This paper investigates, using prior shape models and the concept of ball
scale (b-scale), ways of automatically recognizing objects in 3D images without
performing elaborate searches or optimization. That is, the goal is to place
the model in a single shot close to the right pose (position, orientation, and
scale) in a given image so that the model boundaries fall in the close vicinity
of object boundaries in the image. This is achieved via the following set of
key ideas: (a) A semi-automatic way of constructing a multi-object shape model
assembly.
Acquisition-to-acquisition signal intensity variations (non-standardness) are
inherent in MR images. Standardization is a post processing method for
correcting inter-subject intensity variations through transforming all images
from the given image gray scale into a standard gray scale wherein similar
intensities achieve similar tissue meanings. The lack of a standard image
intensity scale in MRI leads to many difficulties in tissue characterizability,
image display, and analysis, including image segmentation.