Die vorliegende Arbeit befasst sich mit zwei neuen methodischen Ansätzen auf dem Gebiet der Fluoreszenzmikroskopie. Im ersten Teil der Arbeit wir eine Methode vorgestellt, mit der die Winkelselektivität der Fluoreszenzanregung verbessert werden kann. Die ExPAN (excitation polarization angle narrowing) genannte Technik nutzt stimulierte Emission, um den Effekt der Photoselektion zu vergrößern. ExPAN lässt sich potentiell für verschiedene Methoden einsetzen, in denen fluoreszenzmarkierte Proben untersucht werden und ist insbesondere im Kontext von Fluoreszenzanisotropie-Messungen oder der Bestimmung von molekularen Orientierungen von Interesse. Solche Methoden finden in den Biowissenschaften breite Anwendung und werden z.B. zum Studium von Rezeptor-Liganden-Interaktionen oder der Proteindynamik eingesetzt. Im Rahmen der Arbeit wird ExPAN in Kombination mit einem neuen Ansatz in der Weitfeldmikroskopie untersucht, bei der die Orientierung von Farbstoffmolekülen als Kontrastmechanismus genutzt wird. Dabei wird die Polarisationsrichtung des Anregungslichts rotiert, um Informationen über die molekulare Orientierung zu gewinnen. Aufgrund der Photoselektion weist das Fluoreszenzsignal von Molekülen mit bevorzugter Ausrichtung dadurch eine periodische Modulation auf. Es wird gezeigt, dass diese Information zur Unterscheidung von Molekülen mit abweichender Orientierung genutzt werden kann, selbst wenn sich deren Signale räumlich überlagern. Für die Versuche wurde ein modifiziertes Weitfeld-Mikroskop konstruiert und die Methode zum einen experimentell an Einzelmolekülen und zum anderen mittels Simulationen erprobt. Dabei konnten Signale von Farbstoffmolekülen mit einem Abstand von bis zu 80 nm separiert werden. Darüber hinaus wurde ein moduliertes Fluoreszenzsignal bei oberflächenmarkierten Mikropartikeln in wässriger Lösung sowie bei fixierten biologischen Proben beobachtet. Eine Verbesserung der Photoselektion durch ExPAN wird experimentell nachgewiesen und gezeigt, dass mit ExPAN auch ähnlich orientierte Moleküle unterschieden werden können. Im zweiten Teil der Arbeit wird eine Methode zur Verbesserung der Auflösung von konfokalen Laser-Scanning-Mikroskopen vorgestellt, die als Multidetektor-Scanning (MDS) bezeichnet wird und auf dem Prinzip der Image-Scanning-Mikroskopie (ISM) beruht. Mit ISM lässt sich die Auflösung von Fluoreszenzmikroskopen theoretisch verdoppeln. Da ISM einen Flächendetektor voraussetzt, wurden in der Vergangenheit hauptsächlich CCD oder CMOS Kameras als Detektoren eingesetzt. In dieser Arbeit werden anstelle einer Kamera mehrere Einzelphotonendetektoren verwendet und über ein Glasfaserbündel zu einem Flächendetektor kombiniert. Dadurch ist es erstmals möglich, die Methode in Verbindung mit Fluoreszenzlebensdauer-Mikroskopie (FLIM) einzusetzen. FLIM hat sich in den Biowissenschaften als wichtige Mikroskopie-Technik etabliert und wird unter anderem bei Protein-Protein-Interaktionsstudien oder zur Untersuchung des NADH-Metabolismus eingesetzt. Die Verbesserung der räumlichen Auflösung von FLIM mit MDS ist somit für eine Reihe von biologischen Fragestellungen von potentiellem Interesse. Im Rahmen der Arbeit wurde ein Multidetektor-Scanning-Mikroskop konstruiert und durch die Vermessung von fluoreszierenden Mikropartikeln charakterisiert. Eine Verbesserung der Auflösung durch MDS wird an fixierten biologischen Proben demonstriert. Dabei wurde eine Auflösung von 168 nm mit MDS sowie 146 nm mit MDS und Dekonvolution erreicht. Schließlich wird die Kombination der Methode mit Fluoreszenzlebensdauer-Mikroskopie demonstriert.

No description available.

Membranproteine spielen eine wichtige Rolle in vielen biochemischen Prozessen der Zelle, wie zum Beispiel der Signaltransduktion, der Zelladhesion oder auch der Erkennung von Krankheitserregern. Viele dieser Proteine sind von Bedeutung für die Entwicklung neuer innovativer Medikamente. Somit hat auch die Entwicklung von Sensoren, die die Untersuchung von Membranproteinen in ihrer natürlichen Umgebung erlauben an Bedeutung gewonnen [1]. Thema dieser Doktorarbeit war die Entwicklung von Analysekonzepten die es ermöglichen unterschiedliche Aspekte von Membraninteraktionen zu untersuchen und zu quantifizieren. Als Analysemethode wurde dafür reflektometrische Interferenz Spektroskopie (RIfS) eine markierungsfreie, optische Methode verwendet. RIfS erlaubt es die Höhe dünner transparenter Filme zu bestimmen, indem das Weißlicht-Reflexionspektrum eines solchen Films aufgezeichnet wird. Durch die Überlagerung der in dem Film mehrfach reflektierten Teilstrahlen entsteht ein Interferenzmuster im Reflexionsspektrum, welches Aufschluß gibt über die Schichtdicke und den Brechungsindex des transparenten Films. Es wurde bereits gezeigt, dass RIfS eine geeignete Methode zur Untersuchung von Protein-ProteinWechselwirkungen ist [2]. Aus diesem Grund wurde RIfS als Detektionsverfahren für die Entwicklung eines Membransensors gewählt. Im Laufe dieser Arbeit entstanden zwei Aufbauten für reflektometrische Messungen. Ein Standard RIfS Aufbau und ein Instrument das die Methode mit Fluoreszenz-Mikroskopie kombiniert. Um dieWechselwirkung von Proteinen selbst und Proteinen mit Membranbestandteilen wie Lipiden zu untersuchen, wurde ein Konzept basierend auf festkörperunterstützten Membranen entwickelt. Dieses Experiment erlaubt es die Wechselwirkungen auf artifiziellen Membranen, sowie auf rekonstituierten Zellmembranen zu untersuchen. Zudem wurde ein Analysekonzept mit Nano-BLMs entwickelt, dass es erlaubt den simultanen Transport von Molekülen in ein membranverschlossenes Kompartiment hinein als auch heraus zu beobachten. Neben diesen membranbasierten Experimenten wurde auch ein Konzept entwickelt, welches es erlaubt die molekulare Erkennungsreaktion von sehr kleiner Analyten direkt zu messen. Dieses Messkonzept erlaubt es die Bindung von Molekülen mit sehr kleinem Molekulargewicht an einen auf dem Sensor immobilisierten Partner direkt zu quantifizieren.

Protein-DNA interactions govern the fundamental cellular processes of DNA replication, transcription, repair, and chromosome organisation. Despite their importance, the detailed molecular mechanisms of protein-DNA interactions and their organisation in the cell remain elusive. The complexity of molecular biology demands new experimental concepts that resolve the structural and functional diversity of biomolecules. In this thesis, I describe fluorescence methods that give a direct view on protein-DNA interactions at the single-molecule level. These methods employ photoswitching to control the number of active fluorophores in the sample. Forster Resonance Energy Transfer (FRET) measures the distance between a donor and an acceptor fluorophore to report on biomolecular structure and dynamics in vitro. Because a single distance gives only limited structural information, I developed "switchable FRET" that employs photoswitching to sequentially probe multiple FRET pairs per molecule. Switchable FRET resolved two distances within static and dynamic DNA constructs and protein-DNA complexes. Towards application of switchable FRET, I investigated aspects of the nucleotide selection mechanism of DNA polymerase. I further explored application of single-molecule imaging in the complex environment of the living cell. Photoswitching was used to resolve the precise localisations of individual fluorophores. I constructed a super-resolution fluorescence microscope to image fixed cellular structures and track the movement of individual fluorescent fusion proteins in live bacteria. I applied the method to directly visualise DNA repair processes by DNA polymerase I and ligase, generating a quantitative account of their repair rates, search times, copy numbers, and spatial distribution in the cell. I validated the approach by tracking diffusion of replisome components and their association with the replication fork. Finally, super-resolution microscopy showed dense clusters of SMC (Structural Maintenance of Chromosomes) protein complexes in vivo that have previously been hidden by the limited resolution of conventional microscopy.

<p>Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.</p><p>Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions. </p><p>To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.</p><p>To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology. </p><p>Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy. </p><p>Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation. </p><p>Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone. </p><p>Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted. </p><p>In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.</p> / Dissertation

We have investigated some of the many photonic and plasmonic properties of the diatom Coscinodiscus wailesii. We start by showing that when diatom frustules are converted to high-index magnesium silicide while maintaining their structure, they exhibit a broad (1μm - 2μm) photonic bandgap that varies in wavelength according to the position and angle of the incident light on the frustule. We then demonstrate the use of the micro and nanostructured silica diatom frustule as a low-cost, easily prepared substrate for surface-enhanced Raman spectroscopy by coating the frustule in 25 nm of silver and a monolayer of thiophenol. Some potential applications of diatoms to water quality measurements are suggested, and steps are taken to image a diatom frustule and chloroplasts simultaneously in vivo using rhodamine 19 dye and fluorescence microscopy. We propose future experiments that could ascertain whether there is any biological effect of the light filtering properties of the diatom frustule, and put forth some suggestions as to how to influence the morphology and photonic properties of the frustule via chemical contaminants in the diatom seawater growth medium.

<p>Many research questions in biological research lead to numerous microscope images that need to be evaluated. Here digital image cytometry, i.e., quantitative, automated or semi-automated analysis of the images is an important rapidly growing discipline. This thesis presents contributions to that field. The work has been carried out in close cooperation with biomedical research partners, successfully solving real world problems.</p><p>The world is 3D and modern imaging methods such as confocal microscopy provide 3D images. Hence, a large part of the work has dealt with the development of new and improved methods for quantitative analysis of 3D images, in particular fluorescently labeled skeletal muscle cells.</p><p>A geometrical model for robust segmentation of skeletal muscle fibers was developed. Images of the multinucleated muscle cells were pre-processed using a novel spatially modulated transform, producing images with reduced complexity and facilitating easy nuclei segmentation. Fibers from several mammalian species were modeled and features were computed based on cell nuclei positions. Features such as myonuclear domain size and nearest neighbor distance, were shown to correlate with body mass, and femur length. Human muscle fibers from young and old males, and females, were related to fiber type and extracted features, where myonuclear domain size variations were shown to increase with age irrespectively of fiber type and gender.</p><p>A segmentation method for severely clustered point-like signals was developed and applied to images of fluorescent probes, quantifying the amount and location of mitochondrial DNA within cells. A synthetic cell model was developed, to provide a controllable golden standard for performance evaluation of both expert manual and fully automated segmentations. The proposed method matches the correctness achieved by manual quantification. </p><p>An interactive segmentation procedure was successfully applied to treated testicle sections of boar, showing how a common industrial plastic softener significantly affects testosterone concentrations.</p>

Biomedical study researchers using animals to model disease and treatment need fast, deep, noninvasive, and inexpensive multi-channel imaging methods. Traditional fluorescence microscopy meets those criteria to an extent. Specifically, two-photon and confocal microscopy, the two most commonly used methods, are limited in penetration depth, cost, resolution, and field of view. In addition, two-photon microscopy has limited ability in multi-channel imaging. Light sheet microscopy, a fast developing 3D fluorescence imaging method, offers attractive advantages over traditional two-photon and confocal microscopy. Light sheet microscopy is much more applicable for in vivo 3D time-lapsed imaging, owing to its selective illumination of tissue layer, superior speed, low light exposure, high penetration depth, and low levels of photobleaching. However, standard light sheet microscopy using Gaussian beam excitation has two main disadvantages: 1) the field of view (FOV) of light sheet microscopy is limited by the depth of focus of the Gaussian beam. 2) Light-sheet images can be degraded by scattering, which limits the penetration of the excitation beam and blurs emission images in deep tissue layers. While two-sided sheet illumination, which doubles the field of view by illuminating the sample from opposite sides, offers a potential solution, the technique adds complexity and cost to the imaging system. We investigate a new technique to address these limitations: Bessel light sheet microscopy in combination with incoherent nonlinear Structured Illumination Microscopy (SIM). Results demonstrate that, at visible wavelengths, Bessel excitation penetrates up to 250 microns deep in the scattering media with single-side illumination. Bessel light sheet microscope achieves confocal level resolution at a lateral resolution of 0.3 micron and an axial resolution of 1 micron. Incoherent nonlinear SIM further reduces the diffused background in Bessel light sheet images, resulting in confocal quality images in thick tissue. The technique was applied to live transgenic zebra fish tg(kdrl:GFP), and the sub-cellular structure of fish vasculature genetically labeled with GFP was captured in 3D. The superior speed of the microscope enables us to acquire signal from 200 layers of a thick sample in 4 minutes. The compact microscope uses exclusively off-the-shelf components and offers a low-cost imaging solution for studying small animal models or tissue samples.

<p>Two-photon excited fluorescence microscopy (TPM) has become a standard biological imaging tool due to its simplicity and versatility. The fundamental contrast mechanism is derived from fluorescence of intrinsic or extrinsic markers via simultaneous two-photon absorption which provides inherent optical sectioning capabilities. The NIR-II wavelength window (1000–1350 nm), a new biological imaging window, is promising for TPM because tissue components scatter and absorb less at longer wavelengths, resulting in deeper imaging depths and better contrasts, compared to the conventional NIR-I imaging window (700–1000 nm). However, the further enhancement of TPM has been hindered by a lack of good two-photon fluorescent imaging markers in the NIR-II. </p><p>In this dissertation, we design and characterize novel two-photon imaging markers, optimized for NIR-II excitation. More specifically, the work in this dissertation includes the investigation of two-photon excited fluorescence of various highly conjugated porphyrin arrays in the NIR-II excitation window and the utilization of nanoscale polymersomes that disperse these highly conjugated porphyrin arrays in their hydrophobic layer in aqueous environment. The NIR-emissive polymersomes, highly conjugated porphyrins-dispersed polymersomes, possess superb two-photon excited brightness. The synthetic nature of polymersomes enables us to formulate fully biodegradable, non-toxic and surface-functionalized polymersomes of varying diameters, making them a promising and fully customizable multimodal diagnostic nano-structured soft-material for deep tissue imaging at high resolutions. We demonstrated key proof-of-principle experiments using NIR-emissive polymersomes for in vivo two-photon excited fluorescence imaging in mice, allowing visualization of blood vessel structure and identification of localized tumor tissue. In addition to spectroscopic characterization of the two-photon imaging agents and their imaging capabilities/applications, the effect of the laser setup (e.g., repetition rate of the laser, peak intensity, system geometry) on two-photon excited fluorescence measurements is explored to accurately measure two-photon absorption (TPA) cross-sections. A simple pulse train shaping technique is demonstrated to separate pure nonlinear processes from linear background signals, which hinders accurate quantification of TPA cross-sections.</p> / Dissertation

Dans cette thèse, nous nous intéressons à la restauration d'image tridimensionnelle de microscopie de fluorescence. Deux difficultés majeures dans ce système d'imagerie sont traitées. La première est le flou variable en profondeur qui est dû aux aberrations induites par la variation des indices de réfraction dans le système optique et le spécimen imagé. La deuxième est le bruit qui est principalement dû au processus de comptage de photons. L'objectif de cette thèse est de réduire ces distorsions afin de fournir aux biologistes une image de meilleure qualité possible. Dans la première partie de cette thèse, nous étudions les modèles d'approximation du flou variable en profondeur et nous choisissons un modèle adéquat au problème d'inversion. Dans ce modèle, la réponse impulsionnelle (RI) variable en profondeur est approchée par une combinaison convexe d'un ensemble de RIs invariables spatialement. Nous développons pour ce modèle deux méthodes rapides de restauration non-aveugle par minimisation d'un critère régularisé, chacune d'elles est adaptée au type de bruit présent dans les images de microscopie confocale ou à champ large. Dans la deuxième partie, nous abordons le problème de restauration aveugle et proposons deux méthodes dans lesquelles le flou variable en profondeur et l'image sont conjointement estimés. Dans la première méthode, la RI est estimée en chaque voxel du volume considéré afin de laisser une grande liberté sur la forme de la RI, tandis que dans la deuxième méthode, la forme de la RI est contrainte par une fonction gaussienne afin de réduire le nombre de variables inconnues et l'espace des solutions possibles. Dans ces deux méthodes d'estimation aveugle, l'effet des aberrations optiques n'est pas efficacement estimé en raison du manque d'information. Nous améliorons ces méthodes d'estimation en alternant des contraintes dans les domaines fréquentiel et spatial. Des résultats sont montrés en simulation et sur des données réelles. / In this thesis, we focus on the restoration of three-dimensional image of fluorescence microscopy. Two major difficulties in this imaging system are considered. The first one is the depth-variant blur due to aberrations induced by the refractive index variation in the optical system and the imaged specimen. The second difficulty is the noise due to the photon counting process. The goal of this thesis is to reduce these distortions in order to provide biologists with a better image quality. In the first part of this thesis, we study the approximation models of the depth-variant blur and choose an appropriate model for the inversion problem. In that model, the depth-variant point spread function (PSF) is approximated by a convex combination of a set of space-invariant PSFs. We then develop for that model two fast non-blind restoration methods by minimizing a regularized criterion, each of these methods is adapted to the type of noise present in images of confocal or wide field microscopy. In the second part, we address the problem of blind restoration and propose two methods where the depth-variant blur and the image are jointly estimated. In the first method, the PSF is estimated at each voxel in the considered volume in order to allow high degree of freedom on the PSF shape while in the second method, the shape of the PSF is constrained by a Gaussian function in order to reduce the number of unknown variables and the space of possible solutions. In both blind estimation methods, the effect of optical aberrations is not effectively estimated due to the lack of information. We thus improve these estimation methods by alternating some constraints in the frequency and spatial domains. Results on simulated and real data are shown.