PUBLICATION
An Automated Method for Cell Detection in Zebrafish
- Authors
- Liu, T., Li, G., Nie, J., Tarokh, A., Zhou, X., Guo, L., Malicki, J., Xia, W., and Wong, S.T.
- ID
- ZDB-PUB-080306-10
- Date
- 2008
- Source
- Neuroinformatics 6(1): 5-21 (Journal)
- Registered Authors
- Liu, Tianming, Malicki, Jarema, Wong, Stephen T.C., Xia, Weiming
- Keywords
- Zebrafish, Alzheimer’s disease, Retina development, Image processing, Neuronal cell detection, Modeling
- MeSH Terms
-
- Algorithms*
- Animals
- Automation/methods
- Automation/standards
- Cell Count/methods
- Cell Death/physiology
- Central Nervous System/cytology*
- Central Nervous System/physiology
- Computer Simulation/standards*
- Computer Simulation/trends
- Fluorescent Antibody Technique/methods
- Image Cytometry/instrumentation
- Image Cytometry/methods*
- Immunohistochemistry/methods
- Microscopy, Fluorescence/methods
- Models, Animal
- Neurons/cytology*
- Neurons/physiology
- Retina/cytology
- Retina/physiology
- Software/standards
- Software/trends
- Software Design
- Staining and Labeling/methods
- Zebrafish/anatomy & histology*
- Zebrafish/physiology
- PubMed
- 18288618 Full text @ Neuroinformatics
Citation
Liu, T., Li, G., Nie, J., Tarokh, A., Zhou, X., Guo, L., Malicki, J., Xia, W., and Wong, S.T. (2008) An Automated Method for Cell Detection in Zebrafish. Neuroinformatics. 6(1):5-21.
Abstract
Quantification of cells is a critical step towards the assessment of cell fate in neurological disease or developmental models. Here, we present a novel cell detection method for the automatic quantification of zebrafish neuronal cells, including primary motor neurons, Rohon-Beard neurons, and retinal cells. Our method consists of four steps. First, a diffused gradient vector field is produced. Subsequently, the orientations and magnitude information of diffused gradients are accumulated, and a response image is computed. In the third step, we perform non-maximum suppression on the response image and identify the detection candidates. In the fourth and final step the detected objects are grouped into clusters based on their color information. Using five different datasets depicting zebrafish cells, we show that our method consistently displays high sensitivity and specificity of over 95%. Our results demonstrate the general applicability of this method to different data samples, including nuclear staining, immunohistochemistry, and cell death detection.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping