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Title: HEp-2 Staining Pattern Classification
Fulltext: PDF
Authors: Strandmark, Petter and Ulén, Johannes and Kahl, Fredrik
Year: 2012
Document Type:Conference Paper
Conference: International Conference on Pattern Recognition (ICPR)
Status: In Press
Refereed: Yes
Publisher: ffl
BibTeX item:BibTeX
Abstract: Classifying images of HEp-2 cells from indirect immunofluorescence has important clinical applications. We have developed an automatic method based on random forests that classifies an HEp-2 cell image into one of six classes. The method is applied to the data set of the ICPR 2012 contest. The previously obtained best accuracy is 79.3% for this data set, whereas we obtain an accuracy of 97.4%. The key to our result is due to carefully designed feature descriptors for multiple level sets of the image intensity. These features characterize both the appearance and the shape of the cell image in a robust manner.

 

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Last updated: 2012-01-17

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