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» Guiding Model Search Using Segmentation
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ISBI
2011
IEEE
14 years 3 months ago
Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the...
Marius Erdt, Matthias Kirschner, Klaus Drechsler, ...
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
15 years 3 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
ISBI
2002
IEEE
16 years 15 days ago
Statistical shape models for segmentation and structural analysis
Biomedical imaging of large patient populations, both cross-sectionally and longitudinally, is becoming a standard technique for noninvasive, in-vivo studies of the pathophysiolog...
Guido Gerig, Martin Andreas Styner, Gábor S...
CVPR
2005
IEEE
16 years 1 months ago
Shape Regularized Active Contour Using Iterative Global Search and Local Optimization
Recently, nonlinear shape models have been shown to improve the robustness and flexibility of segmentation. In this paper, we propose Shape Regularized Active Contour (ShRAC) that...
Tianli Yu, Jiebo Luo, Narendra Ahuja
MICRO
1990
IEEE
147views Hardware» more  MICRO 1990»
15 years 3 months ago
Motivation and framework for using genetic algorithms for microcode compaction
Genetic algorithms are a robust adaptive optimization technique based on a biological paradigm. They perform efficient search on poorly-defined spaces by maintaining an ordered po...
Steven J. Beaty, Darrell Whitley, Gearold Johnson