Background And Objective: The accurate identification of fat droplets is a prerequisite for the automatic quantification of steatosis in histological images. A major challenge in this regard is the distinction between clustered fat droplets and vessels or tissue cracks.
Methods: We present a new method for the identification of fat droplets that utilizes adjacency statistics as shape features. Adjacency statistics are simple statistics on neighbor pixels.
Results: The method accurately identified fat droplets with sensitivity and specificity values above 90%. Compared with commonly-used shape features, adjacency statistics greatly improved the sensitivity toward clustered fat droplets by 29% and the specificity by 17%. On a standard personal computer, megapixel images were processed in less than 0.05s.
Conclusions: The presented method is simple to implement and can provide the basis for the fast and accurate quantification of steatosis.
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| http://dx.doi.org/10.1016/j.cmpb.2015.05.009 | DOI Listing |
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