02326nas a2200133   4500008004100000020001400041245006400055210006300119260001200182300001400194490000700208520193000215856004702145       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://tisat.inf.u-szeged.hu/en/node/100101680nas a2200109   4500008004100000245006400041210006300105260004200168300001400210520129900224856004701523       2000                        eng d00aFuzzy-connected 3D image segmentation at interactive speeds0 aFuzzyconnected 3D image segmentation at interactive speeds  aBellingham; WashingtonbSPIEc2000///  a212 - 2233 aImage segmentation techniques using fuzzy connectednessprinciples have 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 algorithms under two categories -- 
label correcting and label setting. Extensive testing of these 
algorithms on a variety of 3D medical images taken from large 
ongoing applications demonstrates that a 20 - 360 fold 
improvement over current speeds is achievable with a combination 
of algorithms and fast modern PCs. 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 with tissue 
specific meaning (such as CT or standardized MR images) are 
utilized, all parameters for the segmentation method can be 
fixed once for all, all intermediate data can be computed before 
the user interaction is needed, and the user can be provided 
with more information at the time of interaction.
  uhttps://tisat.inf.u-szeged.hu/en/node/101400316nas a2200085   4500008004100000245006500041210006500106260001200171856004700183       1999                        eng d00aFuzzy Connected 3D Object Segmentation at Interactive Speeds0 aFuzzy Connected 3D Object Segmentation at Interactive Speeds  c1999///  uhttps://tisat.inf.u-szeged.hu/en/node/1071