1 July 2009 Image segmentation for biomedical applications based on alternating sequential filtering and watershed transformation
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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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. Gorpas, D. Gorpas, D. Yova, 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); doi: 10.1117/12.831715; https://doi.org/10.1117/12.831715
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