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Members of the Image Learning and Analytics Lab enjoying an end-of-summer retreat in August, 2015.

Overview

The Image Learning and Analytics Lab studies learning-based algorithms and tools to analyze, recognize, and quantify images. One major focus of the lab is automated analysis of high-dimensional high-throughput biological images such as the algorithms for analyzing cellular and subcellular objects in microscopic neuronal images and recordings. It is also our mission to provide open, effective, and user-friendly tools for the scientific community in order to meet the ever-increasing demand of complex and high content image data.

 

News

  • Congrats to Randall Suvanto, Alex Ekstrom and other co-authors for the NIH 2016 paper on automatic neuron counting!
  • Congrats to Jon Sanders’ successful defense! (Jun 2016)
  • Road trip! ILAAL lab travels to Kalamazoo, MI, for a joint research meeting/retreat with collaborator Ye lab of University of Michigan. (Apr 2016) photo
  • The paper on Automatic Dendrite Length Quantification for High Throughput Screening of Mature Neurons has been accepted by Nueroinformatics!  Congratulations to Tim, Venkat and all of the co-authors!!  (Spring 2015)
  • We would like to welcome Joseph Steinke to the team! (Fall 2014)
  • Venkat Pasupuleti is traveling to Long Beach, CA, to present his research results! (Sept 2014)
  • Congratulations to Tim Smafield on his successful defense! (June 2014)
  • A collaborative paper on Drosophila topography has been accepted by Current Biology.  Our team is responsible for fine-scale 3D quantification.  (Spring 2014)
  • We are happy to welcome Shawn Horvatic to the team! (Spring 2014)
  • Road Trip! The team is travelling to the University of Michigan to observe imaging experiments. (Dec 2013)
  • Dr. Jie Zhou attends ACM BCB 2013 presenting “Performance Model Selection for Learning-Based Biological Image Analysis on a Cluster.”
  • Venkat Pasupuleti has joined the team (supported by NIH).
  • The paper “BIOCAT: A Pattern Recognition Platform for Customizable Biological Image Classification and Annotation” has been accepted by BMC Bioinformatics.
  • Dr. Jie Zhou has been awarded the NIH/NIMH R15 MH099569 as the principal investigator for Automatic 3D Quantification of Synapse Distribution in Complex Dendritic Arbor.
  • Timothy Smafield has joined the team (supported by Great Journeys Assistantship).
  • Eric Swatkowski joins the team (supported by LA&S URAP).
  • Jonathan Sanders has joined the team (supported by LA&S URAP and the Office of Student Engagement of Experiential Learning).

 

Contact

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Jie Zhou, Ph.D

Associate Professor
Department of Computer Science
Northern Illinois University

 

email: jzhou@niu.edu
web: http://faculty.cs.niu.edu/~zhou/index.html