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. 2013 Jun 19;29(13):i274–i282. doi: 10.1093/bioinformatics/btt225

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© The Author 2013. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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Fig. 2. — Four typical examples for target complex segmentation based on simulated data. Each row is an example, whereas each subfigure is a slice through the x-z plane in the 3D image. (A) Ground truth. (B) Simulated subtomograms at SNR 0.005 and tilt angle range (Section 3.1). (C) After Gaussian smoothing with automatic scale selection. (D) After Watershed segmentation. (E) After boundary segment detection. (F) Selected segment cluster from model based clustering. (G) Detected target complex regions

Inline graphic — Four typical examples for target complex segmentation based on simulated data. Each row is an example, whereas each subfigure is a slice through the x-z plane in the 3D image. (A) Ground truth. (B) Simulated subtomograms at SNR 0.005 and tilt angle range (Section 3.1). (C) After Gaussian smoothing with automatic scale selection. (D) After Watershed segmentation. (E) After boundary segment detection. (F) Selected segment cluster from model based clustering. (G) Detected target complex regions