1. Center for Research Computing Data
  2. Prospective Users
  3. Supported Research
  4. High-Throughput Analysis of High-Content Biological Images

High-Throughput Analysis of High-Content Biological Images

Principal Investigator: Jie Zhou, Ph.D., Department of Computer Science.

Image Learning and Analytics Lab at department of computer science works on automatic analysis, quantification and annotation of high dimensional images using machine learning and pattern recognition approaches. Ongoing projects include quantification of dendritic and synaptic metrics using light microscopic neuronal images, analysis of dynamic neuronal activity and behavior, as well as the development of high-throughput platform for learning-based biological image annotation and model selection.

Automatic Dendritic Metric Analysis

 

Distributed learning model selection of BIOCAT
(BIOimage Classification and Annotation Tool)

Automatic Dendritic Metric Analysis. The diagram is the workflow of automatic analysis of dendritic metrics using light microscopic images. The raw microscopic image was contributed by Huganir lab at Johns Hopkins University..
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