Introduction

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.

Publications

  1. 3D cell nuclei segmentation based on gradient flow tracking.
    Cite this
    Li G, Liu T, Tarokh A, Nie J, Guo L, Mara A, Holley S, Wong ST, 2007-01-01 - BMC cell biology

Credits

  1. Gang Li
    Developer

  2. Tianming Liu
    Developer

  3. Ashley Tarokh
    Developer

  4. Jingxin Nie
    Developer

  5. Lei Guo
    Developer

  6. Andrew Mara
    Developer

  7. Scott Holley
    Developer

  8. Stephen T C Wong
    Investigator

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT006365
Tool TypeApplication
Category
PlatformsLinux/Unix
Technologies
User InterfaceTerminal Command Line
Download Count0
Submitted ByStephen T C Wong