02320nas a2200133   4500008004100000020001400041245006400055210006300119260001200182300001400194490000700208520193000215856004102145       2002                        eng d  a1524-070300aFuzzy-connected 3D image segmentation at interactive speeds0 aFuzzyconnected 3D image segmentation at interactive speeds  c2002///  a259 - 2810 v643 aImage segmentation techniques using fuzzy connectednessprinciples hake shown their effectiveness in segmenting a 
variety of objects in several large applications in recent 
years. However, one problem with these algorithms has been their 
excessive computational requirements. In an attempt to 
substantially speed them up. in the present paper, we study 
systematically a host of 18 'optimal' graph search algorithms. 
Extensive testing of these algorithms on a variety of 3D medical 
images taken from large ongoing applications demonstrates that a 
20 1000-fold improvement over current speeds is achievable with 
a combination of algorithms and last modern PCs. Utilizing 
efficient algorithms and careful selection of implementations 
can speed up the computation of fuzzy connectedness values by a 
factor of 16 29 (on the same hardware), as compared to the 
implementation previously used in our applications utilizing 
fuzzy object segmentation. The optimality of an algorithm 
depends on the input data as well as on the choice of the fuzzy 
affinity relation. The running time is reduced considerably (by 
a factor up to 34 for brain MR and even more for bone CT), when 
the algorithms make use of predetermined thresholds for the 
fuzz), objects. The reliable recognition (assisted by human 
operators) and the accurate, efficient. and sophisticated 
delineation (automatically performed by the computer) can be 
effectively incorporated into a single interactive process. If 
images having intensities kith tissue-Specific meaning (such Lis 
CT or standardized MR images) are utilized. most of the 
parameters for the segmentation method can be fixed once for 
all. all, intermediate data (feature and fuzzy affinity values 
for the hole scene) can be computed before the user interaction 
is needed and the user can be provided kith more information at 
the little of interaction.
  uhttps://inf.u-szeged.hu/en/node/1001