RETINA - Retinal Image Analysis

Goals

The goal of this project is to study existing and develop new accurate and reliable machine vision and pattern recognition methods for an automatic fundus image analysis. The main focus is on an accurate and reliable detection of evidences of the diabetes. Applications of the methods would be for example hospital level monitoring for progress of the disease, automatic screening system which delegates patients to further medical inspection and a support tool for medical decision making.

The secondary goal of the project is to develop a general tool for collecting general medical image data; the tool should have a proper user interface for medical doctors and provide easily understandable mechanisms to mark different kind of medical findings. The tool should utilize a general medical image description language to properly and reliably deliver the important information to the image processing experts.

The project is a collaborative effort between Laboratory of Information Processing, Lappeenranta University of Techonology and

1. Department of Ophthalmology, University of Kuopio (professor Hannu Uusitalo's research group).

The project is financially supported by

1. YTI Research Center, Mikkeli Polytechnic.

Sub-projects

News

Data collecting application is ready and first results of automatic processing are ready.

Contact information

Joni Kämäräinen	E-Mail	WWW	Post-doc researcher
Heikki Kälviäinen	E-Mail	WWW	Professor
Arto Kaarna	E-Mail	WWW	Professor
Markku Kuivalainen	E-Mail	WWW	Graduated 2005

Download

Source code

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Data sets

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Links to other resources

Research groups working on similar subjects
Institute for Signal Processing, University of Luebeck, Germany	Vessel segmentation

Documentation

Do not hesitate to to contact authors (e-mail, etc.) in order to retrieve copies or reprints of the following publications.

1. Articles in international scientific journals with referee practice
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2. Articles in international compilation works and in international scientific conference proceedings with referee practice
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5. Scientific monographs
   1. Kuivalainen, Markku, Retinal image analysis using machine vision, MSc (Diploma) thesis, Lappeenranta University of Technology. 2005.
      (PDF medium quality - 13MB) (PDF high quality - 45MB)
6. Other scientific publications
   1. Forsstrom, J., Kalesnykiene, V., Kuivalainen, M., Sorri, I., Uusitalo, H., Kamarainen, J., Automated Pattern Recognition for the Detection of Diabetic Changes in Digital Fundus Images, Poster abstract for ARVO 2005 Annual Meeting (Fort Lauderdale, Florida, 2005).