3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

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3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

dc.contributor.author	Li, Gang
dc.contributor.author	Liu, Tianming
dc.contributor.author	Tarokh, Ashley
dc.contributor.author	Nie, Jingxin
dc.contributor.author	Guo, Lei
dc.contributor.author	Mara, Andrew
dc.contributor.author	Holley, Scott
dc.contributor.author	Wong, Stephen TC
dc.date.accessioned	2012-12-10T19:41:43Z
dc.date.issued	2007
dc.identifier.citation	Li, Gang, Tianming Liu, Ashley Tarokh, Jingxin Nie, Lei Guo, Andrew Mara, Scott Holley, and Stephen TC Wong. 2007. 3D cell nuclei segmentation based on gradient flow tracking. BMC Cell Biology 8: 40.	en_US
dc.identifier.issn	1471-2121	en_US
dc.identifier.uri	http://nrs.harvard.edu/urn-3:HUL.InstRepos:10021572
dc.description.abstract	Background: Reliable segmentation of cell nuclei from three dimensional (3D) microscopic images is an important task in many biological studies. We present a novel, fully automated method for the segmentation of cell nuclei from 3D microscopic images. It was designed specifically to segment nuclei in images where the nuclei are closely juxtaposed or touching each other. The segmentation approach has three stages: 1) a gradient diffusion procedure, 2) gradient flow tracking and grouping, and 3) local adaptive thresholding. Results: Both qualitative and quantitative results on synthesized and original 3D images are provided to demonstrate the performance and generality of the proposed method. Both the over-segmentation and under-segmentation percentages of the proposed method are around 5%. The volume overlap, compared to expert manual segmentation, is consistently over 90%. Conclusion: The proposed algorithm is able to segment closely juxtaposed or touching cell nuclei obtained from 3D microscopy imaging with reasonable accuracy.	en_US
dc.language.iso	en_US	en_US
dc.publisher	BioMed Central	en_US
dc.relation.isversionof	doi://10.1186/1471-2121-8-40	en_US
dc.relation.hasversion	http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2064921/pdf/	en_US
dash.license	LAA
dc.subject	tissue sections	en_US
dc.subject	algorithm	en_US
dc.subject	images	en_US
dc.subject	model	en_US
dc.title	3D Cell Nuclei Segmentation Based on Gradient Flow Tracking	en_US
dc.type	Journal Article	en_US
dc.description.version	Version of Record	en_US
dc.relation.journal	BMC Cell Biology	en_US
dash.depositing.author	Li, Gang
dc.date.available	2012-12-10T19:41:43Z
dash.affiliation.other	HMS^Otology and Laryngology	en_US