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Automatic analysis method of protein expression images based on generalized data field

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4 Author(s)
Shuliang Wang ; Int. Sch. of Software, Wuhan Univ., Wuhan, China ; Ying Li ; Wenchen Tu ; Peng Wang

For detection of protein expression in biomedicai image, shape measurement of protein expression mostly depends on semi-automatic analysis of image analysis software which makes the results vulnerable to subjective factors, since the automatic analysis is too complicated to operate. Therefore, a novel algorithm based on generalized data field (GDF) is proposed to determine the region of protein expression. Instead of being directly divided into the measured object and background, all the data objects, namely pixels of an image, are naturally clustered into multiple classes based on potential distribution in generalized data field. Each class represents protein expression in different degree, which precisely describes the details of protein expression. Compared with image-pro plus software analysis, KM and EM, experiment results demonstrate that the protein expression can be extracted easily and objectively from an image by GDF. Furthermore, noises of background are eliminated by the smoothing procedure of GDF.

Published in:

Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on

Date of Conference:

4-7 Oct. 2012

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