Multi-Seed Region Growing Algorithmfor Medical Image Segmentation
Marco Gierlinger, Dinah Brandner, Bernhard G. Zagar
Kapitel/Beitrag aus dem Buch: Heizmann M. & Längle T. 2020. Forum Bildverarbeitung 2020.
Part of
Kapitel/Beitrag aus dem Buch: Heizmann M. & Längle T. 2020. Forum Bildverarbeitung 2020.
We present a heuristic approach to segment an image
into multiple regions for subsequent feature extraction.
The algorithm is based on region growing and allows parallel
implementation by employing multiple seeds, that independently
grow a region until all pixels of the image have been
assigned. Seeds are homogeneously dispersed in pixel space
and the growth of regions is controlled by prioritizing neighboring
pixels via a bucket queue. The heuristic is based on
histograms that are built up during growth to derive binary
images for each seed. These binary images are weighted by
additive image fusion. A simple preprocessing technique is
applied to tune the algorithm’s outcome. We explain how input
parameters influence the algorithm’s outcome and how
practical solutions can be obtained.
Gierlinger, M et al. 2020. Multi-Seed Region Growing Algorithmfor Medical Image Segmentation. In: Heizmann M. & Längle T (eds.), Forum Bildverarbeitung 2020. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.58895/ksp/1000124383-21
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Veröffentlicht am 25. November 2020