16 April 1996 Genetic algorithms applied to Fourier-descriptor-based geometric models for anatomical object recognition in medical images
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Abstract
In this work we encode the shape complexity of a search object using 3D Fourier descriptors (FDs) and allow genetic algorithms (GAs) to optimize the object's shape and position. Using magnetic resonance image (MRI) data, we perform an approximate segmentation on one lateral ventricle in the brain and use the FDs from this as seeding values for the GAs to search for the left and right lateral ventricles in subsequent 3D data sets. We show that the method is capable of coping with normal biological variation. We compare a GA-guided segmentation with an interactive region growing method and find an agreement of not less than 80 plus or minus 6% in voxel classification with a corresponding average edge placement error of 2.2 plus or minus 0.4 mm. Finally we examine how the optimization can be speeded up by a distributed parallel implementation.
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Kostas Delibasis, Peter E. Undrill, George G. Cameron, "Genetic algorithms applied to Fourier-descriptor-based geometric models for anatomical object recognition in medical images", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); doi: 10.1117/12.237967; https://doi.org/10.1117/12.237967
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