[CSBi-events] Upcoming Seminar

[csbi-events@mit.edu]

Dear CSBi Members, FYI

Machine Visual Screening

MIT Machine Vision Seminar 2005/2006
Speaker: Arman M. Garakani
Speaker Affiliation: Reify corporation
Host: Berthold K.P. Horn
Host Affiliation: MIT CSAIL
Date: 12-14-2005
Time: 2:45 PM - 3:45 PM
Location: Patil/Kiva Seminar Room (32-G449)

Biologists have always relied on viewing biological systems as they 
evolve in space and time. Most of us -- even non biologists -- can 
recognize a dynamic biological event such as a beating heart, a 
dividing, migrating or spreading cell. How is it that we can "label" 
these events without imposing a model? One explanation may be that 
the entire event projects information about its dynamic nature. 
Oscillating events may be recognized by their repetitive 
presentation. Similarly, spreading events may be recognized by their 
continuously enlarging presentation. A visual event is captured 
digitally into a snapshot sequence. Measuring similarity between any 
snapshot and all other snapshots is particularly hard. The 
transformation between two snapshots has to describe geometric 
changes of deformable objects, illumination changes, intensity 
changes, and so on. If there were no mutual information in a visual 
event, it would be impossible to measure similarity among its 
snapshots. In our experience, most biological events, when captured 
appropriately, are consistent and contain measurable mutual 
information.

During this talk, I will describe our work at Reify corporation. We 
have developed a set of technologies to extract and measure 
biological events enabling "machine visual screening" of biology. We 
measure the mutual information inherent in an image sequence digital 
capture of a biological event. We call this measurement the Aggregate 
Change Index (ACI). ACI can in many cases be directly used as a 
functional readout. In many other cases it can form a robust basis of 
other functional readouts. Whether measuring mechanical work of motor 
proteins or heart function of a young zebra fish for a phenotypic 
compound profiling, ACI and other mutual information based 
measurements present the possibility of unbiased, robust, and 
repeatable functional readouts of the marvellously consistent set of 
systems that is Biology.

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Bio:
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Arman Garakani is co-founder and chief technology officer at Reify 
corp. He was previously at Cognex corp where he played an 
instrumental part in vision software and algorithm development. 
Arman's graduate research was in computational methods in Fluid 
Mechanics at Alden Laboratory; one of the oldest continuously 
operating hydraulic laboratories in the world. Arman holds a BS in 
Mechanical Engineering from Worcester Polytechnic Institute and an MS 
in Management of Technology from MIT.

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Linda K. Earle, Outreach Coordinator
Computational and Systems Biology (CSBi)
Phone: (617) 324-0074
Fax: (617) 324-0081

Massachusetts Institute of Technology
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