Feature representation and signal classification in fluorescence in-situ hybridization image analysis
نویسندگان
چکیده
منابع مشابه
Feature representation and signal classification in fluorescence in-situ hybridization image analysis
Fast and accurate analysis of fluorescence in-situ hybridization (FISH) images for signal counting will depend mainly upon two components: a classifier to discriminate between artifacts and valid signals of several fluorophores (colors), and well discriminating features to represent the signals. Our previous work has focused on the first component. To investigate the second component, we evalua...
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BACKGROUND Previous systems for dot (signal) counting in fluorescence in situ hybridization (FISH) images have relied on an auto-focusing method for obtaining a clearly defined image. Because signals are distributed in three dimensions within the nucleus and artifacts such as debris and background fluorescence can attract the focusing method, valid signals can be left unfocused or unseen. This ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
سال: 2001
ISSN: 1083-4427
DOI: 10.1109/3468.983421