NDLI: Adaptive cell nuclei detection from fluorescence images by optimizing object sizes

Content Provider	IEEE Xplore Digital Library
Author	Bashar, M.K. Fujimori, T. Komatsu, K. Kobayashi, T.J.
Copyright Year	2012
Description	Author affiliation: Division of Embryology, National Institute for Basic Biology, Okazaki, Aichi, Japan (Komatsu, K.) \|\| Medical Corporation Kishokai, Bell Research Center, Nagoya, Aichi, Japan (Fujimori, T.) \|\| Institute of Industrial Science, The University of Tokyo, Japan (Bashar, M.K.; Kobayashi, T.J.)
Abstract	Although a few attempts were observed, there are high biological demands for the extraction of three dimensional cell nuclei from cellular images. Most common methods are manual and their results include subjective errors. Some other methods apply segmentation followed by centroid extraction. However, high dimensional segmentation is still unreliable, especially for biomedical images having juxtaposed cells. In this research, we propose direct method that exploits intensity distribution and object geometry to extract nuclei centroids from fluorescence microscopy images. A spatiotemporal adaptive multiscale filtering is applied for the object enhancement with noise suppression. A two-stage procedure is then followed. In Stage-1, we extract candidate centroids for the probable cell nuclei based on a local characteristic ratio (R) at every voxel. In Stage-2, an iterative procedure is proposed, which estimates approximate object radius from each candidate centroid by maximizing mean intensity gradients over successive pairs of regions in the enhanced image and removing smaller spurious objects. Investigations and quantitative analysis with a set 100 3D mouse embryo images reveal a promising performance of the proposed method in terms of average sensitivity and positional error, compared to an existing method.
Starting Page	621
Ending Page	626
File Size	421190
Page Count	6
File Format	PDF
ISBN	9781467316644
e-ISBN	9781467316668
DOI	10.1109/IECBES.2012.6498044
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Characteristics voxel ratio Intensity gradient tracking Adaptive multiscale cube filtering
Content Type	Text
Resource Type	Article

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