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- W2187268220 abstract "Automatic segmentation oftheliver hasthe potential toassist inthediagnosis ofdisease, preparation for organtransplantation, andpossibly assist intreatment planning. Thispaperpresents initial results fromworkthatextends on previous two-dimensional (2D)segmentation methodsby implementing fullthree-dimensional (3D)liver segmentation, usinga self-reparameterising discrete deformable model.This methodovercomes manyoftheweaknesses inherent in2D segmentation techniques, suchastheinability toautomatically segmentseparate lobesoftheliver ineachimageslice, and sensitivity toindividual-slice noise. Results arepresented showing volumetric andoverlap comparison oftwelveautomatically segmented livers withtheir corresponding manually segmented livers, whichweretreated asthegoldstandard forthis study." @default.
- W2187268220 created "2016-06-24" @default.
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- W2187268220 date "2006-01-01" @default.
- W2187268220 modified "2023-09-27" @default.
- W2187268220 title "Automatic 3DSegmentation oftheLiver fromComputed Tomography Images, aDiscrete Deformable Model Approach" @default.
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