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medGIFT retrieving medical images based on their visual content

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medGIFT retrieving medical images based on their visual content. SIS-Forum, ICT4D, WSIS ... 2003 H pitaux Universitaires de Gen ve. What will be presented ... – PowerPoint PPT presentation

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Title: medGIFT retrieving medical images based on their visual content


1
medGIFT retrieving medical images based on
their visual content
Henning Müller Service of medical
informatics University hospitals of
Geneva Geneva, Switzerland
  • SIS-Forum, ICT4D, WSIS
  • Geneva, 9.-13.12.2003

2
What will be presented
  • The University Hospitals of Geneva
  • Service of medical informatics
  • The role of open source
  • Content-based visual data access
  • Medical image retrieval
  • GIFT and medGIFT
  • Benefits from visual data access
  • demonstration

3
The University Hospitals of Geneva
  • 2,200 beds in 6 hospitals
  • Radiology gt13,000 images produced a day
  • Medical Informatics 60 people, many projects
  • Service for the hospital
  • Electronic patient record
  • Picture Archive
  • Research
  • Image processing, Natural Language Processing
  • E-toile
  • Teaching
  • Medical students, postgraduate course
  • Telemedicine

4
The role of Open Source Software
  • Source Code is freely available
  • Better software quality
  • Better documentation of source code
  • Vendor independence (no out of business problems)
  • Large base of potential developers
  • Publicly available knowledge
  • Software is often free of charge
  • The service needs to be paid
  • In developing countries often the only option
  • Publicly funded research projects should be OS

5
Content-based visual data access Situation
6
Content-based visual data access
  • Developed due to the exploding creation of
    multimedia data and the availability of it often
    on the web, but also within companies (CNN)
  • Annotation is expensive, thus only possible in
    commercially interesting domains
  • Subjectivity, spelling errors,
  • Goal is to have a data access based on
    automatically extracted visual features
  • Query by example Show me images like this one
  • Problem to have a starting point for a query
  • Advantages and problems need to be understood for
    proper use

7
Content-based visual data access example
Blobworld, Berkeley
8
Medical image retrieval
  • Access currently mainly by patient ID
  • No use of implicitly stored knowledge in the
    images
  • With film, nothing else is possible
  • Teaching databases offer text and structured data
  • Possibilities of content-based access
  • Teaching
  • Lecturers
  • Students
  • Research
  • Diagnostic aid
  • Especially for less experienced professionals

9
An example
Emphysema
Micro nodules
?
Emphysema
Macro nodules
10
GIFT and medGIFT
  • GNU Image Finding Tool (GIFT)
  • Framework of components
  • Server, clients, databases, feature extractors,
    query language
  • Open Source
  • medGIFT
  • Medical adaptation of GIFT
  • More importance for gray scales and textures
  • Interface that shows the diagnosis
  • Link with the teaching file
  • Specializations are foreseen
  • Research project

11
The Interface
12
Conclusions
  • Hospitals need science/research to advance in
    teaching and patient care
  • Open Source should be model for publicly funded
    research projects to create publicly available
    knowledge, and to reuse software
  • We will need new tools to manage the large
    amounts of audiovisual data that are being
    created
  • Content-based visual data access is one such tool
  • The introduction of it in the medical domain
    needs an effort of all partners and can pay off
    in the long run
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