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Structural annotation of em images by graph cut
2009
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Biological images have the potential to reveal complex signatures that may not be amenable to morphological modeling in terms of shape, location, texture, and color. An effective analytical method is to characterize the composition of a specimen based on user-defined patterns of texture and contrast formation. However, such a simple requirement demands an improved model for stability and robustness. Here, an interactive computational model is introduced for learning patterns of interest by
doi:10.1109/isbi.2009.5193249
dblp:conf/isbi/ChangAP09
fatcat:kn7ts3rnkfhxvexiyj6staubzy