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Methods for segmentation of medical images are divided into three generations, where each generation adds an additional level of algorithmic complexity. The first generation is composed of the simplest forms of image analysis such as the use of intensity thresholds and region growing. The second generation is characterized by the application of uncertainty models and optimization methods, and the third generation incorporates knowledge into the segmentation process. Sources of segmentation software from industry and academia are identified along with databases for segmentation validation.
Withey et al. (Mon,) studied this question.
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