Image enhancement for tracking the translucent larvae of Drosophila melanogaster

Drosophila melanogaster larvae are model systems for studies of development, synaptic transmission, sensory physiology, locomotion, drug discovery, and learning and memory. A detailed behavioral understanding of larvae can advance all these fields of neuroscience. Automated tracking can expand fine-...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2010-12, Vol.5 (12), p.e15259-e15259
Main Authors: Khurana, Sukant, Li, Wen-Ke, Atkinson, Nigel S
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Animals
Automation
Behavior
Behavior, Animal
Biology
Darkening
Digital cameras
Drosophila
Drosophila melanogaster
Drug discovery
Engineering
Gene Expression Regulation, Developmental
Image contrast
Image enhancement
Image processing
Image Processing, Computer-Assisted
Insects
Larva - physiology
Larvae
Learning
Light
Locomotion
Memory
Methods
Movement
Nervous system
Neurobiology
Neurosciences
Normal Distribution
Paradigms
Pattern Recognition, Automated - methods
Physiological aspects
Polyamines
Static objects
Subtraction
Synaptic transmission
Synaptogenesis
Tracking
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Drosophila melanogaster larvae are model systems for studies of development, synaptic transmission, sensory physiology, locomotion, drug discovery, and learning and memory. A detailed behavioral understanding of larvae can advance all these fields of neuroscience. Automated tracking can expand fine-grained behavioral analysis, yet its full potential remains to be implemented for the larvae. All published methods are unable to track the larvae near high contrast objects, including the petri-dish edges encountered in many behavioral paradigms. To alleviate these issues, we enhanced the larval contrast to obtain complete tracks. Our method employed a dual approach of optical-contrast boosting and post-hoc image processing for contrast enhancement. We reared larvae on black food media to enhance their optical contrast through darkening of their digestive tracts. For image processing we performed Frame Averaging followed by Subtraction then Thresholding (FAST). This algorithm can remove all static objects from the movie, including petri-dish edges prior to processing by the image-tracking module. This dual approach for contrast enhancement also succeeded in overcoming fluctuations in illumination caused by the alternating current power source. Our tracking method yields complete tracks, including at the edges of the behavioral arena and is computationally fast, hence suitable for high-throughput fine-grained behavioral measurements.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0015259