Fast and accurate identification of fat droplets in histological images
Fast and accurate identification of fat droplets in histological images
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DOI：
10.1016/j.cmpb.2015.05.009
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发表时间：
2015-09-01
影响因子：
6.1
通讯作者：
Hahn, Horst K.
中科院分区：
文献类型：
--
作者：
Homeyer, Andre;Schenk, Andrea;Hahn, Horst K.
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 0.05 s.Conclusions: The presented method is simple to implement and can provide the basis for the fast and accurate quantification of steatosis. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
