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Maria de la Iglesia - CEIB: a R&D services in bioimaging oriented to integration of environments with her on cloud computing
1.
2. INTRODUCTION
• Introduction
• Current status of bioimaging in the AVS
(Valencia Health Agency)
• CEIB Objectives
• Project Overview
• System parts
• R&D
• Conclusions
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
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
Notes de l'éditeur
C – E - I – B : CENTRE OF EXCELENCE FOR BIOMEDICAL IMAGING, IN SPANISH CEIB-AVS
I WILL DIVIDE MY PRESENTATION IN THIS TOPICS I WILL TAK ABOUT
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.
THE ARQUITECTURE OF THE SYSTEM CONSISTS OF….
AS YOU CAN SEE
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)
CEIB IS AIMED TO BE A RE…
AND SO ON
I SHOW YOU A BRIEF SUMMARY OF THE WORKING LINES
IF WE FOCUS IN THE FIRST POINT OUR MAIN GOALS ARE 1 2 3
THE SECOND GOAL LEAD AS TO THE NEXT TOPICS
THE NEXT GOAL IS RELATED TO IMAGE POST-PORCESING THROUGH
THE NEXT GOAL IS COMPUTING SUPPORTED…
THE ARQUITECTURE OF OUR SYSTEM WILL CONSIS IN THE FUTURE OF A CLOUD CEIB R&D THAT IS COMPOSED BY GEBID AND BIKE
IS BASED IN XNAT FRAMEWORK WHICH ALLOWS THE ORGANITATION AND SHARING OF BIOIMAGE DATA
AS YOU CAN SEE THIS FRAMEWORK SUPPORS DIFERENT KINDS OF DATA RELATED TO CLINICAL TRIAL
XNAT ORGANIZES THE WORK FLOW IN CLINICAL TRIALS
XNAT FRAMEWORK IS DIVIDED IN THREE LEVELS
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 …..
I WANT TO REMARK THAT ALL OUR SYSTEM IS BASED BY OPEN SOURCE
Figura 2 Proceso de extracción de información relevante mediante la creación de imágenes paramétricas
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.
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.
Figura 2 Proceso de extracción de información relevante mediante la creación de imágenes paramétricas
DICOM TAGS
I WANT TO CONFESS YOU THAT WE HAVE A DREAM….. FOR EXAMPLE WIHT HIGH SPECIALIZAD REPORTS