Pattern Recognition Software and Techniques for Biological Image Analysis

The increasing prevalence of automated image acquisition systems is enabling new types of microscopy experiments that generate large image datasets. However, there is a perceived lack of robust image analysis systems required to process these diverse datasets. Most automated image analysis systems are tailored for specific types of microscopy, contrast methods, probes, and even cell types. This imposes significant constraints on experimental design, limiting their application to the narrow set of imaging methods for which they were designed. One of the approaches to address these limitations is pattern recognition, which was originally developed for remote sensing, and is increasingly being applied to the biology domain. This approach relies on training a computer to recognize patterns in images rather than developing algorithms or tuning parameters for specific image processing tasks. The generality of this approach promises to enable data mining in extensive image repositories, and provide objective and quantitative imaging assays for routine use. Here, we provide a brief overview of the technologies behind pattern recognition and its use in computer vision for biological and biomedical imaging. We list available software tools that can be used by biologists and suggest practical experimental considerations to make the best use of pattern recognition techniques for imaging assays

From Birds to Drug-Resistant Cancer, a novel In situ Methodology to Explore Divergent Genome Evolution

Fluorescent hybridisatio nmethodologies have not changed in principles over the past 30 years, with the increase of computational sequencing technologies causing the replacement of in situ hybridisations. Fluorescence in situ hybridisation (FISH) is in need of a refresh to be a worthwhile tool in a modern day cytogenetic laboratory to overcome short comings of these new methods. The creation of the novel multilayer FISH protocol has effectively eliminated many negative aspects of classic FISH based experiments, such as a large reduction in cost and is no longer as limited by fluorophore availability. Here presented within this thesis is the creation of this methodology and application to a wide variety of cytogenetic hypothesises. Key species from the Galliform order were investigated in order to detect previously missed intrachromosomal rearrangements within their macrochromosomes, a premise formerly overlooked. Rearrangements were found within chromosomes of the galliforme species used such as E.chinensis which displays a intrachromosomal inversion on the p-arm of chromosome 2. Furthermore, the creation of an interphase state folding prediction tool has been used to assess the arrangement of macrochromosomes during cellular growth stages within G.gallus. Here it is noted that there are particular arrangements identified which are similar across chromosomes studied. The chicken lymphoma cell line DT40 is of great importance in B-cell receptor studies along with gene disruption experiments. Presented here is an updated karyotype for the cell line. Here shows contrasting and more in-depth evidence of aberrations to further develop our understanding of the genomic arrangement of this useful cell line. The level of tumour heterogeneity in a cancer is a diagnostic tool allowing clinicians to comment on therapeutic choices and prognosis of the disease. Found to be dominant in recurrent cancers, cytotoxic resistant tumour cell populations may indeed exist within initial primary tumours at low frequency to be positively selected during chemotherapy. Within a neuroblastoma cell line,and cyto-toxic resistant derivatives lines,there has been identified a level of genomic heterogeneity which may give clues towards the generation of drug resistance mechanisms

Multiscale image analysis of calcium dynamics in cardiac myocytes

Cardiac myocytes constitute a unique physiological system. They are the muscle cells that build up heart tissue and provide the force to pump blood by synchronously contracting at every beat. This contraction is regulated by calcium concentration, among other ions, which exhibits a very complex behaviour, rich in dynamical states at the molecular, cellular and tissue levels. Details of such dynamical patterns are closely related to the mechanisms responsible for cardiac function and also cardiac disease, which is the first cause of death in the modern world. The emerging field of translational cardiology focuses on the study of how such mechanisms connect and influence each other across spatial and temporal scales finally yielding to a certain clinical condition. In order to study such patterns, we benefit from the recent and very important advances in the field of experimental cell physiology. In particular, fluorescence microscopy allows us to observe the distribution of calcium in the cell with a spatial resolution below the micron and a frame rate around the millisecond, thus providing a very accurate monitoring of calcium fluxes in the cell. This thesis is the result of over five years' work on biological signal and digital image processing of cardiac cells. During this period of time the aim has been to develop computational techniques for extracting quantitative data of physiological relevance from microscopy images at different scales. The two main subjects covered in the thesis are image segmentation and classification methods applied to fluorescence microscopy imaging of cardiac myocytes. These methods are applied to a variety of problems involving different space and time scales such as the localisation of molecular receptors, the detection and characterisation of spontaneous calcium-release events and the propagation of calcium waves across a culture of cardiac cells. The experimental images and data have been provided by four internationally renowned collaborators in the field. It is thanks to them and their teams that this thesis has been possible. They are Dr. Leif Hove-Madsen from the Institut de Ciències Cardiovasculars de Catalunya in Barcelona, Prof. S. R. Wayne Chen from the Department of Physiology and Pharmacology in the Libin Cardiovascular Institute of Alberta, University of Calgary, Dr. Peter P. Jones from the Department of Physiology in the University of Otago, and Prof. Glen Tibbits from the Department of Biomedical Physiology & Kinesiology at the Simon Fraser University in Vancouver. The work belongs to the biomedical engineering discipline, focusing on the engineering perspective by applying physics and mathematics to solve biomedical problems. Specifically, we frame our contributions in the field of computational translational cardiology, attempting to connect molecular mechanisms in cardiac cells up to cardiac disease by developing signal and image-processing methods and machine-learning methods that are scalable through the different scales. This computational approach allows for a quantitative, robust and reproducible analysis of the experimental data and allows us to obtain results that otherwise would not be possible by means of traditional manual methods. The results of the thesis provide specific insight into different cell mechanisms that have a non-negligible impact at the clinical level. In particular, we gain a deeper knowledge of cell mechanisms related to cardiac arrhythmia, fibrillation phenomena, the emergence of alternans and anomalies in calcium handling due to cell ageing.Els cardiomiòcits constitueixen un sistema fisiològic únic. Són les cèl·lules muscular que formen el cor i proporcionen la força per bombar la sang fent una contracció a cada batec. La regulació d'aquesta contracció es fa mitjançant concentració de calci (entre d'altres ions) i presenta una dinàmica molt complexa tant a l'escala molecular, cel·lular i de teixit. Detalls d'aquesta dinàmica estan fortament relacionats amb la funció cardíaca i per sobre de tot amb patologies cardíaques. La disciplina emergent de la cardiologia translacional es centra en l'estudi de com aquests mecanismes es connecten i s'influencien entre sí a través de diferents escales temporals i espacials finalment donant lloc a condicions clíniques. Per estudiar aquests patrons ens beneficiem dels recents avenços en fisiologia i biologia cel·lular. En particular, la microscòpia de fluorescència ens permet observar la distribució de calci dins una cèl·lula amb una resolució espacial per sota de la micra i temporal per sota del mil·lisegon, permetent un monitoratge acurat dels fluxos de calci en la cèl·lula cardíaca. Aquesta tesi és el resultat de més de cinc anys de feina en processament de senyal i imatge de cardiomiòcits humans. Durant aquest període de temps l'objectiu principal ha estat desenvolupar tècniques computacionals per extraure dades d'imatges de microscòpia amb rellevància fisiològica. Els dos temes principals coberts a la tesi són segmentació d'imatges i classificadors, aplicats a imatges de microscòpia de fluorescència de cardiomiòcits. Els mètodes s'apliquen a diferents problemes involucrant diverses escales espacials i temporals, des de determinar la posició de receptors a l’escala molecular passant detectar i caracteritzar alliberament espontani de calci intracel·lular fins a la propagació d'ones de calci en un cultiu de cèl·lules cardíaques. Les dades experimentals han estat proporcionades per quatre col·laboradors de renom internacional. És gràcies a ells i els seus equips que aquesta tesi ha estat possible. Són el Dr. Leif Hove-Madsen de l'Institut de Ciències Cardiovasculars de Catalunya a Barcelona, el Dr. S.R. Wayne Chen del Department of Physiology and Pharmacology al Libin Cardiovascular Institute of Alberta, University of Calgary, el Dr. Peter P. Jones del Department of Physiology a la University of Otago, i el Dr. Glen Tibbits del Department of Biomedical Physiology & Kinesiology de la Simon Fraser University a Vancouver. El treball pertany a la disciplina de la enginyeria biomèdica, fent èmfasi a la perspectiva de l'enginyeria, aplicant física i matemàtiques per solucionar problemes de la biomedicina. Específicament, s'emmarca en la cardiologia translacional computacional, mirant de connectar mecanismes a l’escala molecular amb patologies cardíaques mitjançant tècniques de processament de dades i aprenentatge automàtic que són escalables a les diferents escales d’aplicació. Aquest enfocament computacional permet una anàlisi quantitatiu, robust i reproduïble de les dades experimentals i ens permet d'obtenir resultats que serien impossibles d'assolir mitjançant els tradicionals mètodes manuals. Els resultats que proporciona la tesi han permès aprofundir en l'enteniment de diferents mecanismes fisiològics amb impacte en l'àmbit clínic. Particularment hem permès d’assolir coneixements relacionats amb l'arítmia cardíaca, la fibril·lació, processos d'alternança i anomalies relacionades amb l’envelliment

Computing Network of Diseases and Pharmacological Entities through the Integration of Distributed Literature Mining and Ontology Mapping

The proliferation of -omics (such as, Genomics, Proteomics) and -ology (such as, System Biology, Cell Biology, Pharmacology) have spawned new frontiers of research in drug discovery and personalized medicine. A vast amount (21 million) of published research results are archived in the PubMed and are continually growing in size. To improve the accessibility and utility of such a large number of literatures, it is critical to develop a suit of semantic sensitive technology that is capable of discovering knowledge and can also infer possible new relationships based on statistical co-occurrences of meaningful terms or concepts. In this context, this thesis presents a unified framework to mine a large number of literatures through the integration of latent semantic analysis (LSA) and ontology mapping. In particular, a parameter optimized, robust, scalable, and distributed LSA (DiLSA) technique was designed and implemented on a carefully selected 7.4 million PubMed records related to pharmacology. The DiLSA model was integrated with MeSH to make the model effective and efficient for a specific domain. An optimized multi-gram dictionary was customized by mapping the MeSH to build the DiLSA model. A fully integrated web-based application, called PharmNet, was developed to bridge the gap between biological knowledge and clinical practices. Preliminary analysis using the PharmNet shows an improved performance over global LSA model. A limited expert evaluation was performed to validate the retrieved results and network with biological literatures. A thorough performance evaluation and validation of results is in progress

Image analysis for gene expression based phenotype characterization in yeast cells

  Image analysis of objects in the microscope scale requires accuracy so that measurements can be used to differentiate between groups of objects that are being studied. This thesis deals with measurements in yeast biology that are obtained through microscope images. We study the algorithms and workflow of image analysis of yeast cells in order to understand and improve the measurement accuracy. The Saccharomyces cerevisiae cell is widely used as a model organism in the life sciences. It is essential to study the gene and protein behaviour within these cells, and consequently making it possible to find treatment and solutions for genetic and hereditary diseases. This is possible since many processes that occurs at the molecular level in this organism are similar to those in human cells. In the research group Imaging and Bioinformatics, we have developed a framework for analysis of yeast cells. This framework is intended to serve as a support for research in yeast biology. The framework is integrated in one application and presented via a GUI. The application integrates modules and algorithms including segmentation, measurement, analysis and visualization.  Erasmus-Mundus, Raymond-Sackler, LSBSLIACS - OU

Development and application of deep learning and spatial statistics within 3D bone marrow imaging

The bone marrow is a highly specialised organ, responsible for the formation of blood cells. Despite 50 years of research, the spatial organisation of the bone marrow remains an area full of controversy and contradiction. One reason for this is that imaging of bone marrow tissue is notoriously difficult. Secondly, efficient methodologies to fully extract and analyse large datasets remain the Achilles heels of imaging-based research. In this thesis I present a pipeline for generating 3D bone marrow images followed by the large-scale data extraction and spatial statistical analysis of the resulting data. Using these techniques, in the context of 3D imaging, I am able to identify and classify the location of hundreds of thousands of cells within various bone marrow samples. I then introduce a series of statistical techniques tailored to work with spatial data, resulting in a 3D statistical map of the tissue from which multi-cellular interactions can be clearly understood. As an illustration of the power of this new approach, I apply this pipeline to diseased samples of bone marrow with a particular focus on leukaemia and its interactions with CD8+ T cells. In so doing I show that this novel pipeline can be used to unravel complex multi-cellular interactions and assist researchers in understanding the processes taking place within the bone marrow.Open Acces

How microplastics and adsorbed pollutants affect zebrafish development?

A presença de microplásticos no ecossistema aquático é, nos dias de hoje, uma realidade extremamente preocupante que acarreta sérios riscos para o meio ambiente e para a saúde pública. A capacidade dos microplásticos de adsorverem poluentes orgânicos, como é o caso do benzo[α]pireno (BaP), levanta preocupações adicionais, pois cria uma nova rota de entrada de compostos tóxicos na cadeia alimentar. No entanto, o conhecimento atual sobre o impacto dos microplásticos, inalterados e/ou contaminados, nos organismos aquáticos é ainda insuficiente e requer estudos adicionais. O trabalho desenvolvido no âmbito desta tese pretende assim fornecer novos dados sobre os efeitos biológicos dos microplásticos utilizando como modelo o peixe-zebra (Danio rerio). Pequenos teleósteos, como é o caso do peixe-zebra, oferecem vantagens significativas relativamente aos modelos animais clássicos e são atualmente utilizados como organismos de primeira linha para avaliar os riscos ambientais associados aos compostos tóxicos presentes nos meios aquáticos. Estudos toxicológicos requerem o uso de materiais inertes e condições controladas, todavia, nenhum dos sistemas atualmente comercializados é adequado para avaliar o efeito tóxico dos microplásticos. Estes sistemas contêm componentes feitos de polímeros plásticos que podem libertar partículas plásticas micrométricas, lixiviar os constituintes químicos ou adsorver os compostos químicos em estudo. O sistema de aquários autônomo ZEB316 foi desenvolvido no âmbito deste trabalho com o objetivo de suprimir esta necessidade e de facultar uma solução económica e fácil de implementar que permita a realização de estudos toxicológicos de última geração. Este sistema é construído com materiais inertes e resistentes à corrosão e proporciona boas condições de alojamento através de um sistema eficiente de recirculação e filtragem da água. A avaliação dos parâmetros da água e do desempenho do crescimento dos peixes mostrou que o sistema ZEB316 oferece condições de alojamento comparáveis à dos sistemas comercialmente disponíveis. A maioria dos resultados obtidos no âmbito desta dissertação provêm da análise de imagens de microscopia de campo claro e/ou fluorescência. Embora o uso de imagens de microscopia seja comum na maioria dos laboratórios e permita obter uma quantidade considerável de informação, a análise destas imagens é geralmente um processo moroso, em parte devido à falta de ferramentas automáticas/semiautomáticas dedicadas que permitam a sua análise. Nesse sentido, desenvolvemos diversas macros para o software ImageJ, com o objetivo de reduzir o erro associado à análise pelo usuário, aumentando assim a reprodutibilidade dos dados e a padronização das metodologias experimentais. Uma vez que o foco deste trabalho está centrado no estudo da osteotoxicidade, é de salientar o desenvolvimento de um conjunto de macros específicas para esse fim e denominadas ZFBONE. Este conjunto de ferramentas permite aos usuários avaliar, a partir de imagens 2D, parâmetros morfométricos de várias estruturas ósseas (por exemplo, opérculo, raios e escamas da barbatana caudal), mas também a extensão e a intensidade das colorações específicas do osso. Além disso, outras macros foram desenvolvidas para outros fins, por exemplo, para analisar os vários parâmetros morfométricos relativos aos embriões de peixe ou para avaliar cortes histológicos. Uma vez desenvolvidos os meios e técnicas necessários para a execução dos ensaios toxicológicos, e subsequente análise dos resultados, procedeu-se à realização das várias experiências que visam compreender efeito biológico dos microplásticos e contaminates no peixe-zebra. Assim, larvas de peixe-zebra foram produzidas e mantidas no sistema previamente descrito, ZEB316, e expostas cronicamente, durante o seu desenvolvimento, a partículas de polietileno de 20- 27 μm, inalteradas (MP) ou contaminadas com benzo[α]pireno (MP-BaP). Estas partículas foram adicionadas à dieta dos peixes através de uma suplementação a 1% m/m. Apesar de não se ter registado qualquer alteração ao nível dos parâmetros morfológicos aos 30 dias pós-fertilização (dpf), a presença de MP e MP-BaP acabou por ter um efeito negativo no crescimento dos espécimes aos 90 e 360 dpf. A fecundidade relativa, a morfologia do ovo/embrião e a área do vitelo também sofreram um impacto negativo em peixes-zebra alimentados com MP-BaP. No que respeita ao estado geral do esqueleto, os peixes expostos a dietas experimentais contendo MP e MP-BaP sofreram um aumento significativo na incidência de deformações esqueléticas aos 30 dpf quando comparados com peixes alimentados com a dieta controlo, bem como um desenvolvimento anómalo da barbatana caudal e escamas, e uma diminuição da qualidade do osso aos 90 dpf. Um comprometimento da formação óssea intergeracional foi também observado na prole de espécimes expostos a MP ou MP-BaP, que se refletiu numa redução do osso opercular dos descendentes aos 6 dpf. Além de um claro efeito no desenvolvimento ósseo, a análise histológica do intestino revelou ainda um número reduzido de células caliciformes em peixes alimentados com dieta MP-BaP, um claro sinal de inflamação intestinal. Finalmente, a exposição das larvas a MP-BaP levou a um aumento da expressão de genes associados à via de resposta do BaP, ao mesmo tempo que impactou negativamente na expressão de genes envolvidos no estresse oxidativo. Os resultados obtidos indicaram um maior comprometimento do desenvolvimento ósseo no peixe-zebra quando sujeito a uma dieta contendo microplásticos contaminados com BaP (MP-BaP), por comparação com a dieta contendo microplásticos não contaminados (MP). Outros autores demostraram também que a presença de BaP afeta a formação das vértebras e o desenvolvimento generalizado do esqueleto, no entanto os mecanismos envolvidos nestes fenómenos permanecem pouco estudados. Desta forma, realizámos ensaios adicionais in vivo com o objetivo de avaliar os efeitos osteotóxicos do BaP durante o desenvolvimento e regeneração óssea em peixe-zebra. A exposição aguda de larvas de peixe-zebra entre os 3 e os 6 dpf ao BaP levou a uma redução do tamanho do osso opercular e uma diminuição quantitativa de células positivas para osteocalcina, indicando um efeito composto na maturação dos osteoblastos. Por sua vez, quando se trata de uma exposição crônica das larvas de peixe-zebra ao BaP, entre os 3 e os 30 dpf, verificou-se que o desenvolvimento do esqueleto axial é afetado, aumentando a incidência e gravidade das deformações esqueléticas. Em peixes jovens adultos, observou-se ainda que a exposição ao BaP afetou não só a mineralização dos raios da barbatana caudal e escamas recém-formados, como prejudicou também o seu padrão morfológico, fenómenos que têm por base uma remodelação óssea desequilibrada. Relativamente às análises de expressão genética de vários marcadores verificou-se que o BaP induziu a ativação das vias xenobióticas e metabólicas e impactou negativamente na formação e organização da matriz extracelular. Curiosamente, a exposição ao BaP regulou positivamente os marcadores de inflamação nas larvas e aumentou o recrutamento de neutrófilos. Uma interação direta entre neutrófilos e a matriz extracelular óssea, ou células responsáveis pela formação do osso, foi observada in vivo, o que sugere um papel dos neutrófilos nos mecanismos subjacentes à osteotoxicidade do BaP. Globalmente, os resultados obtidos no âmbito deste trabalho sugerem que a exposição crónica a microplásticos inalterados e/ou contaminados não prejudica apenas o crescimento dos peixes, mas também o seu desempenho a nível reprodutivo, saúde geral do seu esqueleto, e compromete a descendência por meio de efeitos intergeracionais. Além disso, este trabalho fornece novos dados sobre os principais mecanismos celulares e moleculares envolvidos na osteotoxicidade do BaP e aborda o possível papel dos neutrófilos na redução da resposta óssea inflamatória.The presence of microplastics in the aquatic ecosystem represents a major issue for the environment and human health. The capacity of organic pollutants such as benzo[α]pyrene (BaP) to adsorb onto microplastic particles raises additional concerns, as it creates a new route for toxic compounds to enter the food web. Current knowledge on the impact of pristine and/or contaminated microplastics on aquatic organisms remains insufficient, and this work aims at providing new insights by evaluating their biological effects in zebrafish (Danio rerio). The ZEB316, a standalone housing system built with inert materials, and a comprehensive set of ImageJ semi-automatic tools were first developed and optimized to perform state-of-the-art toxicological studies and obtain meaningful data from morphometric analysis of brightfield/ fluorescence images. Zebrafish larvae were exposed throughout their development to polyethylene microplastics, pristine or spiked with BaP, supplemented in the fish diet. While exposure up to 30 days post-fertilization only increased the incidence of skeletal deformities, long-term exposure to pristine/contaminated microplastics not only jeopardized fish growth, reproduction performance, and skeletal health, but it also caused an intergenerational effect. To further study the mechanisms underlying BaP osteotoxicity, several bone-related in vivo assays were used to evaluate the effects of waterborne exposure to BaP during bone development and regeneration. BaP inhibited osteoblast maturation and ECM mineralization and stimulated osteoclast activity, thus affecting bone remodeling. Transgenic and transcriptomic approaches suggested that besides the activation of xenobiotic and metabolic pathways, which may negatively impact extracellular matrix formation and organization, BaP activates inflammatory mechanisms that recruit neutrophils, which affect both osteoblast and osteoclast activity, possibly through a direct interaction of the neutrophils with the bone matrix. This work provides novel data on the effects of microplastics exposure during zebrafish development, in particular its osteotoxic effects, and gives new insights into the cellular and molecular players involved in BaP osteotoxicity.Marco Tarasco was supported by the Portuguese Foundation for Science and Technology (FCT) through the PhD grant SFRH/BD/128634/2017 and COVID/BD/151848/2021 and by NEUBIAS-COST STSM program as part of action CA15124. This work was funded by FCT through projects UID/Multi/04326/2019, UID/00350/2020, UIDB/04326/2020, UID/MAR/00350/2013 and from the operational programs MAR2020 and COMPETE 2020 through projects OSTEOMAR MAR-02.01.01-FEAMP-0057 and EMBRC.PT ALG-01-0145-FEDER-022121

Interactive Learning for the Analysis of Biomedical and Industrial Imagery

In der vorliegenden Dissertation werden Methoden des überwachten Lernens untersucht und auf die Analyse und die Segmentierung digitaler Bilddaten angewendet, die aus diversen Forschungsgebieten stammen. Die Segmentierung und die Klassifikation spielen eine wichtige Rolle in der biomedizinischen und industriellen Bildverarbeitung, häufig basiert darauf weitere Erkennung und Quantifikation. Viele problemspezifische Ansätze existieren für die unterschiedlichsten Fragestellungen und nutzen meist spezifisches Vorwissen aus den jeweiligen Bilddaten aus. In dieser Arbeit wird ein überwachtes Lernverfahren vorgestellt, das mehrere Objekte und deren Klassen gleichzeitig segmentieren und unterscheiden kann. Die Methode ist generell genug um einen wichtigen Bereich von Anwendungen abzudecken, für deren Lösung lokale Merkmale eine Rolle spielen. Segmentierungsergebnisse dieses Ansatzes werden auf verschiedenen Datensätzen mit unterschiedlichen Problemstellungen gezeigt. Die Resultate unterstreichen die Anwendbarkeit der Lernmethode für viele biomedizinische und industrielle Anwendungen, ohne dass explizite Kenntnisse der Bildverarbeitung und Programmierung vorausgesetzt werden müssen. Der Ansatz basiert auf generellen Merkmalsklassen, die es erlauben lokal Strukturen wie Farbe, Textur und Kanten zu beschreiben. Zu diesem Zweck wurde eine interaktive Software implementiert, welche, für gewöhnliche Bildgrößen, in Echtzeit arbeitet und es somit einem Domänenexperten erlaubt Segmentierungs- und Klassifikationsaufgaben interaktiv zu bearbeiten. Dafür sind keine Kenntnisse in der Bildverarbeitung nötig, da sich die Benutzerinteraktion auf intuitives Markieren mit einem Pinselwerkzeug beschränkt. Das interaktiv trainierte System kann dann ohne weitere Benutzerinteraktion auf viele neue Bilder angewendet werden. Der Ansatz ist auf Segmentierungsprobleme beschränkt, für deren Lösung lokale diskriminative Merkmale ausreichen. Innerhalb dieser Einschränkung zeigt der Algorithmus jedoch erstaunlich gute Resultate, die in einer applikationsspezifischen Prozedur weiter verbessert werden können. Das Verfahren unterstützt bis zu vierdimensionale, multispektrale Bilddaten in vereinheitlichter Weise. Um die Anwendbar- und Übertragbarkeit der Methode weiter zu illustrieren wurden mehrere echte Anwendungsfälle, kommend aus verschiedenen bildgebenden Bereichen, untersucht. Darunter sind u. A. die Segmentierung von Tumorgewebe, aufgenommen mittelsWeitfeldmikroskopie, die Quantifikation von Zellwanderungen in konfokalmikroskopischen Aufnahmen für die Untersuchung der adulten Neurogenese, die Segmentierung von Blutgefäßen in der Retina des Auges, das Verfolgen von Kupferdrähten in einer Anwendung zur Produktauthentifikation und die Qualitätskontrolle von Mikroskopiebildern im Kontext von Hochdurchsatz-Experimenten. Desweiteren wurde eine neue Klassifikationsmethode basierend auf globalen Frequenzschätzungen für die Prozesskontrolle des Papieranlegers an Druckmaschinen entwickelt

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

This work was supported by EMBL funds and by by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project number 240245660 – SFB 1129 (project Z2).In recent years, Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) has emerged as a flexible method that enables semi-automated volume ultrastructural imaging. We present a toolset for adherent cells that enables tracking and finding cells, previously identified in light microscopy (LM), in the FIB-SEM, along with the automatic acquisition of high-resolution volume datasets. We detect the underlying grid pattern in both modalities (LM and EM), to identify common reference points. A combination of computer vision techniques enables complete automation of the workflow. This includes setting the coincidence point of both ion and electron beams, automated evaluation of the image quality and constantly tracking the sample position with the microscope’s field of view reducing or even eliminating operator supervision. We show the ability to target the regions of interest in EM within 5 µm accuracy while iterating between different targets and implementing unattended data acquisition. Our results demonstrate that executing volume acquisition in multiple locations autonomously is possible in EM.Publisher PDFPeer reviewe

New algorithms for the analysis of live-cell images acquired in phase contrast microscopy

La détection et la caractérisation automatisée des cellules constituent un enjeu important dans de nombreux domaines de recherche tels que la cicatrisation, le développement de l'embryon et des cellules souches, l’immunologie, l’oncologie, l'ingénierie tissulaire et la découverte de nouveaux médicaments. Étudier le comportement cellulaire in vitro par imagerie des cellules vivantes et par le criblage à haut débit implique des milliers d'images et de vastes quantités de données. Des outils d'analyse automatisés reposant sur la vision numérique et les méthodes non-intrusives telles que la microscopie à contraste de phase (PCM) sont nécessaires. Comme les images PCM sont difficiles à analyser en raison du halo lumineux entourant les cellules et de la difficulté à distinguer les cellules individuelles, le but de ce projet était de développer des algorithmes de traitement d'image PCM dans Matlab® afin d’en tirer de l’information reliée à la morphologie cellulaire de manière automatisée. Pour développer ces algorithmes, des séries d’images de myoblastes acquises en PCM ont été générées, en faisant croître les cellules dans un milieu avec sérum bovin (SSM) ou dans un milieu sans sérum (SFM) sur plusieurs passages. La surface recouverte par les cellules a été estimée en utilisant un filtre de plage de valeurs, un seuil et une taille minimale de coupe afin d'examiner la cinétique de croissance cellulaire. Les résultats ont montré que les cellules avaient des taux de croissance similaires pour les deux milieux de culture, mais que celui-ci diminue de façon linéaire avec le nombre de passages. La méthode de transformée par ondelette continue combinée à l’analyse d'image multivariée (UWT-MIA) a été élaborée afin d’estimer la distribution de caractéristiques morphologiques des cellules (axe majeur, axe mineur, orientation et rondeur). Une analyse multivariée réalisée sur l’ensemble de la base de données (environ 1 million d’images PCM) a montré d'une manière quantitative que les myoblastes cultivés dans le milieu SFM étaient plus allongés et plus petits que ceux cultivés dans le milieu SSM. Les algorithmes développés grâce à ce projet pourraient être utilisés sur d'autres phénotypes cellulaires pour des applications de criblage à haut débit et de contrôle de cultures cellulaires.Automated cell detection and characterization is important in many research fields such as wound healing, embryo development, immune system studies, cancer research, parasite spreading, tissue engineering, stem cell research and drug research and testing. Studying in vitro cellular behavior via live-cell imaging and high-throughput screening involves thousands of images and vast amounts of data, and automated analysis tools relying on machine vision methods and non-intrusive methods such as phase contrast microscopy (PCM) are a necessity. However, there are still some challenges to overcome, since PCM images are difficult to analyze because of the bright halo surrounding the cells and blurry cell-cell boundaries when they are touching. The goal of this project was to develop image processing algorithms to analyze PCM images in an automated fashion, capable of processing large datasets of images to extract information related to cellular viability and morphology. To develop these algorithms, a large dataset of myoblasts images acquired in live-cell imaging (in PCM) was created, growing the cells in either a serum-supplemented (SSM) or a serum-free (SFM) medium over several passages. As a result, algorithms capable of computing the cell-covered surface and cellular morphological features were programmed in Matlab®. The cell-covered surface was estimated using a range filter, a threshold and a minimum cut size in order to look at the cellular growth kinetics. Results showed that the cells were growing at similar paces for both media, but their growth rate was decreasing linearly with passage number. The undecimated wavelet transform multivariate image analysis (UWT-MIA) method was developed, and was used to estimate cellular morphological features distributions (major axis, minor axis, orientation and roundness distributions) on a very large PCM image dataset using the Gabor continuous wavelet transform. Multivariate data analysis performed on the whole database (around 1 million PCM images) showed in a quantitative manner that myoblasts grown in SFM were more elongated and smaller than cells grown in SSM. The algorithms developed through this project could be used in the future on other cellular phenotypes for high-throughput screening and cell culture control applications