ABSTRACT
Magnetic resonance imaging (MRI) segmentation provides important information for detecting a variety of tumors, lesions, and abnormalities in clinical diagnosis. The segmentation can be described as the definition of clusters whose points are associated to similar sets of intensity values in the different images. An efficient analysis of dual-echo medical imaging volumes can be derived from a set of different diagnostic volumes carrying complementary information provided by medical imaging technology. The extraction of such volumes from imaging data is said to be segmentation, and it is usually performed, in the image space, defining sets of vowels with similar features within a whole dual-echo volume.
