SIMA: Python software for analysis of dynamic fluorescence imaging data thumbnail
SIMA: Python software for analysis of dynamic fluorescence imaging data
www.frontiersin.org
The normalized cuts approach to segmentation (Shi and Malik, 2000) is a novel technique for the segmentation of dynamic fluorescence imaging data and is complementary to existing approaches, such as spatio-temporal independent complement analysis
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  • The normalized cuts approach to segmentation (Shi and Malik, 2000) is a novel technique for the segmentation of dynamic fluorescence imaging data and is complementary to existing approaches, such as spatio-temporal independent complement analysis

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