Coupled shape distribution-based segmentation of multiple objects.
In this paper we develop a multi-object prior shape model for use in curve evolution-based image segmentation. Our prior shape model is constructed from a family of shape distributions (cumulative distribution functions) of features related to the shape. Shape distribution-based object representations possess several desired properties, such as robustness, invariance, and good discriminative and generalizing properties. Further, our prior can capture information about the interaction between multiple objects. We incorporate this prior in a curve evolution formulation for shape estimation. We apply this methodology to problems in medical image segmentation.
Litvin
Andrew
A
Boston University, Boston, Massachusetts, USA. litvin@bu.edu
Karl
William C
WC
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity