Medical image fusion is the process of registering and combining multiple images from
single or multiple imaging modalities to improve the imaging quality and reduce …

Automatic medical image segmentation is an unsolved problem that has captured the
attention of many researchers. The purpose of this survey is to identify a representative set of …

Regions in three-dimensional magnetic resonance (MR) brain images can be classified
using protocols for manually segmenting and labeling structures. For large cohorts, time and …

The goal of this work was to develop a method for accurate and robust automatic
segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images …

Abstract KS 0, Λ, Ξ, Ω and negative particle h− yields and transverse mass spectra,
measured at central rapidity in p-Pb and Pb-Pb collisions at 158 A GeV/c, are presented and …

We compare three widely used brain volumetry methods available in the software packages
FSL, SPM5, and FreeSurfer and evaluate their performance using simulated and real MR …

We present a preliminary design and experimental results of tumor objects tracking method
for magnetic resonance imaging (MRI) brain images (some stock images) that utilizes color …

Fully-automated brain segmentation methods have not been widely adopted for clinical use
because of issues related to reliability, accuracy, and limitations of delineation protocol. By …

A new method has been developed for probabilistic segmentation of five different types of
brain structures: white matter, gray matter, cerebro-spinal fluid without ventricles, ventricles …

A framework of fuzzy information fusion is proposed in this paper to automatically segment
tumor areas of human brain from multispectral magnetic resonance imaging (MRI) such as …