Automatic contour propagation in cine cardiac magnetic resonance images.

We have developed a method for automatic contour propagation in cine cardiac magnetic resonance images. The method consists of a new active contour model that tries to maintain a constant contour environment by matching gray values in profiles perpendicular to the contour. Consequently, the contours should maintain a constant position with respect to neighboring anatomical structures, such that the resulting contours reflect the preferences of the user.

High-throughput screening using beta-lactamase reporter-gene technology for identification of low-molecular-weight antagonists of the human gonadotropin releasing hormone receptor.

G-protein coupled receptors (GPCRs) signal via G-proteins to intracellular second messengers. Assays that link transcription of a detectable reporter to promoters that are activated by such signaling cascades are highly sensitive and allow screening for compounds that either activate or inactivate a GPCR of interest. This study describes the development and performance of an antagonistic screen on the human gonadotropin releasing hormone receptor (GnRH-R).

Automated 3-D PDM construction from segmented images using deformable models.

In recent years, several methods have been proposed for constructing statistical shape models to aid image analysis tasks by providing a priori knowledge. Examples include principal component analysis of manually or semiautomatically placed corresponding landmarks on the learning shapes [point distribution models (PDMs)], which is time consuming and subjective. However, automatically establishing surface correspondences continues to be a difficult problem.

A discrete dynamic contour model.

A discrete dynamic model for defining contours in 2-D images is developed. The structure of this model is a set of connected vertices. With a minimum of interaction, an initial contour model can be defined, which is then automatically modified by an energy minimizing process.