<p dir="ltr">This thesis describes advancements in both chemical imaging and optical manipulation methodologies for their application in tandem monitoring and control of biochemical processes. We developed a fast acquisition multimodal nonlinear imaging platform based on pulse-picking to minimize photoperturbation to the sample during imaging. By frequency doubling the imaging source, through acousto-optic modulation and simple comparator circuitry, we developed a comprehensive platform that uses chemical specific signals generated during imaging to control the pixel location for laser activation for reaction control. This feedback loop allows for advanced decision logic on a pixel by pixel basis.</p>

<p dir="ltr">In this dissertation, efforts and innovations are made to advance subtle pattern mining, edge computing, and system efficiency optimization for biomedical applications, thereby advancing precision medicine big data.</p><p dir="ltr">Brain visual dynamics encode rich functional and biological patterns of the neural system, promising for applications like intention decoding, cognitive load quantization and neural disorder measurement. We here focus on the understanding of the brain visual dynamics for the Amyotrophic lateral sclerosis (ALS) population. We leverage a deep learning framework for automatic feature learning and classification, which can translate the eye Electrooculography (EOG) signal to meaningful words. We then build an edge computing platform on the smart phone, for learning, visualization, and decoded word demonstration, all in real-time. In a further study, we have leveraged deep transfer learning to boost EOG decoding effectiveness. More specifically, the model trained on basic eye movements is leveraged and treated as an additional feature extractor when classifying the signal to the meaningful word, resulting in higher accuracy.</p><p dir="ltr">Efforts are further made to decoding functional Near-Infrared Spectroscopy (fNIRS) signal, which encodes rich brain dynamics like the cognitive load. We have proposed a novel Multi-view Multi-channel Graph Neural Network (mmGNN). More specifically, we propose to mine the multi-channel fNIRS dynamics with a multi-stage GNN that can effectively extract the channel- specific patterns, propagate patterns among channels, and fuse patterns for high-level abstraction. Further, we boost the learning capability with multi-view learning to mine pertinent patterns in temporal, spectral, time-frequency, and statistical domains.</p><p dir="ltr">Massive-device systems, like wearable massive-sensor computers and Internet of Things (IoTs), are promising in the era of big data. The crucial challenge is about how to maximize the efficiency under coupling constraints like energy budget, computing, and communication. We propose a deep reinforcement learning framework, with a pattern booster and a learning adaptor. This framework has demonstrated optimally maximizes the energy utilization and computing efficiency on the local massive devices under a one-center fifteen-device circumstance.</p><p dir="ltr">Our research and findings are expected to greatly advance the intelligent, real-time, and efficient big data harnessing, leveraging deep learning, edge computing, and efficiency optimization.</p>

<p dir="ltr">Single-particle tracking (SPT) provides high-resolution spatial-temporal information on biomolecule dynamics. However, localization inaccuracies, limited track lengths, heterogeneous fluorescence backgrounds, and potential molecular motion blur pose significant challenges that hinder the accurate extraction of movement trajectories and their underlying motion behavior. The conventional SPT pipeline struggles to comprehensively address detection, localization, linkage, and parameter inference simultaneously, resulting in information loss during sequential processing. To overcome these challenges, we propose SPTnet, an end-to-end deep learning framework that leverages a transformer-based architecture to optimize trajectory and motion parameter estimations in parallel through a global loss. SPTnet bypasses traditional SPT processes, directly inferring molecular trajectories and motion parameters from fluorescence microscopy video frames with precision approaching the statistical information limit. Our results demonstrate that SPTnet outperforms conventional methods under commonly encountered but challenging conditions such as short trajectories, low signal-to-noise ratio (SNR), heterogeneous backgrounds, motion blur, and especially when molecules exhibit non-Brownian behaviors.</p><p dir="ltr">Besides SPT, we used single-molecule localization microscopy (SMLM) to study cytokinetic protein in fission yeast. During cytokinesis, myosin-II constricts the contractile ring that separates one cell into two daughter cells. The fission yeast cytokinetic contractile ring contains two types of myosin Ⅱ, Myo2 and Myp2. However, the precise ultrastructural arrangement of the two type Ⅱ myosins remains in question. We investigated the relative spatial arrangement of Myo2p and Myp2p within contractile ring using two-color super-resolution microscopy based on salvaged fluorescence imaging. Quantitative analysis of the nanoscale images should provide useful information for modeling contractile ring assembly and constriction.</p><p><br></p>

La tomographie de cohérence optique plein champ est une technique de microscopie permettant d’imager un plan d’intérêt en profondeur dans un milieu diffusant. Cette technique a été utilisée pour l’examen de pièces opératoires dans un but de diagnostic en cancérologie. L’utilisation de cette technique permettrait en effet de fournir un outil de diagnostic peropératoire rapide et fiable, évitant ainsi de nombreuses procédures de réopération. Ces réopérations peuvent survenir lorsque – lors du diagnostic final par analyse de coupes histologiques – le pathologiste décèle la présence de tissus cancéreux restant, non retirés au cours de l’opération.L’OCT plein champ a montré de bons résultats pour cette application. Néanmoins, cette technique ne fournit qu’un contraste morphologique des tissus, ne permettant pas d’utiliser des critères de qualification des pièces opératoires basées – par exemple – sur la morphologie ou la densité cellulaire.Nous avons développé une nouvelle modalité d’imagerie basée sur l’OCT plein champ permettant de révéler un contraste métabolique dans le tissu à une échelle subcellulaire. Ce contraste permet de révéler les cellules précédemment non distinguées en OCT plein champ. Nous avons également utilisé la mesure quantitative de cette modalité pour réaliser des outils d’aide au diagnostic utilisant des approches d’apprentissage par ordinateur. / Full filed optical coherence tomography is a microscopy imaging technique allowing to image a specific slice in a scattering medium, in depth. This technique has been used for the diagnosis of biopsy in cancerology. This technique could be an efficient and fast way to diagnose excised tissues during surgery. This would avoid numerous reoperations procedures. These reoperations are necessary when a pathologist suspects cancerous tissue to still be present in the patient, based on histological slide examination.FFOCT has shown promising results for that purpose. Nevertheless, this technique only gives a morphological contrast of tissues, which is not enough for applying some diagnostic criteria such as cell morphology or cell density.We developed a new imaging modality based on FFOCT allowing to reveal metabolic contrast in tissues at the subcellular scale. This contrast reveals cells previously indistinguishable with FFOCT. We also used this quantitative metric to propose tools to facilitate diagnosis, using machine learning approaches.

This dissertation presents a contribution to quantitative microwave imaging for breast tumor detection. The study made in the frame of a joint supervision Ph.D. thesis between University Paris-SUD 11 (France) and Mälardalen University (Sweden), has been conducted through two experimental microwave imaging setups, the existing 2.45 GHz planar camera (France) and the multi-frequency flexible robotic system, (Sweden), under development. In this context a 2D scalar flexible numerical tool based on a Newton-Kantorovich (NK) scheme, has been developed. Quantitative microwave imaging is a three dimensional vectorial nonlinear inverse scattering problem, where the complex permittivity of an object is reconstructed from the measured scattered field, produced by the object. The NK scheme is used in order to deal with the nonlinearity and the ill-posed nature of this problem. A TM polarization and a two dimensional medium configuration have been considered in order to avoid its vectorial aspect. The solution is found iteratively by minimizing the square norm of the error with respect to the scattered field data. Consequently, the convergence of such iterative process requires, at least two conditions. First, an efficient calibration of the experimental system has to be associated to the minimization of model errors. Second, the mean square difference of the scattered field introduced by the presence of the tumor has to be large enough, according to the sensitivity of the imaging system. The existing planar camera associated to a flexible 2D scalar NK code, are considered as an experimental platform for quantitative breast imaging. A preliminary numerical study shows that the multi-view planar system is quite efficient for realistic breast tumor phantoms, according to its characteristics (frequency, planar geometry and water as a coupling medium), as long as realistic noisy data are considered. Furthermore, a multi-incidence planar system, more appropriate in term of antenna-array arrangement, is proposed and its concept is numerically validated. On the other hand, an experimental work which includes a new fluid-mixture for the realization of a narrow band cylindrical breast phantom, a deep investigation in the calibration process and model error minimization, is presented. This conducts to the first quantitative reconstruction of a realistic breast phantom by using multi-view data from the planar camera. Next, both the qualitative and quantitative reconstruction of 3D inclusions into the cylindrical breast phantom, by using data from all the retina, are shown and discussed. Finally, the extended work towards the flexible robotic system is presented. / A dissertation prepared through an international convention for a joint supervision thesis with Université Paris-SUD 11, France / Microwaves in biomedicine

Η κατασκευή συστημάτων τομογραφίας του ανθρώπινου ιστού τα οποία θα χρησιμοποιούν το υπέρυθρο φάσμα ακτινοβολίας αποτελεί σημαντική προοπτική για τη δημιουργία νέων ιατρικών διαγνωστικών μεθόδων. Ένα από τα σημαντικότερα προβλήματα που πρέπει να επιλυθούν είναι η μικρή διεισδυτική ικανότητα και ο υψηλός βαθμός απορρόφησης και σκέδασης που παραμορφώνει ισχυρά την ακτινοβολία που διαδίδεται μέσα από τον ανθρώπινο ιστό. Στα πλαίσια της διδακτορικής διατριβής, μελετήθηκε το πρόβλημα του εντοπισμού της θέσης των αγγείων σε ψηφιακές φωτογραφίες του ανθρώπινου δακτύλου που έχουν ληφθεί στο υπέρυθρο φάσμα. Για τον σκοπό αυτό αναπτύχθηκε μεγάλος αριθμός πρωτότυπων μεθόδων κανονικοποίησης της φωτεινότητας της εικόνας, μη-γραμμικής ενίσχυσης της αντίθεσης, αφαίρεσης των γραμμών δακτυλικών αποτυπωμάτων, εντοπισμού του προτύπου ή δικτύου αγγείων και βελτίωσης του προτύπου των αγγείων χρησιμοποιώντας μεθόδους μαθηματικής μορφολογίας. Συνοπτικά στην παρούσα διδακτορική διατριβή προτάθηκαν και εξετάσθηκαν διαφορετικές πρωτότυπες μέθοδοι και αλγόριθμοι με επίβλεψη ή χωρίς επίβλεψη για την εξαγωγή του προτύπου αγγείων από υπέρυθρες εικόνες του ανθρώπινου δακτύλου καθώς και διαφορετικές πρωτότυπες μέθοδοι και αλγόριθμοι χωρίς επίβλεψη για την εξαγωγή του δικτύου αγγείων από αμφιβληστροειδικές εικόνες του ανθρώπινου οφθαλμού. Επίσης, η ερευνητική προσπάθεια επικεντρώθηκε στην βελτίωση των εικόνων που λαμβάνονται από το προτεινόμενο σύστημα απόκτησης εικόνων, γεγονός το οποίο οδήγησε στην ανάπτυξη πρωτότυπων μεθόδων προ-επεξεργασίας και τη μετέπειτα βελτίωση των αρχικών αποτελεσμάτων κατάτμησης που προκύπτουν από την εφαρμογή των μεθόδων ή αλγορίθμων κατάτμησης προτύπου αγγείων, γεγονός το οποίο οδήγησε στην ανάπτυξη πρωτότυπων μεθόδων μετά-επεξεργασίας. / The construction of tomographic systems of human tissue which use the infrared spectrum of radiation constitutes an important capability of making new medical diagnostic methods. One of the most crucial problems which must be resolved is the low penetrating ability and the high degree of absorption and scattering which strongly distort the radiation that pass through the human tissue. In this thesis, the problem of the extraction of finger vein pattern from infrared images of finger and the similar problem of retinal vessel tree segmentation were studied. Moreover, the problem of shading and non-uniform illumination correction was also studied in images which suffer from the above problems either due to imperfect set-up of the image acquisition system or due to the interaction between objects and illumination on the scene. In this thesis, existing algorithms were improved and novel algorithms were developed. Both vein pattern extraction algorithms and shading and non-uniform illumination correction algorithms were proposed. The proposed methods include novel preprocessing modules for intensity normalization, elimination of fingerprint lines, non linear contrast enhancement using spatial information, and shading and non uniform illumination correction. The vein pattern extraction was performed using ten novel methods that use structural classification methods, spatial derivatives information and fuzzy set theory. The effectiveness of the proposed methods and algorithms was evaluated both on real and artificial images distorted by different types of noise and different signal to noise ratios. The majority of the methods present satisfactory accuracy on the detection of vein network, something happens due to the successful collaboration between the preprocessing methods and the vein pattern extraction methods. In addition, the problem of improving the vein network extraction accuracy was successfully handled using advanced postprocessing methods based on binary mathematical morphology. Finally, in this thesis two novel methods for retinal vessel segmentation were proposed and evaluated. They also compared with the most important methods have already been presented in the literature and one of them achieved the best experimental results from all the unsupervised methods evaluated in the publicly available DRIVE database.

L’émergence des technologies de l’information et de la communication (TIC) au début des années 1990, notamment internet, a permis de produire facilement des données et de les diffuser au reste du monde. L’essor des bases de données, le développement des outils applicatifs et la réduction des coûts de stockage ont conduit à l’augmentation quasi exponentielle des quantités de données au sein de l’entreprise. Plus les données sont volumineuses, plus la quantité d’interrelations entre données augmente. Le grand nombre de corrélations (visibles ou cachées) entre données rend les données plus entrelacées et complexes. Les données sont aussi plus hétérogènes, car elles peuvent venir de plusieurs sources et exister dans de nombreux formats (texte, image, audio, vidéo, etc.) ou à différents degrés de structuration (structurées, semi-structurées, non-structurées). Les systèmes d’information des entreprises actuelles contiennent des données qui sont plus massives, complexes et hétérogènes. L’augmentation de la complexité, la globalisation et le travail collaboratif font qu’un projet industriel (conception de produit) demande la participation et la collaboration d’acteurs qui viennent de plusieurs domaines et de lieux de travail. Afin d’assurer la qualité des données, d’éviter les redondances et les dysfonctionnements des flux de données, tous les acteurs doivent travailler sur un référentiel commun partagé. Dans cet environnement de multi-utilisation de données, chaque utilisateur introduit son propre point de vue quand il ajoute de nouvelles données et informations techniques. Les données peuvent soit avoir des dénominations différentes, soit ne pas avoir des provenances vérifiables. Par conséquent, ces données sont difficilement interprétées et accessibles aux autres acteurs. Elles restent inexploitées ou non exploitées au maximum afin de pouvoir les partager et/ou les réutiliser. L’accès aux données (ou la recherche de données), par définition est le processus d’extraction des informations à partir d’une base de données en utilisant des requêtes, pour répondre à une question spécifique. L’extraction des informations est une fonction indispensable pour tout système d’information. Cependant, cette dernière n’est jamais facile car elle représente toujours un goulot majeur d’étranglement pour toutes les organisations (Soylu et al. 2013). Dans l’environnement de données complexes, hétérogènes et de multi-utilisation de données, fournir à tous les utilisateurs un accès facile et simple aux données devient plus difficile pour deux raisons : - Le manque de compétences techniques. Pour formuler informatiquement une requête complexe (les requêtes conjonctives), l’utilisateur doit connaitre la structuration de données, c’est-à-dire la façon dont les données sont organisées et stockées dans la base de données. Quand les données sont volumineuses et complexes, ce n’est pas facile d’avoir une compréhension approfondie sur toutes les dépendances et interrelations entre données, même pour les techniciens du système d’information. De plus, cette compréhension n’est pas forcément liée au savoir et savoir-faire du domaine et il est donc, très rare que les utilisateurs finaux possèdent les compétences suffisantes. - Différents points de vue des utilisateurs. Dans l’environnement de multi-utilisation de données, chaque utilisateur introduit son propre point de vue quand il ajoute des nouvelles données et informations techniques. Les données peuvent être nommées de manières très différentes et les provenances de données ne sont pas suffisamment fournies. / The emergence of Information and Comunication Technologies (ICT) in the early 1990s, especially the Internet, made it easy to produce data and disseminate it to the rest of the world. The strength of new Database Management System (DBMS) and the reduction of storage costs have led to an exponential increase of volume data within entreprise information system. The large number of correlations (visible or hidden) between data makes them more intertwined and complex. The data are also heterogeneous, as they can come from many sources and exist in many formats (text, image, audio, video, etc.) or at different levels of structuring (structured, semi-structured, unstructured). All companies now have to face with data sources that are more and more massive, complex and heterogeneous.technical information. The data may either have different denominations or may not have verifiable provenances. Consequently, these data are difficult to interpret and accessible by other actors. They remain unexploited or not maximally exploited for the purpose of sharing and reuse. Data access (or data querying), by definition, is the process of extracting information from a database using queries to answer a specific question. Extracting information is an indispensable function for any information system. However, the latter is never easy but it always represents a major bottleneck for all organizations (Soylu et al. 2013). In the environment of multiuse of complex and heterogeneous, providing all users with easy and simple access to data becomes more difficult for two reasons : - Lack of technical skills : In order to correctly formulate a query a user must know the structure of data, ie how the data is organized and stored in the database. When data is large and complex, it is not easy to have a thorough understanding of all the dependencies and interrelationships between data, even for information system technicians. Moreover, this understanding is not necessarily linked to the domain competences and it is therefore very rare that end users have sufficient theses such skills. - Different user perspectives : In the multi-use environment, each user introduces their own point of view when adding new data and technical information. Data can be namedin very different ways and data provenances are not sufficiently recorded. Consequently, they become difficultly interpretable and accessible by other actors since they do not have sufficient understanding of data semantics. The thesis work presented in this manuscript aims to improve the multi-use of complex and heterogeneous data by expert usiness actors by providing them with a semantic and visual access to the data. We find that, although the initial design of the databases has taken into account the logic of the domain (using the entity-association model for example), it is common practice to modify this design in order to adapt specific techniques needs. As a result, the final design is often a form that diverges from the original conceptual structure and there is a clear distinction between the technical knowledge needed to extract data and the knowledge that the expert actors have to interpret, process and produce data (Soylu et al. 2013). Based on bibliographical studies about data management tools, knowledge representation, visualization techniques and Semantic Web technologies (Berners-Lee et al. 2001), etc., in order to provide an easy data access to different expert actors, we propose to use a comprehensive and declarative representation of the data that is semantic, conceptual and integrates domain knowledge closeed to expert actors.

Cette thèse traite du couplage d'un tomographe optique par luminescence (LCT) et d'un tomographe par rayons X (XCT), en présence d'une contrainte sur la géométrie d'acquisition du XCT. La couverture angulaire du XCT est limitée à 90 degrés pour satisfaire des contraintes spatiales imposées par le LCT existant dans lequel le XCT doit être intégré. L'objectif est de dériver une information anatomique, à partir de l'image morphologique issue du XCT. Notre approche a consisté i) en l'implémentation d'un algorithme itératif régularisé pour la reconstruction tomographique à angle limité, ii) en la construction d'un atlas anatomique statistique de la souris et iii) en l'implémentation d'une chaîne automatique réalisant la segmentation des images XCT, l'attribution d'une signification anatomique aux éléments segmentés, le recalage de l'atlas statistique sur ces éléments et ainsi l'estimation des contours de certains tissus à faible contraste non identifiables en pratique dans une image XCT standard. / This thesis addresses the combination of an Optical Luminescence Tomograph (OLT) and X-ray Computerized Tomograph (XCT), dealing with geometrical constraints defined by the existing OLT system in which the XCT must be integrated. The result is an acquisition geometry of XCT with a 90 degrees angular range only. The aim is to derive an anatomical information from the morphological image obtained with the XCT. Our approach consisted i) in the implementation of a regularized iterative algorithm for the tomographic reconstruction with limited angle data, ii) in the construction of a statistical anatomical atlas of the mouse and iii) in the implementation of an automatic segmentation workflow performing the segmentation of XCT images, the labelling of the segmented elements, the registration of the statistical atlas on these elements and consequently the estimation of the outlines of low contrast tissues that can not be identified in practice in a standard XCT image.

Cette thèse a pour objectif l’étude d’un lien effectif potentiel entre la motilité cellulaire, la mécanique cellulaire, et l’activité biochimique de ces mêmes cellules. Ce couplage a été étudié dans divers systèmes biologiques, et aussi bien dans des cultures de cellules qu’à l’intérieur de tissus plus complexes. Notamment, nous avons particulièrement cherché à détecter un couplage électromécanique dans des neurones qui pourrait être impliqué dans la propagation du message nerveux.Pour ce faire, nous avons dû développer deux microscopes optiques à la sensibilité extrême. Ces microscopes se composent de deux parties principales. La première sert à détecter des mouvements axiaux plus petits que la longueur d’onde optique, soit en dessous de 100 nanomètres. La deuxième partie permet la détection d’un signal de fluorescence, offrant la possibilité de suivre l’évolution biochimique de la cellule. Avec ces deux microscopes multimodaux, il est donc possible de suivre de manière simultanée un contraste de motilité, un contraste mécanique, un contraste structurel et un contraste biochimique. Si l’un de ces systèmes est basé sur la tomographie de cohérence optique plein champ et permet de faire de telles mesures en 3-D et en profondeur dans les tissus biologiques, le second ne permet que des mesures dans des cultures de cellules, mais est bien plus robuste au bruit mécanique. Dans ce manuscrit, nous allons essentiellement décrire le développement de ces deux appareils, et préciser les contrastes auxquels ils sont sensibles spécifiquement.Nous développerons également deux des applications principales de ces microscopes que nous avons étudié dans le détail au cours de cette thèse. La première application développe l’intérêt d’un de nos microscopes pour la détection sans marquage des principaux composants cellulaires et structuraux de la cornée et de la rétine. La seconde application tend à détecter et à suivre des ondes électromécaniques dans des neurones de mammifères / This PhD project aims to explore the relationship that might exist between the dynamic motility and mechanical behavior of different biological systems and their biochemical activity. In particular,we were interested in detecting the electromechanical coupling that may happen in active neurons, and may assist in the propagation of the action potential. With this goal in mind, we have developed two highly sensitive optical microscopes that combine one modality that detects sub-wavelength axial displacements using optical phase imaging and another modality that uses a fluorescence path. Therefore, these multimodal microscopes can combine a motility, a mechanical,a structural and a biochemical contrast at the same time. One of this system is based ona multimodal combination of full-field optical coherence tomography (FF-OCT) and allows the observation of such contrast inside thick and scattering biological tissues. The other setup provides a higher displacement sensitivity, but is limited to measurements in cell cultures. In this manuscript, we mainly discuss the development of both systems and describe the various contrastst hey can reveal. Finally, we have largely used our systems to investigate diverse functions of the eye and to look for electromechanical waves in cell cultures. The thorough description of both biological applications is also provided in the manuscript

As dental caries is one of the most common diseases, the early and noninvasive detection of carious lesions plays an important role in public health care. Optical coherence tomography (OCT) with its ability of depth-resolved, high-resolution, noninvasive, fast imaging has been previously recognized as a promising tool in dentistry. Additionally, polarization sensitive imaging provides quantitative measures on the birefringent tissue properties and can be utilized for imaging dental tissue, especially enamel and dentin. By imaging three exemplary tooth samples ex vivo with proximal white spot, brown spot, and cavity, we show that the combination of polarization sensitive OCT and the degree of polarization uniformity (DOPU) algorithm is a promising approach for the detection of proximal carious lesions due to the depolarization contrast of demineralized tissue. Furthermore, we investigate different sizes of the DOPU evaluation kernel on the resulting contrast and conclude a suitable value for this application. We propose that DOPU provides an easy to interpret image representation and appropriate contrast for possible future screening applications in early caries diagnostics.