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Publications of J.C. Olivo-Marin
Result of the query in the list of publications :
3 Articles |
1 - Blind deconvoltion for thin layered confocal imaging.
P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. Applied Optics, 48(22): pages 4437-4448, August 2009.
Keywords : Blind Deconvolution, Confocal microscopy, Inverse Problems.
Copyright : Optical Society of America
@ARTICLE{ppankajakshan09b,
|
| author |
= |
{Pankajakshan, P. and Zhang, B. and Blanc-Féraud, L. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Blind deconvoltion for thin layered confocal imaging}, |
| year |
= |
{2009}, |
| month |
= |
{August}, |
| journal |
= |
{Applied Optics}, |
| volume |
= |
{48}, |
| number |
= |
{22}, |
| pages |
= |
{4437-4448}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/39/55/23/PDF/AppliedOpticsPaperTypesetting.pdf}, |
| keyword |
= |
{Blind Deconvolution, Confocal microscopy, Inverse Problems} |
| } |
Abstract :
We propose an alternate minimization algorithm for estimating the point-spread function (PSF) of a confocal laser scanning microscope and the specimen fluorescence distribution. A three-dimensional separable Gaussian model is used to restrict the PSF solution space and a constraint on the specimen is used so as to favor the stabilization and convergence of the algorithm. The results obtained from the simulation show that the PSF can be estimated to a high degree of accuracy, and those on real data show better deconvolution as compared to a full theoretical PSF model. |
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2 - Gaussian approximations of fluorescence microscope point-spread function models.
B. Zhang and J. Zerubia and J.C. Olivo-Marin. Applied Optics, 46(10): pages 1819-1829, April 2007.
Copyright : © 2007 Optical Society of America
@ARTICLE{jz_applied_photo,
|
| author |
= |
{Zhang, B. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
= |
{Gaussian approximations of fluorescence microscope point-spread function models}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| journal |
= |
{Applied Optics}, |
| volume |
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{46}, |
| number |
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{10}, |
| pages |
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{1819-1829}, |
| keyword |
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{} |
| } |
Abstract :
We comprehensively study the least-squares Gaussian approximations of the diffraction-limited 2D-3D paraxial-nonparaxial point-spread functions (PSFs) of the wide field fluorescence microscope (WFFM), the laser scanning confocal microscope (LSCM), and the disk scanning confocal microscope (DSCM). The PSFs are expressed using the Debye integral. Under an L∞ constraint imposing peak matching, optimal and near-optimal Gaussian parameters are derived for the PSFs. With an L1 constraint imposing energy conservation, an optimal Gaussian parameter is derived for the 2D paraxial WFFM PSF. We found that (1) the 2D approximations are all very accurate; (2) no accurate Gaussian approximation exists for 3D WFFM PSFs; and (3) with typical pinhole sizes, the 3D approximations are accurate for the DSCM and nearly perfect for the LSCM. All the Gaussian parameters derived in this study are in explicit analytical form, allowing their direct use in practical applications. |
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3 - Richardson-Lucy Algorithm with Total Variation Regularization for 3D Confocal Microscope Deconvolution.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and P. Roux and J.C. Olivo-Marin and J. Zerubia. Microscopy Research Technique, 69: pages 260-266, April 2006.
Keywords : Confocal microscopy, Variational methods, Total variation, Deconvolution.
@ARTICLE{dey_mrt_05,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Roux, P. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Richardson-Lucy Algorithm with Total Variation Regularization for 3D Confocal Microscope Deconvolution}, |
| year |
= |
{2006}, |
| month |
= |
{April}, |
| journal |
= |
{Microscopy Research Technique}, |
| volume |
= |
{69}, |
| pages |
= |
{260-266}, |
| url |
= |
{http://dx.doi.org/10.1002/jemt.20294}, |
| keyword |
= |
{Confocal microscopy, Variational methods, Total variation, Deconvolution} |
| } |
Abstract :
Confocal laser scanning microscopy is a powerful and popular technique for 3D imaging of biological specimens. Although confocal microscopy images are much sharper than standard epifluorescence ones, they are still degraded by residual out-of-focus light and by Poisson noise due to photon-limited
detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy iterative algorithm, which computes a maximum likelihood estimation adapted to Poisson statistics. As this algorithm tends to amplify noise, regularization constraints based on some prior knowledge on the data have to be applied to stabilize the solution. Here, we propose to combine the Richardson-Lucy algorithm with a regularization constraint based on Total Variation, which suppresses unstable oscillations while preserving object edges. We
show on simulated and real images that this constraint improves the deconvolution results as compared to the unregularized Richardson-Lucy algorithm, both visually and quantitatively. |
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7 Conference articles |
1 - Wavefront sensing for aberration modeling in fluorescence MACROscopy.
P. Pankajakshan and A. Dieterlen and G. Engler and Z. Kam and L. Blanc-Féraud and J. Zerubia and J.C. Olivo-Marin. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Chicago, USA, April 2011.
Keywords : fluorescence MACROscopy , phase retrieval, field aberration.
@INPROCEEDINGS{PanjakshanISBI2011,
|
| author |
= |
{Pankajakshan, P. and Dieterlen, A. and Engler, G. and Kam, Z. and Blanc-Féraud, L. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
= |
{Wavefront sensing for aberration modeling in fluorescence MACROscopy}, |
| year |
= |
{2011}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| address |
= |
{Chicago, USA}, |
| url |
= |
{http://hal.inria.fr/inria-00563988/en/}, |
| keyword |
= |
{fluorescence MACROscopy , phase retrieval, field aberration} |
| } |
Abstract :
In this paper, we present an approach to calculate the wavefront in
the back pupil plane of an objective in a fluorescent MACROscope.
We use the three-dimensional image of a fluorescent bead because it
contains potential pupil information in the ‘far’ out-of-focus planes
for sensing the wavefront at the back focal plane of the objective.
Wavefront sensing by phase retrieval technique is needed for several
reasons. Firstly, the point-spread function of the imaging system
can be calculated from the estimated pupil phase and used for image
restoration. Secondly, the aberrations in the optics of the objective
can be determined by studying this phase. Finally, the estimated
wavefront can be used to correct the aberrated optical path with-
out a wavefront sensor. In this paper, we estimate the wavefront of
a MACROscope optical system by using Bayesian inferencing and
derive the Gerchberg-Saxton algorithm as a special case. |
|
2 - Point-spread function model for fluorescence MACROscopy imaging.
P. Pankajakshan and Z. Kam and A. Dieterlen and G. Engler and L. Blanc-Féraud and J. Zerubia and J.C. Olivo-Marin. In Asilomar Conference on Signals, Systems and Computers, pages 1364-136, Pacific Grove, CA, USA , November 2010.
Keywords : fluorescence MACROscopy , point-spread function, pupil function, vignetting .
@INPROCEEDINGS{PanjakshanASILOMAR2010,
|
| author |
= |
{Pankajakshan, P. and Kam, Z. and Dieterlen, A. and Engler, G. and Blanc-Féraud, L. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
= |
{Point-spread function model for fluorescence MACROscopy imaging}, |
| year |
= |
{2010}, |
| month |
= |
{November}, |
| booktitle |
= |
{Asilomar Conference on Signals, Systems and Computers}, |
| pages |
= |
{1364-136}, |
| address |
= |
{Pacific Grove, CA, USA }, |
| url |
= |
{http://hal.inria.fr/inria-00555940/}, |
| keyword |
= |
{fluorescence MACROscopy , point-spread function, pupil function, vignetting } |
| } |
Abstract :
In this paper, we model the point-spread function (PSF) of a fluorescence MACROscope with a field aberration. The MACROscope is an imaging arrangement that is designed to directly study small and large specimen preparations without physically sectioning them. However, due to the different optical components of the MACROscope, it cannot achieve the condition of lateral spatial invariance for all magnifications. For example, under low zoom settings, this field aberration becomes prominent, the PSF varies in the lateral field, and is proportional to the distance from the center of the field. On the other hand, for larger zooms, these aberrations become gradually absent. A computational approach to correct this aberration often relies on an accurate knowledge of the PSF. The PSF can be defined either theoretically using a scalar diffraction model or empirically by acquiring a three-dimensional image of a fluorescent bead that approximates a point source. The experimental PSF is difficult to obtain and can change with slight deviations from the physical conditions. In this paper, we model the PSF using the scalar diffraction approach, and the pupil function is modeled by chopping it. By comparing our modeled PSF with an experimentally obtained PSF, we validate our hypothesis that the spatial variance is caused by two limiting optical apertures brought together on different conjugate planes. |
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3 - Blind deconvolution for diffraction-limited fluorescence microscopy.
P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), pages 740-743, Paris, France, May 2008.
Keywords : Confocal microscopy, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, total variation regularization.
Copyright : This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.
@INPROCEEDINGS{ppankajakshan08a,
|
| author |
= |
{Pankajakshan, P. and Zhang, B. and Blanc-Féraud, L. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Blind deconvolution for diffraction-limited fluorescence microscopy}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| pages |
= |
{740-743}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_ppankajakshan08a.pdf}, |
| keyword |
= |
{Confocal microscopy, Blind Deconvolution, point spread function, Richardson-Lucy algorithm, total variation regularization} |
| } |
Abstract :
Optical Sections of biological samples obtained from a fluorescence Confocal Laser Scanning Microscopes (CLSM) are often degraded by out-of-focus blur and photon counting noise. Such physical constraints on the observation are a result of the diffraction-limited nature of the optical system, and the reduced amount of light detected by the photomultiplier respectively. Hence, the image stacks can benefit from postprocessing restoration methods based on deconvolution. The parameters of the acquisition system’s Point Spread Function (PSF) may vary during the course of experimentation, and so they have to be estimated directly from the observation data. We describe here an alternate minimization algorithm for the simultaneous blind estimation of the specimen 3D distribution of fluorescent sources and the PSF. Experimental results on real data show that the algorithm provides very good deconvolution results in comparison to theoretical microscope PSF models. |
|
4 - Parametric blind deconvolution for confocal laser scanning microscopy.
P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. 29th International Conference of IEEE EMBS (EMBC-07), pages 6531-6534, August 2007.
Keywords : Confocal microscopy, Blind Deconvolution, Poisson noise, Total variation, EM algorithm, Bayesian estimation.
Copyright : ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@INPROCEEDINGS{Pankajakshan07a,
|
| author |
= |
{Pankajakshan, P. and Zhang, B. and Blanc-Féraud, L. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{Parametric blind deconvolution for confocal laser scanning microscopy}, |
| year |
= |
{2007}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. 29th International Conference of IEEE EMBS (EMBC-07)}, |
| pages |
= |
{6531-6534}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/4352184/4352185/04353856.pdf?tp=&isnumber=&arnumber=4353856}, |
| keyword |
= |
{Confocal microscopy, Blind Deconvolution, Poisson noise, Total variation, EM algorithm, Bayesian estimation} |
| } |
Abstract :
In this paper, we propose a method for the
iterative restoration of fluorescence Confocal Laser Scanning
Microscopic (CLSM) images and parametric estimation of the
acquisition system’s Point Spread Function (PSF). The CLSM is
an optical fluorescence microscope that scans a specimen in 3D
and uses a pinhole to reject most of the out-of-focus light. However,
the quality of the images suffers from two basic physical
limitations. The diffraction-limited nature of the optical system,
and the reduced amount of light detected by the photomultiplier
cause blur and photon counting noise respectively. These images
can hence benefit from post-processing restoration methods
based on deconvolution. An efficient method for parametric
blind image deconvolution involves the simultaneous estimation
of the specimen 3D distribution of fluorescent sources and
the microscope PSF. By using a model for the microscope
image acquisition physical process, we reduce the number of
free parameters describing the PSF and introduce constraints.
The parameters of the PSF may vary during the course of
experimentation, and so they have to be estimated directly from
the observed data. A priori model of the specimen is further
applied to stabilize the alternate minimization algorithm and to
converge to the solutions. |
|
5 - A study of Gaussian approximations of fluorescence microscopy PSF models.
B. Zhang and J. Zerubia and J.C. Olivo-Marin. In Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIII of Proc. SPIE, in press, Vol. 6090, San Jose, USA, January 2006.
Copyright : SPIE
@INPROCEEDINGS{zerubia_spie06,
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{Zhang, B. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
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{A study of Gaussian approximations of fluorescence microscopy PSF models}, |
| year |
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{2006}, |
| month |
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{January}, |
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{Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIII of Proc. SPIE, in press}, |
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{6090}, |
| address |
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{San Jose, USA}, |
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|
6 - Deconvolution in confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB), pages 117--120, May 2004.
@INPROCEEDINGS{Dey04b,
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| author |
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{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
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{Deconvolution in confocal microscopy with total variation regularization}, |
| year |
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{2004}, |
| month |
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{May}, |
| booktitle |
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{Proc. French-Danish Workshop on Spatial Statistics and Image Analysis in Biology (SSIAB)}, |
| pages |
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{117--120}, |
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{http://www3.jouy.inra.fr/miaj/public/imaste/ssiab2004/program/abw92/}, |
| keyword |
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{} |
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|
7 - A deconvolution method for confocal microscopy with total variation regularization.
N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and J.C. Olivo-Marin and J. Zerubia. In Proc. IEEE International Symposium on Biomedical Imaging (ISBI), Arlington, USA, April 2004.
Keywords : 3D confocal microscopy, Poisson deconvolution, total variation regularization.
@INPROCEEDINGS{Dey04a,
|
| author |
= |
{Dey, N. and Blanc-Féraud, L. and Zimmer, C. and Kam, Z. and Olivo-Marin, J.C. and Zerubia, J.}, |
| title |
= |
{A deconvolution method for confocal microscopy with total variation regularization}, |
| year |
= |
{2004}, |
| month |
= |
{April}, |
| booktitle |
= |
{Proc. IEEE International Symposium on Biomedical Imaging (ISBI)}, |
| address |
= |
{Arlington, USA}, |
| pdf |
= |
{http://dx.doi.org/10.1109/ISBI.2004.1398765}, |
| keyword |
= |
{3D confocal microscopy, Poisson deconvolution, total variation regularization} |
| } |
Abstract :
Confocal laser scanning microscopy is a powerful and increasingly popular technique for 3D imaging of biological specimens. However the acquired images are degraded by blur from out-of-focus light and Poisson noise due to photon-limited detection. Several deconvolution methods have been proposed to reduce these degradations, including the Richardson-Lucy algorithm, which computes a maximum likelihood estimation adapted to Poisson statistics. However this method tends to amplify noise if used without regularizing constraint. Here, we propose to combine the Richardson-Lucy algorithm with a regularizing constraint based on total variation, whose smoothing avoids oscillations while preserving edges. We show on simulated images that this constraint improves the deconvolution result both visually and using quantitative measures. |
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