Discriminative Random Field Segmentation of Lung Nodules in CT Studies

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="683216.fig.003a" src="https://static.hindawi.com/articles/cmmm/volume-2013/683216/figures/683216.fig.003a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Inferred segmentation</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="683216.fig.003b" src="https://static.hindawi.com/articles/cmmm/volume-2013/683216/figures/683216.fig.003b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Ground truth segmentation</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="683216.fig.003c" src="https://static.hindawi.com/articles/cmmm/volume-2013/683216/figures/683216.fig.003c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>Unsegmented</td></tr></table></td></tr></table>

<table>Tumor 23: Comparison of inferred segmentation versus the ground truth labeling with the unsegmented subvolume for reference.</table>

Computational and Mathematical Methods in Medicine

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Figure 3

Figure 3: Discriminative Random Field Segmentation of Lung Nodules in CT Studies 