ONCO-MEDIA

ONtology and COntext related MEdical image Distributed Intelligent Access

 

Regional program ICT-Asia, Research – Innovation, 2006 – 2010

Scientific challenges / Clinical Applications / Perspectives

 

ONCO-MEDIA Challenges: 

Ontology and COntext related MEdical image Distributed Intelligent Access

 

ONTOLOGY

                   Semantic Gap

                   Structured Medical Knowledge / Ontology

CONTEXT

                   Contextual Retrieval

                   Contextual Navigation

                   Contextual Query

MEDICAL

                   Privacy  issues

DISTRIBUTED PARALLEL COMPUTATION

                   Increase the computation capabilities (2D, 3D images)

                   Distributed medical databases

INTELLIGENT SYSTEMS

                   Data mining (neural networks, association rule mining,

                   intelligent inter-media fusion…)

ACCESS

                   Knowledge based similarity methods

                   Medical image / cases retrieval

 
Content Based Medical Image Retrieval approach in ONCO-MEDIA

CBMIR approach in ONCO-MEDIA:

 

Clinical decision support techniques

produce a stronger need to retrieve

images that can be valuable for

supporting diagnoses:

 

- Evidence-based medicine (EBM)

- Image/Case-based reasoning (IBR - CBR)

 

Decision support systems in radiology and CAD for radiological practice are on the rise and create a need for:

 

- Powerful data and meta-data management

          and retrieval

- Medical Multimedia Datamining

- Medical Process Flowchart Mining
Context in CBMIR using the medical gridIBR - Image Based Reasonning principleEBM - Evidence Based Medecine

Context in CBMIR using medical grid

CBMIR (Content-Based Medical Image Retrieval) approach in ONCO-MEDIA:
CNRS - French National Center for Scientific Research MAE - French Ministry of Foreign Affairs

 

Contact: 

 

 

 

Daniel RACOCEANU

French National Research Center - CNRS

A/Prof. (Dr. Habil.) University of Franche-Comté, France

Director of  IPAL - Image & Pervasive Access Lab, Singapore

International Research Unit (UMI CNRS, NUS, I2R A*STAR, UJF),

E-mail: daniel.racoceanu@ens2m.fr, URL : http://www.comp.nus.edu.sg/~danielr/