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Praveen Pankajakshan
Former PhD Student
 Keywords : Variational methods, MCMC, Wavelets, Parameter Estimation, Deconvolution, 3D Reconstruction
 Project : P2R France-Israel
 Demo : see this author's demo
 Contact :
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| Abstract :
I am currently working on the parametric blind deconvolution of Confocal Laser Scanning Microscope (CLSM) images. The CLSM is an optical fluorescence microscope that scans sections of a specimen in 3D and uses a pinhole to reject most out-of-focus light. However, the quality of confocal microscope images suffers from two basic physical limitations.
First, out-of-focus blurs due to the diffraction-limited nature of the optical microscope and secondly, the confocal pinhole drastically reduces the amount of photons detected by the photomultiplier causing poisson noise. The images produces by the CLSM can therefore benefit from post processing by deconvolution methods designed to reduce the blur and noise.
Our current goal is to develop a fast and efficient algorithm for
simultaneous estimation of the point-spread function (PSF) of the microscope and the specimen function. We realize that a good estimation of the PSF is very important for restoration of the original specimen.
However, estimation of the PSF is an undetermined problem with no known unique solution. We overcome this problem by using a physical acquisition model of the microscope and by introducing a priori knowledge about the specimen. This stabilizes the estimation procedure and helps in deciding
between candidate solutions. |
Last publications in Ariana Research Group :
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,
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| 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. |
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. |
Blind Deconvolution for Confocal Laser Scanning Microscopy.
P. Pankajakshan. PhD Thesis, Universite de Nice Sophia Antipolis, December 2009.
Keywords : Confocal Laser Scanning Microscopy, Blind Deconvolution, point spread function, Maximum likelihood estimation , total variation regularization.
@PHDTHESIS{PankajakshanThesis09,
|
| author |
= |
{Pankajakshan, P.}, |
| title |
= |
{Blind Deconvolution for Confocal Laser Scanning Microscopy}, |
| year |
= |
{2009}, |
| month |
= |
{December}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| url |
= |
{http://tel.archives-ouvertes.fr/tel-00474264/fr/}, |
| keyword |
= |
{Confocal Laser Scanning Microscopy, Blind Deconvolution, point spread function, Maximum likelihood estimation , total variation regularization} |
| } |
Résumé :
La microscopie confocale à balayage laser, est une technique puissante pour
étudier les spécimens biologiques en trois dimensions (3D) par sectionnement
optique. Elle permet d’avoir des images de spécimen vivants à une résolution de
l’ordre de quelques centaines de nanomètres. Bien que très utilisée, il persiste
des incertitudes dans le procédé d’observation. Comme la réponse du système à
une impulsion, ou fonction de flou (PSF), est dépendante à la fois du spécimen
et des conditions d’acquisition, elle devrait être estimée à partir des images
observées du spécimen. Ce problème est mal posé et sous déterminé. Pour
obtenir une solution, il faut injecter des connaisances, c’est à dire, a priori dans le
problème. Pour cela, nous adoptons une approche bayésienne. L’état de l’art des
algorithmes concernant la déconvolution et la déconvolution aveugle est exposé
dans le cadre d’un travail bayésien. Dans la première partie, nous constatons
que la diffraction due à l’objectif et au bruit intrinsèque à l’acquisition, sont les
distorsions principales qui affectent les images d’un spécimen. Une approche
de minimisation alternée (AM), restaure les fréquences manquantes au-delà de
la limite de diffraction, en utilisant une régularisation par la variation totale
sur l’objet, et une contrainte de forme sur la PSF. En outre, des méthodes
sont proposées pour assurer la positivité des intensités estimées, conserver le
flux de l’objet, et bien estimer le paramètre de la régularisation. Quand il
s’agit d’imager des spécimens épais, la phase de la fonction pupille, due aux
aberrations sphériques (SA) ne peut être ignorée. Dans la seconde partie, il est
montré qu’elle dépend de la difference à l’index de réfraction entre l’objet et
le milieu d’immersion de l’objectif, et de la profondeur sous la lamelle. Les
paramètres d’imagerie et la distribution de l’intensité originelle de l’objet sont
calculés en modifiant l’algorithme AM. Due à la nature de la lumière incohérente
en microscopie à fluorescence, il est possible d’estimer la phase à partir des
intensités observées en utilisant un modèle d’optique géométrique. Ceci a été
mis en évidence sur des données simulées. Cette méthode pourrait être étendue
pour restituer des spécimens affectés par les aberrations sphériques. Comme la
PSF varie dans l’espace, un modèle de convolution par morceau est proposé, et la
PSF est approchée. Ainsi, en plus de l’objet, il suffit d’estimer un seul paramétre libre. |
Abstract :
Confocal laser scanning microscopy is a powerful technique for studying
biological specimens in three dimensions (3D) by optical sectioning. It permits
to visualize images of live specimens non-invasively with a resolution of few
hundred nanometers. Although ubiquitous, there are uncertainties in the
observation process. As the system’s impulse response, or point-spread function
(PSF), is dependent on both the specimen and imaging conditions, it should be
estimated from the observed images in addition to the specimen. This problem is
ill-posed, under-determined. To obtain a solution, it is necessary to insert some
knowledge in the form of a priori and adopt a Bayesian approach. The state of
the art deconvolution and blind deconvolution algorithms are reviewed within a
Bayesian framework. In the first part, we recognize that the diffraction-limited
nature of the objective lens and the intrinsic noise are the primary distortions
that affect specimen images. An alternative minimization (AM) approach
restores the lost frequencies beyond the diffraction limit by using total variation
regularization on the object, and a spatial constraint on the PSF. Additionally,
some methods are proposed to ensure positivity of estimated intensities, to
conserve the object’s flux, and to well handle the regularization parameter.
When imaging thick specimens, the phase of the pupil function due to spherical
aberration (SA) cannot be ignored. It is shown to be dependent on the refractive
index mismatch between the object and the objective immersion medium, and
the depth under the cover slip. The imaging parameters and the object’s original
intensity distribution are recovered by modifying the AM algorithm. Due to
the incoherent nature of the light in fluorescence microscopy, it is possible to
retrieve the phase from the observed intensities by using a model derived from
geometrical optics. This was verified on the simulated data. This method could
also be extended to restore specimens affected by SA. As the PSF is space varying,
a piecewise convolution model is proposed, and the PSF approximated so that,
apart from the specimen, it is sufficient to estimated only one free parameter.
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All publications in Ariana Research Group
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