Hagai Kirshner

 


Current position: senior image processing algorithm developer at Samsung

Previous positions: senior image processing algorithm developer at Applied Materials; a researcher at the biomedical imaging group, EPFL.

Contact: hagai.kirshner @ epfl.ch (mind the gaps)

Date updated: December 2015


Research Interests:

sampling theory, stochastic processes, biomedical image processing, super-resolution microscopy


Publications:

1.    D. Sage, H. Kirshner, T. Pengo, N. Stuurman, J. Min, S. Manley, M. Unser, “Ongoing Quantitative Evaluation of Software Packages for Single-Molecule Localization Microscopy”, Nature Methods, vol. 12, June 2015

2.      J. Min, C. Vonesch, H. Kirshner, L. Carlini, N. Olivier, S. Holden, S. Manley, J.C. Ye and M. Unser, “FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data”, Scientific Reports, 4:4577, April 2014.

3.      M. Unser, P. Tafti, A. Amini and H. Kirshner, “A unified formulation of Gaussian vs. sparse stochastic processes - Part II: Discrete-domain theory”, to appear in IEEE Trans. Information Theory.

4.      H. Kirshner, M. Unser and J.P. Ward, “On the unique identification of continuous-time autoregressive models from sampled data, IEEE Trans. Signal Processing, vol.62, no.6, pp.1361,1376, March15, 2014.

5.      H. Kirshner, A. Bourquard, J.P. Ward, M. Porat and M. Unser, “Adaptive image resizing based on continuous-domain stochastic modeling, IEEE Trans. Image Processing, vol.23, no.1, pp.413,423, Jan. 2014.

6.      H. Kirshner, F. Aguet, D. Sage, M. Unser, “3-D PSF Fitting for Fluorescence Microscopy: Implementation and localization Applications”, accepted to the Journal of Microscopy, September 2012

7.      J.P. Ward, H. Kirshner, M. Unser, "Is Uniqueness Lost for Under-Sampled Continuous-Time Auto-Regressive Processes?", IEEE Signal Processing Letters, vol. 19, no.4, pp. 183-186, April 2012

8.      H. Kirshner, S. Maggio and M. Unser, "A Sampling Theory Approach for Continuous ARMA Identification", IEEE Transactions on Signal Processing, vol. 59, no. 10, pp. 4620-4634 October 2011

9.      H. Kirshner and M. Porat, “On the role of exponential splines in image interpolation”, IEEE Trans. Image Processing, vol. 18, no.10, pp. 2198–2208, October 2009

10.  T. G. Dvorkind, H. Kirshner, Y.C. Eldar and M. Porat, "Minimax approximation of representation coefficients from generalized samples", IEEE Trans. Signal Processing, vol. 55, no. 9, pp. 4430-4443, September 2007

11.  H. Kirshner and M. Porat, “On the approximation of L2 inner products from sampled data”, IEEE Trans. Signal Processing, vol. 55, no. 5, pp. 2136-2144, May 2007


Book chapters:

1.      H. Kirshner and M. Porat, “From analog information to digital databases - Does it keep everything intact?”, Information Systems Development: Advances in Theory, Practice, and Education, pp. 377-388,2005, Springer US


Algorithms:

Symmetric Exponential B-spline: A Matlab package for calculating symmetric exponential splines -- Sobolev reproducing kernels, B-splines and interpolation functions

Continuous-Time ARMA Identification: A Matlab package for estimating Gaussian continuous-time ARMA parameters from sampled data. No sampling interval constraints are imposed

PSF Generator: An ImageJ plugin for generating and visualizing various 3D models of a microscope point spread function (PSF)

Localization Microscopy: A set of ImageJ plugins for fitting a PSF.

PALM data: Benchmarking photo-activated localization microscopy (PALM) data

 


Conferences proceedings:

1.      Best Paper Award: J. Min, C. Vonesch, N. Olivier, H. Kirshner, S. Manley, J. C. Ye and M. Unser, “Continuous-spatial localization using sparsity constraints for high-density superresolution microscopy”, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI'13), pp. 181-184, April 2013.

2.      H. Kirshner, C. Vonesch and M. Unser, “Can localization microscopy benefit from approximation theory?”, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI'13), pp. 584-587, April 2013.

3.      H. Kirshner, A. Bourquard, J. P. Ward and M. Unser, “Linear interpolation of biomedical images using adaptive exponential kernel”, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI'13), pp. 926-929, April 2013.

4.      H. Kirshner, J.P. Ward and M. Unser, “Identification of rational transfer functions from sampled data”, International Conference on Sampling Theory and Applications (SampTA’13), pp. 341-343, July 2013.

5.      H. Kirshner, T. Pengo, N. Olivier, D. Sage, S. Manley, M. Unser, “A PSF-based approach to biplane calibration in 3D super-resolution microscopy,”Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI’12), pp. 1232-1235, May 2012.

6.      H. Kirshner, T. Pengo, N. Olivier, D. Sage, S. Manley and M. Unser, “Bi-plane calibration in super-resolution microscopy”, The 12th Conference on Methods and Applications of Fluorescence: Spectroscopy, Imaging and Probes (MAF’12), September 2011.

7.      H. Kirshner, D. Sage and M. Unser, “3D PSF models for fluorescence microscopy in ImageJ”, The 12th Conference on Methods and Applications of Fluorescence: Spectroscopy, Imaging and Probes (MAF’12), September 2011.

8.      A. Bourquard, H. Kirshner and M. Unser, ”’Resolution-invariant separable ARMA modeling of images”, The IEEE International conference on Image Processing (ICIP’11), pp. 1873-1876, September 2011.

9.      H. Kirshner, S. Maggio and M. Unser, “Maximum-likelihood identification of sampled Gaussian processes”, International Workshop on Sampling Theory and Applications (SampTA’11), 4 pages, May 2011.

10.  H. Kirshner, M. Poart and M. Unser, “A stochastic minimum-norm approach to image and texture interpolation”, European Signal Processing Conference (EUSIPCO’10), pp. 1004-1008, August 2010.

11.  S. Maggio, H. Kirshner and M. Unser, “Continuous-time AR model identification: does sampling rate really matter?”, European Signal Processing Conference (EUSIPCO’10), pp. 1469-1473, August 2010.

12.  H. Kirshner and M. Poart, “A stochastic model-based approach to image and texture interpolation”, IEEE International conference on Image Processing (ICIP ‘09), pp. 341-344, November 2009.

13.  H. Kirshner and M. Porat, “On spectral estimation and Fourier transform approximation from sampled data”, European Signal Processing Conference (EUSIPCO’09), pp. 2618-2622, August 2009.

14.  H. Kirshner and M. Porat, “Are polynomial models optimal for image interpolation?”, European Signal Processing Conference (EUSIPCO’08), 5 pages, August 2008.

15.  H, Kirshner and M. Porat, “On interpolation of differentially structured images”, European Signal Processing Conference (EUSIPCO’07), pp. 1789-1793, September 2007.

16.  H, Kirshner and M. Porat, “On derivative approximation from sampled data”, International Conference on Sampling Theory and Applications (SampTA’07), June 2007.

17.  H. Kirshner, T. Dvorkind, Y. Eldar and M. Porat, “On signal representation from generalized samples: minmax approximation with Constraints”, European Signal Processing Conference (EUSIPCO’06), September 2006.

18.  T. G. Dvorkind, H. Kirshner, Y. C. Eldar and M. Porat, “Approximating representation coefficients from non-ideal samples”, International Conference on Acoustics, Speech and Signal Processing (ICASSP’06), May 2006.

19.  H. Kirshner and M. Porat, “On optimal representation of digitized signals”, European Signal Processing Conference (EUSIPCO’05), September 2005.

20.  H. Kirshner and M. Porat, “A new approach to sampling finite energy functions and Sobolev signal representation”, International Conference on Sampling Theory and Applications (SampTA’05), July 2005.