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International audience; We propose a combination of 4Pi and Theta microscopies to improve the resolution of fluorescence microscopy by using six microscope objectives in a configuration we call Multiple Objective Microscopy (MOM). A resolution in the 100 nm range is obtained in the three dimensions using low numerical aperture, long working distance objectives. The obtained results not only show that high resolution is not restricted to high numerical aperture objectives, but also open the possibility of exploring large volumes with a very good resolution.

Optical microscopy allows us to study living fluorescent biological samples. Optical sectioning is a technique to obtain three-dimensional (3D) information about the observed object by acquiring a stack of two-dimensional (2D) images at different depths through the sample. However, the specific shape of the 3D optical transfer function of the optical microscope leads to images presenting defects, such as, for example, an apparent elongation along the vertical axis. It is therefore necessary to preprocess the images before any quantitative measurement is performed. This image restoration can be obtained by deconvolution of the acquired 3D image. We have tested several deconvolution algorithms on synthetic images, obtained by convolution of a solid sphere with a measured point spread function. We have compared the restored image with the original one (shape and volume). The linear least-squares method is fast, but artefacts are still present in the restored images. The Carrington method is well adapted to thin objects. The maximum likelihood - expectation maximization method leads to a good reconstruction of the object, but is very time consuming. Resume. La microscopie optique permet l'etude de specimens biologiques vivants et fluorescents. La technique par coupes seriees donne des informations tridimensionnelles (3D) sur l'objet etudie par l'acquisition d'une pile d'images bidimensionnelles a differentes profondeurs de focalisation a travers l'echantillon. Les specificites de la fonction de transfert optique 3D du microscope conduisent a des images presentant des defauts, comme par exemple une elongation apparente selon l'axe vertical. Il est donc necessaire de traiter les images avant toute mesure quantitative. On procede a une deconvolution de l'image 3D obtenue. Nous avons teste differents algorithmes de deconvolution sur des images de synthese obtenues par convolution d'une bille pleine avec une fonction de transfert optique mesuree. Nous avons compare, en forme et en volume, les images restaurees avec l'image d'origine. La methode `linear least square' est rapide, mais l'image restauree presente des artefacts. La methode de Carrington est bien adaptee a la restauration d'objets fins. La methode `maximum likelihood - expectation maximization' permet une bonne reconstruction des images, mais demande de grands temps de calcul.

3-D optical fluorescent microscopy now becomes an efficient tool for the volume investigation of living biological samples. Developments in instrumentation have permitted to beat off the conventional Abbe limit. In any case the recorded image can be described by the convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. Due to the finite resolution of the instrument, the original object is recorded with distortions and blurring, and contaminated by noise. This induces that relevant biological information cannot be extracted directly from raw data stacks. If the goal is 3-D quantitative analysis, then to assess optimal performance of the instrument and to ensure the data acquisition reproducibility, the system characterization is mandatory. The PSF represents the properties of the image acquisition system; we have proposed the use of statistical tools and Zernike moments to describe a 3-D PSF system and to quantify the variation of the PSF. This first step toward standardization is helpful to define an acquisition protocol optimizing exploitation of the microscope depending on the studied biological sample. Before the extraction of geometrical information and/or intensities quantification, the data restoration is mandatory. Reduction of out-of-focus light is carried out computationally by deconvolution process. But other phenomena occur during acquisition, like fluorescence photo degradation named "bleaching", inducing an alteration of information needed for restoration. Therefore, we have developed a protocol to pre-process data before the application of deconvolution algorithms. A large number of deconvolution methods have been described and are now available in commercial package. One major difficulty to use this software is the introduction by the user of the "best" regularization parameters. We have pointed out that automating the choice of the regularization level; also greatly improves the reliability of the measurements although it facilitates the use. Furthermore, to increase the quality and the repeatability of quantitative measurements a pre-filtering of images improves the stability of deconvolution process. In the same way, the PSF prefiltering stabilizes the deconvolution process. We have shown that Zemike polynomials can be used to reconstruct experimental PSF, preserving system characteristics and removing the noise contained in the PSF.

3-D optical fluorescence microscopy is an efficient tool for volumic investigation of biological samples. Nevertheless the image acquired by this way is altered by the properties of the microscope, according to its Point Spread Function (PSF). The aim of deconvolution algorithms is the reassignment of defocused information. This method provides an improvement in data quality and the possibility to compare specimens acquired using different systems. But deconvolution requires making a compromise between the precision of the result and the stability of the process, since this stability is directly related to the noise level of the data. This noise can be of different types, mainly electronic noise due to the sensors but we also include in the term "noise" the variation of fluorescence during the acquisition. Numerous deconvolution algorithms exist, giving variable results according to specimen characteristics. For the cases where deconvolution is not enough to obtain usable data, we developed some pre-process treatments. These tools can be used separately or consecutively depending on the application needs and specimen requirements.

3-D optical fluorescent microscopy becomes now an efficient tool for volumic investigation of living biological samples. The 3-D data can be acquired by Optical Sectioning Microscopy which is performed by axial stepping of the object versus the objective. For any instrument, each recorded image can be described by a convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. To assess performance and ensure the data reproducibility, as for any 3-D quantitative analysis, the system indentification is mandatory. The PSF explains the properties of the image acquisition system; it can be computed or acquired experimentally. Statistical tools and Zernike moments are shown appropriate and complementary to describe a 3-D system PSF and to quantify the variation of the PSF as function of the optical parameters. Some critical experimental parameters can be identified with these tools. This is helpful for biologist to define an aquisition protocol optimizing the use of the system. Reduction of out-of-focus light is the task of 3-D microscopy; it is carried out computationally by deconvolution process. Pre-filtering the images improves the stability of deconvolution results, now less dependent on the regularization parameter; this helps the biologists to use restoration process.

International audience; 3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented.

3-D optical fluorescence microscopy becomes now an efficient tool for volumic investigation of living biological samples. However, acquired raw data suffer from different distortions. In order to carry out biological analysis, restoration of raw data by deconvolution is mandatory. The system identification is useful to obtain the knowledge of the actual system and to quantify the influence of experimental parameters. High order centered moments are used as PSF descriptors. Oil immersion index, numerical aperture and specimen thickness are critical parameters for data quality. Furthermore, PSF identification is helpful to precise the experimental protocol. Application to 3-D anthracycline distribution in breast cancer cells is presented.© (2001) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

International audience; Except for blind methods, deconvolution of 3-D data sets acquired from a fluorescence microscope requires the knowledge of the point spread (PSF) of the instrument. Unsing the XCOSM package, we show first with simulations and then with recorded data that it is possible to recover from an experimental PSF some parameters, which are very difficult or impossible to measure during the acquisition, like the specimen depth or the immersion medium refractive index. Doing so, we can precise the acquisition protocol, which helps to use the instrument under optimal conditions. Furthermore, the knowledge of the actual acquisition condtions permits to use fo the deconvolution process a computed PSF, which is noiseless and as close as possible to the actual PSF. This helps to reduce errors in quantitative measurements after deconvolution, as shown with computations.

International audience; A split spectrum processing technique using a novel moving bandwidth minimization (MBM) method was developed to detect multiple specular targets having different spectral characteristics. Mathematical morphology (MM) algorithms were also implemented in order to compare the results. An experimental approach to optimal parameter determination is described. These non-linear filtering methods are applied to medical in vivo imaging to illustrate specular detection and signal to noise ratio (SNR) enhancement.

The complete process, image acquisition, deblurring, 3D reconstruction and analysis has been tested on 160 normal T lymphoid cells marked with monoclonal antibodies CD4-CD8. The images are acquired from a conventional optical microscope illuminated by a mercury vapor lamp. A set of 16 serial image cuts is first grabbed by a high sensitivity Silicon Intensified Target (SIT) camera fitted on the microscope. The 2D image cuts are then deblurred using an original deconvolution method developed in the laboratory. The 3D reconstruction is processed slice by slice using a variant of the 2D Delaunay triangulation. To get a correct triangulation in the case of our specific application the following stringent requirements must be met. First, we exclude the possibility of joining two contours if we meet an empty cut between them, and secondly we must avoid branching points and finally, we state that reconstructed shapes may not have holes. The 3D reconstruction highlights some qualitative characteristics of the cells. So we can show that the fluorescent spots are either scattered on the membrane surface and present a regular radial arrangement or on the contrary are confined in a restricted area. Accordingly we propose to introduce a spatial coefficient in order to characterize such a volume distribution. In a further development we plan to obtain discriminant descriptors of the immunological status of hematopoietic cells.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The aim of our study is to improve the performances of an optical microscope by image deconvolution technique to attain that of a confocal one in the field of laser cytofluorescence. The fluorescence of antigen lymphocyte sites marked by rhodamine is induced by a laser ((lambda) equals 543 nm) or a mercury vapor lamp. A set of scanned fluorescence images is acquired at different focal planes by a SIT camera, fitted on an optical ZEISS microscope (N.A. 1.25, X100). The entire system is controlled by a PC equipped with a MATROX-MVP-AT image processing card. Since an optical microscope has a more important focal depth than a confocal one, an improved iterative deconvolution algorithm of Van Cittert's has been used to artificially reduce the focal depth. In order to ensure the convergence of such an iterative algorithm, a new criterion for relaxation coefficient is defined through a theoretical study. The experiments show an improvement of 50% in the spatial x-y resolution of 30% in optical z axis gain. As regards our application, this processing brings our system to a comparable performance level as a confocal microscope.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The convergence of Van Cittert’s iterative method of deconvolution is studied from an algebraic point of view without any special prior condition with respect to the system matrix. The convergence criteria are expressed in terms of system eigenvalues. We choose bounds for the general relaxation coefficient μ of Van Cittert’s additional term so as to ensure convergence. We show that the bounds can be estimated from the system matrix. Many powerful nonlinear deconvolution techniques are derived from Van Cittert’s method, even though it appears outmoded. As an example, we demonstrate that Gold’s iterative algorithm is a special Van Cittert’s algorithm with a variable relaxation factor μ