Visual Resume

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Images acknowledgement: INRIA, INRA, Institut Pasteur, UHA, Wikimedia commons, and others
Images are used here for illustration only and is not for commercial interests.
Research results are from my own work.
Email: praveen.pankaj@gmail.com

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  • 1. Hello!My name is Praveen Pankajakshan, ... 1
  • 2. ... and this is my Y 2
  • 3. Biography Cloud 3 Powered by: tagul.com
  • 4. Academics 4
  • 5. UNDERGRADUATEElectrical Engineering IIT ROORKEE INDIA 5
  • 6. GRADUATE SCHOOLElectrical & Computer Engineering Texas A&M University College Station USA 6
  • 7. PHD SUMMA CUM LAUDE Computer Science INRIA Sophia Antipolis &University of Nice-Sophia Antipolis 7
  • 8. he sisCORDI-s Fellowship D T port Ph Re J ury 8
  • 9. What I do now ...Post Doctoral Fellow 9
  • 10. PhD+Postdoc research cloud 10 Powered by: academia.edu
  • 11. Where I live ... x 11
  • 12. Expertise: Computational Nanoscopy 12
  • 13. For me research is like fine cuisine ...Objectivity Creativity Tools 13
  • 14. My Experiencesare drawn from 14
  • 15. My diverse research cloud... 15 Powered by: tagul.com
  • 16. Wh at Ib eli eve in . ..16 Co lla Re bor sea ati rch ve
  • 17. Upcoming book chapter* 2012 + 12 peer reviewed conference and journal articles + many invited talks *P. Pankajakshan, et al. Deconvolution and Denoising for Confocal Microscopy. In F.Cazals and P. Kornprobst, editor, Modeling in Computational Biology and17 Biomedicine, ch.4, Springer, In Publication, 2012.
  • 18. Biography listed inWho’s who in the World 2010, 2011, 2012 18
  • 19. ’10 LS YR er Aw ard ostPSF model for fluorescence MACROscopy imaging ic P Praveen Pankajakshan1, Alain Dieterlen2, Gilbert Engler3, Zvi Kam4, ubl Laure Blanc-Féraud5, Josiane Zerubia5 & Jean-Christophe Olivo-Marin1 1 Quantitative Image Analysis Unit, Pasteur Institute, France, 2 P Laboratoire MIPS-LAB.EL, Universite de Haute-Alsace, France. 3 IBSV Unit, INRA, France, 4 Molecular Cell Biology, Weizmann Institute of Science, Israel. 5 Ariana joint research group, INRIA/CNRS/UNS, France. INTRODUCTION OBJECTIVE To model the point-spread function (PSF) of a MACROscope operating with field Fluorescent MACROscope is useful for observing large samples (of the order of a few aberrations due to optical vignetting. centimeters) and has the following advantages: • large object fields, • large working distances, and • parallax-free imaging. Imaging field aberrations using point source Telecentric lens assembly MACROscope lens assembly Why A PSF MODEL IS IMPORTANT? ZZ XY Observed PSF Unknown XY Point-spread function (PSF)-> Image of ideal point source (4 m). Total magnification 6.25x. volume synthetic object Bio ’10 d METHODOLOGY Stokseth’s PSF model Excitation PSF Emission PSF Lens displacement y-direction M iFo Aw ar ter n Pupil function for a MICROscope { Pos iko { Pupil function for a MACROscope Lens displacement est x-direction Results B N SIMULATE PUPIL OPTIC AL VIGNETTING AND from PSF CONCLUSIONS Z Cat’s eye 1. MACROscope PSF varies as a function of the lateral position. 2. Vignetting was observed for small zooms (large FOV). X X effect X XY 3. This initial PSF model will be enhanced with newer X X acquisitions on different systems. Z XY ACKNOWLEDGEMENTS The first author wish to thank ANR DIAMOND for funding the Simulated PSF postdoctoral research fellowship. The authors also are grateful to Z Dr. Philippe Herbomel from the Institute Pasteur, France and Dr. Z Didier Hentsch from IGBMC, France for the images and the XY XY discussions. ed bead www-syscom.univ-mlr.fr/ANRDIAMOND/ Experimentally obtain l images for different latera Measured bead image www.bioimageanalysis.org position in the field {praveen,jcolivo}@pasteur.fr alain.dieterlen@uha.fr 19
  • 20. If you like my work and have a X 20
  • 21. Contact me ... praveen.pankaj@gmail.com Praveen Pankajakshan +33 (0) 628358064 15 rue de l’ésperance www.bioimageanalysis.org/~praveen 75013 Paris www.linkedin.com/in/praveenpankajpasteur.academia.edu/PraveenPankajakshan praveenpankaj France 21
  • 22. Research Highlight 22
  • 23. ed e rv O bs v ed v ol on DecDeconvolution as virtual inverse lens 23
  • 24. Application: Fluorescence MicroscopyWidefield (WFM) Confocal (CLSM)            M. Minsky. Memoir on inventing the confocal scanning microscope. Scanning, 10:128–138, 1988. 24
  • 25. Volume on Volume on WFM CLSMBackground Better but ...Fluorescence! Low photon count! Convallaria rhizome (Courtesy: INRA) 25
  • 26. WFM CLSMHigh frequencies lost!Frequency Spectra for Convallaria sample 26
  • 27. λ d = 0.61 NA Minimum Radial Resolution ~ 200nm... and yet, there is the Diffraction Barrier 27
  • 28. I minimize trade-offs in microscopy ... SNR Acquisition but how?Speed Resolution 28
  • 29. ... by bridging optics and image ProcessingSample Microscope 3-D Image • Improvement in resolution. • Noise reduction Diffraction limit Aberrations Noise ? ...but requires point- spread function (PSF) Inverse h(x). approach ? 29
  • 30. Point-Spread Function (PSF) h(x) Separate PSF estimation Fluorescent Identify Point BlindPSF Model Beads Sources estimation Complexity Accuracy 30
  • 31. PSF ModelingClear ApodizedPupil Pupil Defocus Fourier Amplitude Pupil Transform PSF Function Microscope Squared PSF Magnitude P. A. Stokseth, “Properties of a defocused optical system,” J. Opt. Soc. Am. A, vol. 59, pp. 1314–1321, Oct. 1969. P. Pankajakshan et al. “Blind Deconvolution for Confocal Laser Scanning Microscopy,” PhD Thesis., 31 Dec. 2009.
  • 32. WFM CLSM −6 −14 −8 −16 −18 −10 −20z −12 z −22 x xAxial MIP PSF for a 40x/1.4 oil immersion lens. P. Pankajakshan, et al. Deconvolution and Denoising for Confocal Microscopy. In F.Cazals and P. Kornprobst, editor, Modeling in Computational Biology and 32 Biomedicine, ch.4, Springer, In Publication, 2012.
  • 33. Determining PSF- Beads as ‘guide stars’ Image Plane on ds ce! an ien Object Plane H r pez xy ex Imaging fluorescent beads 33
  • 34. Blind/Myopic Deconvolution Alternate PSF & Object estimation PSF constraints Observation Object constraints OldObject Update Update New PSF New PSF Object Object Old PSF T. J. Holmes. Blind deconvolution of quantum-limitedP. Pankajakshan et al. “Blind incoherent imagery: maximum-likelihood approach. J.Deconvolution for Confocal Laser Opt. Soc. Am. A, 9:1052–1061, July 1992.Scanning Microscopy,” PhD Thesis., Dec.2009. B. Zhang et al. “A study of Gaussian approximation of fluorescence Microscopy PSF models,” SPIE conf., San 34 Jose, Jan. 2006.
  • 35. Convallaria cell from Parenchyma tissue Observed RestoredFocussed on the cytoplasmic threads of a cell P. Pankajakshan, et al. Deconvolution and Denoising for Confocal Microscopy. In F.Cazals and P. Kornprobst, editor, Modeling in Computational Biology and 35 Biomedicine, ch.4, Springer, In Publication, 2012.
  • 36. Blind Deconvolution of Fluorescent Shell Specification: Diameter 15 microns Thickness specified: 500-700 nm 2x increase in resolution! Observed ThinBlinDe: 40 iter. P. Pankajakshan et al. “Blind Deconvolution for Confocal LaserFWHM: 930nm FWHM: 535.58nm Scanning Microscopy,” PhD Thesis., Dec. 2009. 36
  • 37. Non-Blind vs BlindCommercial software Proposed ThinBlinDe(Using PSF model) 37
  • 38. Convallaria cell from Parenchyma tissue Courtesy: INRA Commercial ThinBlinDe:Observed Non-blind Blind restoration restoration P. Pankajakshan et al. “Blind Deconvolution for Confocal Laser Scanning Microscopy,” PhD Thesis., Dec. 2009. 38
  • 39. Thank you 39
  • 40. Contact me ... praveen.pankaj@gmail.com Praveen Pankajakshan +33 (0) 628358064 15 rue de l’ésperance www.bioimageanalysis.org/~praveen 75013 Paris www.linkedin.com/in/praveenpankajpasteur.academia.edu/PraveenPankajakshan praveenpankaj France 40