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Quantification of Retinopathy of Prematurity via Vessel Segmentation

  • Julien Jomier
  • David K. Wallace
  • Stephen R. Aylward
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2879)

Abstract

Retinopathy of prematurity is a disease that affects the eyes of many babies who are prematurely born. If the retinopathy is not detected in the days following birth blindness may occur. Studies have demonstrated that by observing the blood vessels within the retina, the disease can be quantified in an early stage and early treatment can save the baby’s eyes. We have developed a new tool to assess retinopathy of prematurity. Our technique captures images of the retina to extract and quantify both tortuosity and dilation of blood vessels. Our approach demonstrates a 80% sensitivity and 92% specificity in the prediction of retinopathy compared to experts and shows a significant reduced diagnosis time and clinical integration via speech recognition and glare detection.

Keywords

Speech Recognition Reference Image Vessel Segmentation Retinal Blood Vessel Initial Starting Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Julien Jomier
    • 1
  • David K. Wallace
    • 2
  • Stephen R. Aylward
    • 1
  1. 1.Department of RadiologyComputer-Aided Diagnosis and Display Lab 
  2. 2.Department of OpthalmologyThe University of North Carolina at Chapel HillChapel HillUSA

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