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. 2017 May 26;18:280. doi: 10.1186/s12859-017-1694-9

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© The Author(s). 2017

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 4 — Freehand segmentation. (a) The user uses the mouse to paint on a visualization result to select structures. (b) Voxels are projected. The blue voxel is not selected because its projection is outside the painted region. (c) OpenCL kernels are used to estimate a threshold value. (c1) We generate a histogram for voxels within the shaded region. (c2) The histogram from the shaded region. (c3) We calculate a threshold value from the histogram. Low-intensity signals are usually noise and are excluded from the selection. (c4) Voxels with intensities higher than the threshold value are selected. (d) We cast rays backward to the viewer. The red one is rejected because its ray is obstructed by the green object. (e) We calculate a morphological diffusion to select surrounding structures of the green object based on connectivity