWS THE ORGANITATION AND SHARING OF BIOIMAGE DATA
- #20: AS YOU CAN SEE THIS FRAMEWORK SUPPORS DIFERENT KINDS OF DATA RELATED TO CLINICAL TRIAL
- #21: XNAT ORGANIZES THE WORK FLOW IN CLINICAL TRIALS
- #22: XNAT FRAMEWORK IS DIVIDED IN THREE LEVELS
- #23: THE SECOND ELEMENT OF CLOUD CEIB R&D IS BIKE THAT MEANS… THIS IS OUR CONCEPTUAL FRAMEWORK TO HIGH COMPUTATIONAL FOR BIOMEDICAL IMAGING WE HAVE TWO CRITERIA IN ORDER TO DEVELOP THIS …..
- #24: I WANT TO REMARK THAT ALL OUR SYSTEM IS BASED BY OPEN SOURCE
- #25: Figura 2 Proceso de extracción de información relevante mediante la creación de imágenes paramétricas
- #26: Izquierda, reconstrucción 3D de hueso trabecular extraída a partir de imágenes de RM de alta resolución espacial. Centro, conversión de la geometría de la estructura trabecular a un modelo de elementos finitos basado en peque˜nos elementos hexaedro. En esta imagen tridimensional, cada peque˜no cubo corresponde a un elemento finito. Cada elemento tiene unas propiedades físicoquímicas, correspondientes a hueso en este ejemplo, y está unido al resto de elementos finitos formando una malla. Derecha, mapa paramétrico de las tensiones nodales resultado de la simulación de compresión de la estructura trabecular. Valores elevados (codificados en rojo) indican tensiones nodales elevadas, es decir, regiones que se corresponden con un mayor riesgo de rotura.
- #27: Figura 1 Mapa de procesos para el establecimiento y validación de un biomarcador de imagen. En la parte izquierda de la figura se representan los ítems médico-asistenciales y en la derecha los metodológicos.
- #28: Figura 2 Proceso de extracción de información relevante mediante la creación de imágenes paramétricas
- #29: DICOM TAGS
- #30: I WANT TO CONFESS YOU THAT WE HAVE A DREAM….. FOR EXAMPLE WIHT HIGH SPECIALIZAD REPORTS
- #33: THIS IS OUR PROPOSAL AND THANS FOR YOUR ATTENTION