3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

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3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

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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

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