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Vessel Segmentation and Branching Detection Using an Adaptive Profile Kalman Filter in Retinal Blood Vessel Structure Analysis

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Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 2652))

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Abstract

This paper presents an improved tracking based method for retinal vessel segmentation that uses blood vessel morphology to adapt the tracking parameters. The method includes branching detection and avoidance methods. A bi-level threshold method, based on local vessel information, is used for segmentation. Tracking is based on Kalman filtering. The results are compared with existing ground truth. It is concluded that ground truth segmentation is not easily comparable.

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Author information

Authors and Affiliations

  1. Department of Physics Strand, King’s College London, London, England

    Pedro Quelhas & James Boyce

  2. IDIAP, Dalle Molle Institute for Perceptual Artificial Intelligence, Rue Du Simplon 4, Martigny, Switzerland

    Pedro Quelhas

Authors
  1. Pedro Quelhas

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  2. James Boyce

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Editor information

Editors and Affiliations

  1. Unitat de Gràfics i Visió per Ordinador Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears Edifici Anselm Turmeda, Ctra. de Valldemossa km 7,5, 07122, Palma de Mallorca, Spain

    Francisco José Perales

  2. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio J. C. Campilho

  3. Departamento de Ciencias da la Computacíon e I.A., Universidad de Granada, E.T. S. Ing. Informática, 18071, Granada, Spain

    Nicolás Pérez de la Blanca

  4. Dept. System Engineering and Automation, Universitat Politècnica de Catalunya (UPC) Barcelona, Spain

    Alberto Sanfeliu

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© 2003 Springer-Verlag Berlin Heidelberg

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Quelhas, P., Boyce, J. (2003). Vessel Segmentation and Branching Detection Using an Adaptive Profile Kalman Filter in Retinal Blood Vessel Structure Analysis. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_93

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Chapter
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eBook
JPY 5719
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
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Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
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Tax calculation will be finalised at checkout

Purchases are for personal use only


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