NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery

Background: Automatic quantification of neuronal morphology from images of fluorescence microscopy plays an increasingly important role in high-content screenings. However, there exist very few freeware tools and methods which provide automatic neuronal morphology quantification for pharmacological discovery. Results: This study proposes an effective quantification method, called NeurphologyJ, capable of automatically quantifying neuronal morphologies such as soma number and size, neurite length, and neurite branching complexity (which is highly related to the numbers of attachment points and ending points). NeurphologyJ is implemented as a plugin to ImageJ, an open-source Java-based image processing and analysis platform. The high performance of NeurphologyJ arises mainly from an elegant image enhancement method. Consequently, some morphology operations of image processing can be efficiently applied. We evaluated NeurphologyJ by comparing it with both the computer-aided manual tracin...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Shinn-Ying Ho, Chih-Yuan Chao, Hui-Ling Huang, Tzai-Wen Chiu, Phasit Charoenkwan, Eric Hwang
• Keywords: Biometrics, BMCBI 2011, Coefficient Correlation, Neuronal Morphology, Quantification Method