HCA-Vision

HCA-Vision automates quantitative image analysis of neuronal cultures to measure neurite morphology and support high-throughput identification of neuroactive compounds for drug discovery.


Key Features:

  • Automated Neurite Analysis: Quantifies neurite metrics including total neurite length and number of branching points and extracts detailed neuron morphology features.
  • Discrimination of Subtle Morphological Changes: Detects subtle differences in complex neurite arborization patterns even when neurons and processes are densely packed.
  • Selective Screening: Enables screening for compounds that induce specific neurite outgrowth behaviors.
  • Cell Type Filtering and Separation: Filters and isolates neurons from other brain cell types in mixed cell populations to restrict analysis to neuronal cells.
  • Batch Processing and Data Management: Supports batch processing at primary screening rates and stores results in a built-in database with an ad hoc query builder.
  • Reproducible Measurement and Reporting: Provides rapid and reproducible measurement and reporting of cellular features relevant to drug discovery.

Scientific Applications:

  • Drug Discovery: Identification and screening of neuroactive compounds through quantitative analysis of neuronal cultures.
  • Neurite Outgrowth and Neuronal Health Assessment: Assessment of compound effects on neurite outgrowth and overall neuronal health via morphological analysis.

Methodology:

Employs a suite of automated image-analysis tools to quantify neurite morphology and neurite arborization metrics, performs batch processing at primary screening rates, and stores results in a built-in database with ad hoc query capability.

Topics

Details

Tool Type:
desktop application
Operating Systems:
Windows
Added:
12/18/2017
Last Updated:
12/29/2018

Operations

Publications

Wang D, Lagerstrom R, Sun C, Bishof L, Valotton P, Götte M. HCA-Vision: Automated Neurite Outgrowth Analysis. SLAS Discovery. 2010;15(9):1165-1170. doi:10.1177/1087057110382894. PMID:20855562.

Documentation

Links