@techreport{TR-IC-10-08,
   number = {IC-10-08},
   author  =  {Paulo A. V. Miranda and Alexandre X. Falcão and Jayaram
                   K. Udupa},
   title  =  {{Cloud  Models:  Their  Construction  and  Employment in
                   Automatic MRI Segmentation of the Brain}},
   month = {March},
   year = {2010},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 18 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       A  \emph{cloud} is a triple consisting of a fuzzy object model,
       a   delineation   algorithm,   and  a  criterion  function  for 
       evaluating delineations. It employs recognition and delineation
       in  a  tightly coupled manner to accomplish image segmentation.
       It  captures shape variations of a given object/object assembly
       to  form  an uncertainty region for its boundary. For any image
       position,  delineation is executed in the uncertainty region to
       obtain  a  candidate  object/object assembly, and the criterion
       function  assigns  a score to it. Image segmentation is defined
       by the candidate with the highest score. This work presents and
       compares   three   cloud   models   in  automatic  MR-T1  image 
       segmentation  of  the  cerebrum,  the  cerebellum, and cerebral
       hemispheres.  These  structures are connected in several parts,
       imposing serious segmentation challenges. The results show that
       the   methods  are  fast,  accurate,  and  can  eliminate  user 
       intervention  or,  at  least,  reduce it to simple corrections.
       Their  applications  go beyond medical imaging to new vistas in
       various areas served by image segmentation.
  }
}