Titelaufnahme

Titel
Parallel volume image segmentation with watershed transformation
Verfasser/ VerfasserinWagner, B. ; Dinges, A. ; Müller, P. ; Haase, Gundolf In der Gemeinsamen Normdatei der DNB nachschlagen
Erschienen in
Image Analysis / Salberg, A. B.; Hardeberg, J. Y.; Jenssen, R., Heidelberg, 2009, S. 420-429
Erschienen2009
Ausgabe
Accepted version
SpracheEnglisch
SerieLNCS ; 5575
DokumenttypAufsatz in einem Sammelwerk
Schlagwörter (EN)parallel watershed / SIMD / stream computing / CUDA / gpgpu
ISBN978-3-642-02230-2
URNurn:nbn:at:at-ubg:3-4239 Persistent Identifier (URN)
Zugriffsbeschränkung
 Das Werk ist frei verfügbar
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Parallel volume image segmentation with watershed transformation [0.45 mb]
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Zusammenfassung (Englisch)

In this paper we propose a novel approach to parallel image segmentation of volume images using the watershed transformation on stream computing platforms. The watershed transformation is a powerful mathematical morphology method for gray-scale image segmentation. It is widely used in medical, technical, biological and other image analysis applications, mostly for extracting homogeneous areas with respect to the gray-value gradient. However the watershed-transformation is a very computation intensive task. With the increasing programmability of graphic processing units, a cheap and powerful high performance computing platform is available. We present an algorithm that was especially adapted for stream processing and give a brief formal explanation of the correctness of our method. We also discuss our exemplary implementation for the NVidia CUDA platform and show speedup measurements for sample volume datasets.

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