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Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing

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Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4292))

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Abstract

We present a new spot lesion detection algorithm for retinal images with background diabetic retinopathy (DR) pathologies. The highlight of this algorithm is its capability to deal with all DR-related spot lesions of various sizes and shapes that is accomplished by a unique adaptive multiscale morphological processing technique. A scale map is generated to delineate lesion areas based an edge model, and it is used to fuse multiscale morphological processing results for lesion enhancements. The local/releative entropy thresholding techniques are employed to segment lesion regions, and a scale-guided validation process is used to remove over-detections based on the scale map. The proposed algorithm is tested on 30 retinal images where all spot lesions are hand-labelled for performance evaluation. Compared with two existing algorithms, the proposed one significantly improves the overall performance of spot lesion detection producing higher sensitivity and/or predictive values.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, 74078, USA

    Xin Zhang & Guoliang Fan

Authors
  1. Xin Zhang
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  2. Guoliang Fan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Intel, 95052, Santa Clara, CA, USA

    Ara Nefian

  7. University of California, 430, Computer Science Building, 92697-3425, Irvine, CA, USA

    Gopi Meenakshisundaram

  8. Institute for Data Analysis and Visualization, P.O. Box

    Valerio Pascucci

  9. Department of Computer Science and Engineering, Czech Technical University in Prague, Czech

    Jiri Zara

  10. Rockwell Scientific, 1049 Camino Dos Rios, 91360, Thousand Oaks, CA, USA

    Jose Molineros

  11. Computer Graphics Group, Bielefeld University, D-33501, Bielefeld, Germany

    Holger Theisel

  12. Hewlett Packard Labs, Palo Alto, CA, USA

    Tom Malzbender

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, X., Fan, G. (2006). Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919629_50

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  • DOI: https://doi.org/10.1007/11919629_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48626-8

  • Online ISBN: 978-3-540-48627-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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