The manifold assumption for high-dimensional data assumes that the data ...
Statistical shape modeling is an essential tool for the quantitative ana...
In current biological and medical research, statistical shape modeling (...
Statistical shape modeling (SSM) characterizes anatomical variations in ...
Localization and characterization of diseases like pneumonia are primary...
This work describes an unsupervised method to objectively quantify the
a...
Statistical shape modeling (SSM) has recently taken advantage of advance...
Statistical shape analysis is a very useful tool in a wide range of medi...
Unsupervised representation learning via generative modeling is a staple...
Spatial transformations are enablers in a variety of medical image analy...
Spatial transformations are enablers in a variety of medical image analy...
Deep networks are an integral part of the current machine learning parad...
Difficult image segmentation problems, for instance left atrium MRI, can...
Left atrium shape has been shown to be an independent predictor of recur...
Statistical shape modeling is an important tool to characterize variatio...