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

	Jie Zhou, Ph.D Professor Department of Computer Science Northern Illinois University
	email: jzhou@niu.edu web: http://faculty.cs.niu.edu/~zhou/index.html