DeTerm

DeTerm detects and quantifies dendritic branch terminals in neuronal images using an artificial neural network to provide positional and label data for analysis of dendritic arborization.

Key Features:

• Automated Recognition: Uses an artificial neural network to identify and label dendritic branch terminals in neuronal image data.
• High Precision: Distinguishes dendritic branch terminals from surrounding tissue signals, including in challenging imaging conditions such as whole-mount live larvae.
• Positional Data Output: Outputs detailed positional data for each detected terminal to enable spatial mapping of dendrites.
• Versatility Across Species: Developed with Drosophila class IV dendritic arborization (da) neurons and demonstrated applicability to mouse cerebellar Purkinje cells.

Scientific Applications:

• Dendrite morphogenesis quantification: Quantifies dendritic branch terminal number and spatial distribution to assess dendritic arbor complexity.
• Developmental neurobiology phenotyping: Provides a terminal-level phenotypic readout useful during neurogenesis and other developmental processes.
• Molecular mechanism studies: Enables analysis of molecular mechanisms underlying dendritic arborization by supplying reproducible terminal counts and positions.

Methodology:

Input consists of a neuronal image file with region-of-interest information; an artificial neural network processes the image to recognize and quantify dendritic branch terminals and produces labeled terminals with positional data as output.