« View All Resources
Active Geometric Shape Models
Quan Wang - Posted on September 26, 2012 at 6:07 pm.
The active geometric shape model (AGSM) is a novel approach for fitting a geometric shape in images. Similar to active shape models and active contours, a force field is used in this approach. But the object to be detected is described with a geometric shape, represented by parametric equations. AGSM associates each parameter of this geometric shape with a combination of integrals (summations in the discrete case) of the force field along the contour. By iteratively updating the shape parameters according to these integrals, the optimal fit of the shape in the image can be found. This technique has been used to detect the cross-sections of subarachnoid spaces containing cerebrospinal fluid (CSF) in phase-contrast magnetic resonance (PC-MR) images, where the object of interest can be described by a distorted ellipse. The detection results can be further used by an s-t graph cut to generate a segmentation of the CSF structure. Given a properly configured geometric shape model and force field, this approach is robust to noise and defects (disconnections and non-uniform contrast) in the image. By using a geometric shape model, this approach does not rely on large training datasets, and requires no manual labeling of the training images as is needed when using point distribution models.
Download Attached File