Significados de base segmentation en inglés

Statistical model- based segmentation of the left ventricles has received considerable attention these years.

This study presented a new concept of atlas based segmentation method.

Multi-atlas based segmentation methods have attracted great interest due to their promising performance.

We propose a semi-supervised, kinetic modeling based segmentation technique for molecular imaging applications.

Atlas- based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation.

An automated atlas- based segmentation algorithm was used to generate volumetric measures of the amygdala and hippocampus.

Finally, methods for an evaluation of the atlas- based segmentation and the atlas-based landmark detection are explained.

Different diffusion measures were evaluated using both a region of interest (ROI) - based and a diffusion tensor tractography- based segmentation approach.

The classification algorithm operates on the focal lesions identified during detection, and includes shape- based segmentation, edge pixel weighting, and lesion texture filtering.

Conclusion: A framework for organ delineation in radiotherapy planning is presented, including automated 3D model- based segmentation, as well as tools for interactive corrections.

A novel atlas- based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established.

Although many atlas- based segmentation methods have been developed and validated for the human brain, limited work has been done for the mouse brain.

Multi-atlas based segmentation is an effective technique that transforms a representative set of atlas images and labels into a target image for structural segmentation.

The smooth muscle surface density was measured in both groups by two different observers by the point-counting method and by the color- based segmentation method.

Results: A first evaluation of the presented atlas- based segmentation method shows the correct labeling of 98.5% of the bony voxels.

In this paper, we propose a new method for level set based segmentation of blood vessels by generalizing the FLUX on a Riemannian manifold (R-FLUX).