Eilat Vardi-Gonen


     
 

Name:

Eilat Vardi-Gonen

Position:

Ph.D. student

 

Computer Science Department

 

The Graduate Center, CUNY

Address:

The Graduate Center, CUNY

 

Computer Science Department, Room 4319

 

365 5th Ave.

 

New York, NY 10016

 

USA

E-mail:


Research Interests:

     While working with Dr. Gabor T. Herman at the Medical Image Processing Group, University of Pennsylvania, during the summer of 1998, I implemented an algorithm which uses the Metropolis Algorithm with Gibbs priors to stochastically reconstruct two-dimensional binary images from only three projection directions, see [2], [3].  In 2000, Dr. Herman, Dr. T. Yung Kong and I worked on speeding up that stochastic reconstruction algorithm for cardiac cross-section images, see [4].  In 2001, Dr. Gabor T. Herman and I worked on a stochastic segmentation algorithm using the Metropolis Algorithm with Gibbs priors.  The intended application of this work was the segmentation of trabecular bone from two-dimensional magnetic resonance (M.R.) images taken in-vivo. Such images are relatively low resolution, see [5].  During that time, I did some work with Dr. Felix Wehrli to correct in-vivo M.R. images inhomogeneities, see [6]. 

     I am currently in the Computer Science Department at The Graduate Center, CUNY.  I have started working on the "real-time" interpretation of noisy signals.  The application we are considering is that of improving speech signals for hearing aids.  Following is a brief description of the “real-time” steps we perform in our proposed methodology.  First we transform the input noisy signal to a gray image using the Short-Time Fourier Transform, STFT, a commonly used transform in many signal processing areas. Next we create a corresponding binary image using the Metropolis Algorithm with an annealing schedule where Gibbs priors are used to describe clean speech signals.  We have compared different methods for estimating the prior from a training set of clean speech images.  Using both the noisy gray image and the binary image, we estimate a clean gray image.  One simple way of doing this is by using the binary image as a mask for the noisy gray image. Alternatively a "fuzzy" version of the binary image can be used as a mask.   Finally, we estimate the clean speech signal from the clean gray image by performing the inverse signal to image transform.  Preliminary work and results appeared in [7], [8] and [9].
 

Principal Investigator on Grants:

·                    Column by Column Image-Signal Interpretation, National Library of Medicine, National Institutes of Health, 1F37LM008611-01A1, 2005-2007.

 

Education:
 

Dates Attended 

Degree

Department

University

City

State

Country

9/1994-5/1995

 

 

Bryn Mawr College

Bryn Mawr

PA

USA

10/1995-2/1999

B.A.

Department of Mathematics

Technion - Israel Institute of Technology

Haifa

 

Israel

1/2000-8/2000 

 

Bioengineering Department

University of Pennsylvania

Philadelphia

PA

USA

9/2000-12/2000

 

Department of Mathematics

Temple University

Philadelphia

PA

USA

1/2001-5/2002 

M.S.E.

Bioengineering Department

University of Pennsylvania

Philadelphia

PA

USA

5/2002-present 

Ph.D.

Computer Science Department

The Graduate Center, CUNY

New York

NY

USA

Experience:
 

Dates

Position

Group

University

City

State

Country

summer 1995

Participated in "Inquiry Based Science and Math in Middle School" Program

 

Haverford College

Haverford

PA

USA

summer 1995

Summer Student

 Laboratory of Retinal Microcircuitry

University of Pennsylvania

Philadelphia

PA

USA

8/1998-10/1998

Research Assistant

Medical Image Processing Group

University of Pennsylvania

Philadelphia

PA

USA

3/1999-7/1999

Teaching Assistant

Department of Mathematics

Technion - Israel Institute of Technology

Haifa

 

Israel

1/2000-8/2000

Research Assistant

Medical Image Processing Group

University of Pennsylvania

Philadelphia

PA

USA

9/2000-12/2000

Teaching Assistant

Department of Mathematics

Temple University

Philadelphia

PA

USA

1/2001-4/2002

Research Assistant

Laboratory for Structural NMR Imaging

University of Pennsylvania

Philadelphia

PA

USA

5/2002-present

Research Assistant

Discrete Imaging and Graphics Group

The Graduate Center, CUNY

New York

NY

USA

Conferences:

Publications:

[1]  H. von Gersdorff, E. Vardi, G. Matthews and P. Sterling.  Evidence that Vesicles on the Synaptic Ribbon of Retinal Bipolar Neurons Can be Rapidly Released. Neuron, volume 16(6):  pages 1221-1227, 1996.  Click here to see article online.

[2]  B. M. Carvalho, G. T. Herman, S. Matej, C. Salzberg and E. VardiBinary Tomography for Triplane Cardiography.  In A. Kuba, M. Samal and A. Todd-Pokropek, (eds.): Information Processing in Medical Imaging , volume 1613:  pages 29-41.  Springer-Verlag, Berlin, 1999.

[3]  S. Matej, A. Vardi, G. T. Herman and E. VardiBinary Tomography Using Gibbs Priors.  In G. T. Herman and A. Kuba (eds.):  Discrete Tomography: Foundations, Algorithms and Applications, pages 191-212.  Birkhauser, Boston, 1999.

[4]  E. Vardi, G. T. Herman, and T. Y. Kong.  Speeding Up Stochastic Reconstructions of Binary Images from Limited Projection Directions, Linear Algebra and its Applications: Special Issue on Discrete Tomography, volume 339: pages 75-89.  Elsevier, 2001. Click here to see article online.

[5]  E. Vardi and G. T. Herman. Stochastic Segmentation Using Gibbs Priors, Electronic Notes in Theoretical Computer Science, volume 46: pages 381-392.   Elsevier, 2001. Click here to see article online.

[6]  B. R. Gomberg, M. Fernandez-Seara, B. S. Zemel, P. K. Saha, E. Vardi, L. Loh, L. Hilaire, and F. W. WehrliMeasurement of Trabecular Bone Volume Fraction in the Proximal Femur.  Proceedings of the International Society for Magnetic Resonance in Medicine, 2002.

[7]  E. Vardi-Gonen and G. T. Herman.  Sequential vs. Simultaneous Stochastic Segmentation.  IEEE International Symposium on Biomedical Imaging, pages 1327-1330, 2004.  IEEE Catalog Number: 04EX821C, ISBN: 0-7803-8389-3.

[8]  E. Vardi-Gonen and G. T. Herman.  Sequential Binary Image Estimation.  IEEE 31st Annual Northeast Biomedical Conference, pages 127-128, 2005.  IEEE Catalog Number: 05CH3764C, ISBN: 0-7803-9106-3.

[9]  E. Vardi-Gonen and G. T. Herman.  Sequential Binary Image Estimation Algorithms.  IEEE Signal Processing Society - 12th Digital Signal Processing Workshop; 4th Signal Processing Education Workshop, pages 494-499, 2006.  IEEE Catalog Number: 06EX1488C, ISBN: 1-4244-0535-1.
 

Last Updated: 4/8/08