Statistical models of shape and appearance are powerful tools for interpreting medical
images. We assume a training set of images in which corresponding landmark points have …

Motion of physical objects is non-rigid, in general. Most researchers have focused on the
study of the motion and structure of rigid objects because of its simplicity and elegance …

We describe a method for automatically building statistical shape models from a training set
of example boundaries/surfaces. These models show considerable promise as a basis for …

Written by leading researchers, the 2nd Edition of the Dictionary of Computer Vision & Image
Processing is a comprehensive and reliable resource which now provides explanations of …

We present a new approach for the analysis of the left ventricular shape and motion that is
based on the development of a new class of volumetric deformable models. We estimate the …

Motion of physical objects in the world is, in general, nonrigid. In robotics and computer
vision, the motion of nonrigid objects is of growing interest to researchers from a wide …

Proposes and validates the hypothesis that one can use differential shape properties of the
myocardial surfaces to recover dense field motion from standard three-dimensional (3-D) …

A new approach to the problem of automatic construction of eigenshape models is
presented. Eigenshape models have proved to be successful in a variety of medical image …

A framework for automatic landmark identification is presented based on an algorithm for
corresponding the boundaries of two shapes. The auto-landmarking framework employs a …

A previous publication has described a method of pairwise three-dimensional (3D) surface
correspondence for the automated generation of landmarks on a set of examples from a …