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Deep Neural Networks for Surface Segmentation Meet Conditional Random Fields
To the best of our knowledge, this is the first study to apply a 3-D neural network with a CRFs model for direct surface segmentation.
Optimal Multi-Object Segmentation with Novel Gradient Vector Flow Based Shape Priors
Shape priors have been widely utilized in medical image segmentation to improve segmentation accuracy and robustness.
Simultaneous Multiple Surface Segmentation Using Deep Learning
The task of automatically segmenting 3-D surfaces representing boundaries of objects is important for quantitative analysis of volumetric images, and plays a vital role in biomedical image analysis.
Optimal Surface Segmentation with Convex Priors in Irregularly Sampled Space
Optimal surface segmentation is a state-of-the-art method used for segmentation of multiple globally optimal surfaces in volumetric datasets.
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