[BIC-announce] Fwd: [reparti-cim] Tuesday Sep. 18/2:30pm (MC437) Jon Sporring, visiting Prof.

[Kaleem Siddiqi]

This talk by Jon Sporring, our sabbatical visitor from the University of Copenhagen, may be of interest to many of you.

Best,
Kaleem

Begin forwarded message:

> From: Herve Lombaert <lombaert at cim.mcgill.ca>
> Date: September 13, 2012 9:17:26 PM EDT
> To: <perception-list at cim.mcgill.ca>, <reparti at cim.mcgill.ca>
> Subject: [reparti-cim] Tuesday Sep. 18/2:30pm (MC437) Jon Sporring, visiting Prof.
> 
> Greetings to all,
> 
> The CIM-REPARTI Perception Seminar for this Tuesday (Sep. 18, 2:30pm)
> will feature Jon Sporring, visiting Professor working with Kaleem Siddiqi
> 
> Everybody is welcome
> 
> * Tuesday Sept. 18th, in MC437 at 2:30pm
> 
> http://cim.mcgill.ca/~lombaert/perception-list/
> 
> ************************************************************************
> Title:  Locally Orderless Registration
> 
> Abstract:
> 
> Image registration is an important tool for medical image analysis and
> is used to bring images into the same reference frame by warping the
> coordinate field of one image, such that some similarity meeasure is
> minimized. We study similarity in image registration in the context of
> Locally Orderless Images (LOI), which is the natural way to study
> density estimates and reveals the 3 fundamental scales: the measurement
> scale, the intensity scale, and the integration scale.
> 
> This paper has three main contributions: Firstly, we rephrase a large
> set of popular similarity measures into a common framework, which we
> refer to as Locally Orderless Registration, and which makes full use of
> the features of local histograms. Secondly, we extend the theoretical
> understanding of the local histograms. Thirdly, we use our framework to
> compare two state- of-the-art intensity density estimators for image
> registration: The Parzen Window (PW) and the Generalized Partial Volume
> (GPV), and we demonstrate their differences on a popular similarity
> measure, Normalized Mutual Information (NMI).
> 
> We conclude, that complicated similarity measures such as NMI may be
> evaluated almost as fast as simple measures such as Sum of Squared
> Distances (SSD) regardless of the choice of PW and GPV. Also, GPV is an
> asymmetric measure, and PW is our preferred choice.
> 
> ---
> Jon Sporring received his Master and Ph.d. degrees from the
> Department of Computer Science, University of Copenhagen, Denmark in
> 1995 and 1998, respectively. He completed part of his doctoral studies
> in the U.S., at the IBM Research Center at Almaden, California, USA. On
> completing his Ph.D., he was a visiting researcher at the Computer
> Vision and Robotics Lab at the Foundation for Research & Technology -
> Hellas, Greece, and as an Assistant Research Professor at 3D-Lab, School
> of Dentistry, University of Copenhagen. Since 2003 he has been employed
> as Associate Professor at the Department of Computer Science, University
> of Copenhagen. From 2007-2012 he served as Vice-Chair for Research at
> Department of Computer Science, and from 2008-2009 he was a part-time
> Senior Researcher at Nordic Bioscience. Currently, he is a visiting
> professor at the School of Computer Science, McGill University in
> Montreal, Canada. His primary research fields are Computer Science,
> particularly image processing, computer graphics, information theory,
> and pattern recognition.
> ************************************************************************
> 

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