Images are by nature fuzzy. Approaches to object information extraction from images should
attempt to use this fact and retain fuzziness as realistically as possible. In past image …

The ability to visualize, non-invasively, human internal organs in their true from and shape
has intrigued mankind for centuries. While the recent inventions of medical imaging …

To aid in the display, manipulation, and analysis of biomedical image data, they usually
need to be converted to data of isotropic discretization through the process of interpolation. …

One of the major drawbacks of magnetic resonance imaging (MRI) has been the lack of a
standard and quantifiable interpretation of image intensities. Unlike in other modalities, such …

… interactions between one of the authors of this paper (Udupa) and Barrett of Brigham Young
University. Udupa introduced some of his graph model and optimum boundary formulations […

The lack of a standard image intensity scale in MRI causes many difficulties in image display
and analysis. A two‐step postprocessing method is proposed for standardizing the intensity …

A shape-based interpolation scheme for multidimensional images is presented. This scheme
consists of first segmenting the given image data into a binary image, converting the binary …

The purpose of this paper is to describe a framework for evaluating image segmentation
algorithms. Image segmentation consists of object recognition and delineation. For evaluating …

This paper extends a previously reported theory and algorithms for object definition based
on fuzzy connectedness. In this approach, a strength of connectedness is determined …

Multiple sclerosis (MS) is a disease of the white matter. Magnetic resonance imaging (MRI)
is proven to be a sensitive method of monitoring the progression of this disease and of its …