Image segmentation for biomedical applications based on alternating sequential filtering and watershed transformation

D. Gorpas; D. Yova

doi:10.1117/12.831715

1 July 2009 Image segmentation for biomedical applications based on alternating sequential filtering and watershed transformation

D. Gorpas, D. Yova

Author Affiliations +

Proceedings Volume 7370, Molecular Imaging II; 73700F (2009) https://doi.org/10.1117/12.831715
Event: European Conferences on Biomedical Optics, 2009, Munich, Germany

Abstract

One of the major challenges in biomedical imaging is the extraction of quantified information from the acquired images. Light and tissue interaction leads to the acquisition of images that present inconsistent intensity profiles and thus the accurate identification of the regions of interest is a rather complicated process. On the other hand, the complex geometries and the tangent objects that very often are present in the acquired images, lead to either false detections or to the merging, shrinkage or expansion of the regions of interest. In this paper an algorithm, which is based on alternating sequential filtering and watershed transformation, is proposed for the segmentation of biomedical images. This algorithm has been tested over two applications, each one based on different acquisition system, and the results illustrate its accuracy in segmenting the regions of interest.

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D. Gorpas and D. Yova "Image segmentation for biomedical applications based on alternating sequential filtering and watershed transformation", Proc. SPIE 7370, Molecular Imaging II, 73700F (1 July 2009); https://doi.org/10.1117/12.831715

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