Image processing and reconstruction of cultured neuron skeletons

No Thumbnail Available
File version
Author(s)
Yu, Donggang
D. Pham, Tuan
Yan, Hong
S. Jin, Jesse
Luo, Suhuai
Crane, Denis
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2008
Size
File type(s)
Location
License
Abstract

One approach to investigating neural death is through systematic studies of the changing morphology of cultured brain neurons in response to cellular challenges. Image segmentation and neuron skeleton reconstruction methods developed to date to analyze such changes have been limited by the low contrast of cells. In this paper we present new algorithms that successfully circumvent these problems. The binary method is based on logical analysis of grey and distance difference of images. The spurious regions are detected and removed through use of a hierarchical window filter. The skeletons of binary cell images are extracted. The extension direction and connection points of broken cell skeletons are automatically determined, and broken neural skeletons are reconstructed. The spurious strokes are deleted based on cell prior knowledge. The reconstructed skeletons are processed furthermore by filling holes, smoothing and extracting new skeletons. The final constructed neuron skeletons are analyzed and calculated to find the length and morphology of skeleton branches automatically. The efficacy of the developed algorithms is demonstrated here through a test of cultured brain neurons from newborn mice.

Journal Title

International Journal of Hybrid Intelligent Systems

Conference Title
Book Title
Edition
Volume

5

Issue

4

Thesis Type
Degree Program
School
DOI
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Image Processing

Artificial Intelligence and Image Processing

Cognitive Sciences

Persistent link to this record
Citation
Collections