[CCoE Notice] Research Seminar: ECE Department Chair Candidate Dr. Badri Roysam, Wed. May 12 at 9:30 a.m.

[Lewis, Lindsay R]

Research Seminar

UH Cullen College of Engineering

 

Wednesday, May 12, 2010

9:30 a.m.

Room W122 Engineering Building 2

 

Dr. Badri Roysam

Professor, Department of Electrical, Computer and Systems Engineering

Associate Director, NSF Center for Subsurface Sensing & Imaging Systems (CenSSIS ERC)

Co‐Director, Rensselaer Center for Open Source Software

Rensselaer Polytechnic Institute

 

Quantifying Structures and Phenomena in Complex

and Dynamic Biological Microenvironments

from 4D/5D Optical Microscopy Images

 

Abstract

Many tissue microenvironments that play critical roles in health and disease are complex and dynamic, e.g.,

tumors, stem‐cell niches, brain tissue surrounding neuroprosthetic devices, retinal tissue, cancer stem‐cell

niches, glands, and immune system tissues. Progress in these areas is much too slow compared to the need.

Knowledge is pieced together from large numbers of experiments, each of which yields a small amount of

information. Much of the knowledge still remains qualitative. There is a compelling need to accelerate

progress towards a quantitative understanding. I will describe strategies based on multi‐dimensional optical

microscopy and computational image analysis.

 

Modern optical microscopy has grown into a multi‐dimensional imaging tool. It is now possible to record

dynamic processes in living specimens in their spatial context and temporal order, yielding information‐rich

5‐D images (3‐D space, time, spectra). The task of analyzing these images exceeds human ability. There is a

need for automated systems to map the tissue anatomy, quantify structural associations, identify critical

events, map event locations and timing, identify and quantify spatial and temporal dependencies, produce

meaningful summaries of multivariate measurement data, and compare 4‐D/5‐D datasets for testing

hypotheses, exploration, and systems modeling. Importantly, there is a need for “computational sensing”

methods capable of exceeding human ability.

 

In this talk, I will use examples from neuroscience, cancer histopathology, immunology, and retinal stem‐cell

biology to show the practicality of multi‐dimensional image analysis and computational sensing.

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