6 March 2015 Boundary fitting based segmentation of fluorescence microscopy images
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Abstract
Segmentation is a fundamental step in quantifying characteristics, such as volume, shape, and orientation of cells and/or tissue. However, quantification of these characteristics still poses a challenge due to the unique properties of microscopy volumes. This paper proposes a 2D segmentation method that utilizes a combination of adaptive and global thresholding, potentials, z direction refinement, branch pruning, end point matching, and boundary fitting methods to delineate tubular objects in microscopy volumes. Experimental results demonstrate that the proposed method achieves better performance than an active contours based scheme.
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Soonam Lee, Paul Salama, Kenneth W. Dunn, Edward J. Delp, "Boundary fitting based segmentation of fluorescence microscopy images", Proc. SPIE 9408, Imaging and Multimedia Analytics in a Web and Mobile World 2015, 940805 (6 March 2015); doi: 10.1117/12.2085417; https://doi.org/10.1117/12.2085417
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