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[Seminar] Using Deep Neural Networks to Advance Concussion Research

Wednesday, October 21, 2020

11:00 am - 12:00 pm


MS Teams Meeting


We are developing a next-generation brain histology platform that is based on imaging and analyzing whole brain sections using 10 – 100 molecular markers at a time, sufficient to analyze all the major brain cell types and their functional states over extended regions. Analyzing 100-plex whole-brain-slice mosaics is challenging due to their complexity, variability, and sheer size (~terabytes). While deep neural networks offer unprecedented potential for automated image analysis, they are also accompanied by new and unfamiliar challenges. This talk will describe our progress, challenges (both met and unmet), and emerging strategies for successfully integrating signal reconstruction, deep neural network based cell detection and phenotyping, and high-dimensional data analysis approaches to generate reliable quantitative readouts of cellular alterations at multiple scales ranging from individual cells to multi-cellular units, large cellular ensembles (e.g., cortical layers), and atlas-mapped brain regions for  comparative analysis.

About the Speaker

Badri Roysam (Fellow IEEE & AIMBE) is the Hugh Roy and Lillie Cranz Cullen University Professor, and Chairman of the Electrical and Computer Engineering Department at the University of Houston (2010 – present). From 1989 to 2010, he was a Professor at Rensselaer Polytechnic Institute in Troy, New York, USA, where he directed the Rensselaer unit of the NSF Engineering Research (ERC) Center for Subsurface Sensing and Imaging Systems (CenSSIS ERC), and co-directed the Rensselaer Center for Open Source Software (RCOS). He received the Doctor of Science degree from Washington University, St. Louis, USA, in 1989. Earlier, he received his Bachelor’s degree from the Indian Institute of Technology, Madras, India in 1984.

Badri’s research is on the applications of multi-dimensional image processing, machine learning, big-data, bioinformatics, and high-performance computing to problems in fundamental and clinical biomedicine. He collaborates with a diverse group of biologists, physicians, and imaging researchers. His work is inspired by diverse applications including cancer immunotherapy, traumatic brain injury, retinal diseases, neural implants, learning and memory impairments, binge alcohol, tumor mapping, stem-cell biology, stroke research, and neurodegenerative diseases.

October 21 Seminar
Online via MS Teams