3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

DSpace/Manakin Repository

3D Cell Nuclei Segmentation Based on Gradient Flow Tracking

Citable link to this page

. . . . . .

Title: 3D Cell Nuclei Segmentation Based on Gradient Flow Tracking
Author: Li, Gang; Liu, Tianming; Tarokh, Ashley; Nie, Jingxin; Guo, Lei; Mara, Andrew; Holley, Scott; Wong, Stephen TC

Note: Order does not necessarily reflect citation order of authors.

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.
Full Text & Related Files:
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.
Published Version: doi://10.1186/1471-2121-8-40
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2064921/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10021572

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters