Curvilinear Structure Enhancement in Biomedical Images

Curvilinear structures can appear in many different areas and at a variety of scales. They can be axons and dendrites in the brain, blood vessels in the fundus, streets, rivers or fractures in buildings, and others. So, it is essential to study curvilinear structures in many fields such as neuroscience, biology, and cartography regarding image processing. Image processing is an important field for the help to aid in biomedical imaging especially the diagnosing the disease. Image enhancement is the early step of image analysis. In this thesis, I focus on the research, development, implementation, and validation of 2D and 3D curvilinear structure enhancement methods, recently established. The proposed methods are based on phase congruency, mathematical morphology, and tensor representation concepts. First, I have introduced a 3D contrast independent phase congruency-based enhancement approach. The obtained results demonstrate the proposed approach is robust against the contrast variations in 3D biomedical images. Second, I have proposed a new mathematical morphology-based approach called the bowler-hat transform. In this approach, I have combined the mathematical morphology with a local tensor representation of curvilinear structures in images. The bowler-hat transform is shown to give better results than comparison methods on challenging data such as retinal/fundus images. The bowler-hat transform is shown to give better results than comparison methods on challenging data such as retinal/fundus images. Especially the proposed method is quite successful while enhancing of curvilinear structures at junctions. Finally, I have extended the bowler-hat approach to the 3D version to prove the applicability, reliability, and ability of it in 3D

Mathematical Morphology for Quantification in Biological & Medical Image Analysis

Mathematical morphology is an established field of image processing first introduced as an application of set and lattice theories. Originally used to characterise particle distributions, mathematical morphology has gone on to be a core tool required for such important analysis methods as skeletonisation and the watershed transform. In this thesis, I introduce a selection of new image analysis techniques based on mathematical morphology. Utilising assumptions of shape, I propose a new approach for the enhancement of vessel-like objects in images: the bowler-hat transform. Built upon morphological operations, this approach is successful at challenges such as junctions and robust against noise. The bowler-hat transform is shown to give better results than competitor methods on challenging data such as retinal/fundus imagery. Building further on morphological operations, I introduce two novel methods for particle and blob detection. The first of which is developed in the context of colocalisation, a standard biological assay, and the second, which is based on Hilbert-Edge Detection And Ranging (HEDAR), with regard to nuclei detection and counting in fluorescent microscopy. These methods are shown to produce accurate and informative results for sub-pixel and supra-pixel object counting in complex and noisy biological scenarios. I propose a new approach for the automated extraction and measurement of object thickness for intricate and complicated vessels, such as brain vascular in medical images. This pipeline depends on two key technologies: semi-automated segmentation by advanced level-set methods and automatic thickness calculation based on morphological operations. This approach is validated and results demonstrating the broad range of challenges posed by these images and the possible limitations of this pipeline are shown. This thesis represents a significant contribution to the field of image processing using mathematical morphology and the methods within are transferable to a range of complex challenges present across biomedical image analysis

Peningkatan Kualitas Citra Pada Pembuluh Darah Retina Menggunakan CLAHE dan Adaptive Threshold

Peningkatan kualitas citra pada pembuluh darah retina merupakan langkah awal dalam pengolahan citra. Kualitas citra ditingkatkan bertujuan mempermudah proses segmentasi dan proses selanjutnya. Oleh karena itu pada penelitian ini kami menggunakan metode Clahe + He dengan dataset STARE untuk meningkatkan kualitas citra pada pembuluh darah retina. Dari metode yang kami gunakan di dapat hasil akurasi

Tracing biofilaments from images : analysis of existing methods to quantify the three-dimensional growth of filamentous fungi on solid substrates

Orientador: Prof. Dr. David Alexander MitchellCoorientadora: Prof. Dr. Maura Harumi Sugai-GuériosDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Química. Defesa : Curitiba, 29/05/2018Inclui referências: p.100-113Área de concentração: Engenharia QuímicaResumo: Análise de imagens de biofilamentos tem se tornado uma parte importante na pesquisa em biologia e biotecnologia, pois ela não só elucida a morfologia destas estruturas, mas também fornece ideias sobre o desenvolvimento destas estruturas. Além disso, a morfologia pode ser correlacionada com outras variáveis. Por exemplo, análise de imagem de fungos filamentosos permite correlacionar produtividade de enzimas com diferentes morfologias. Há um interesse em compreender como o micélio de um fungo filamentoso se desevolve ao crescer em substratos sólidos. Para estudar isso, foram obtidas imagens 3D do fungo em crescimento em diversos tempos, objetivando computar dados da morfologia e dinâmica de crescimento: velocidades de extensão da colônia e de pontas, número e posição de ramificações e pontas, comprimentos de segmentos, entre outros dados. Porém, antes de computar estes dados, foi feita uma análise da literatura de métodos de traçado de biofilamentos. A análise foi realizada para facilitar a compreensão do vasto número de métodos disponíveis, desde componentes individuais (e.g. técnicas de realçe de filamentos) a workflows completas de traçado de biofilamentos. Também há muitas opções de implementações de software. Na análise, foram incluídas 87 publicações envolvendo workflows de traçado de filamentos ou componentes. Para a análise, criou-se uma classificação (10 classes, que incluem interação com o usuário, abordagem teórica, técnica de imageamento, entre outras classes e 120 sub-classes) para apoiar a análise com o uso de conceitos de teoria de grafos. A metodologia proposta poderá ser utilizada no futuro com ferramentas de semântica web e uma base de dados e permitirá analisar um número maior de dados. Desta análise, identificaram-se os métodos mais comuns de melhoramento de imagem (Realçe de filamentos, 44.9%, suavização, 16.3% e Subtração de background 14.3%) e as tendências em abordagens teóricas (e.g. abordagens baseadas em grafos juntas à algoritmos de aprendizado de máquina, realçe de filamentos como o gradient vector flow seguidos de abordagem Levei-set fast-marching). Após a análise da literatura, foram selecionados os métodos de melhoramento mais comuns e avaliados segundo seu impacto na qualidade da imagem. Os testes foram realizados em duas amostras de imagem (experimentos do crescimento de Aspergillus niger de microscopia confocal de varredura a laser) através de um planejamento fatorial completo e análise do índice de similaridade estrutural, SSIM, e razão sinal-ruído, SNR. Resultados mostraram que o algoritmo rolling bali de subtração de background com raio 20 pixels teve o maior efeito positivo em SSIM e SNR no geral. Então, ao utilizar as imagens melhoradas como entrada, foram testados 5 métodos de traçado de filamentos (APP, APP2, NeuTube, NeuronStudio e NeuroGPS-Tree). Os resultados do traçado foram avaliados qualitativamente: O método NeuTube mostrou os resultados visualmente mais acurados. Definiu-se então o método e foram traçadas as imagens completas 3D e no tempo e obtivemos parâmetros morfométricos e da dinâmica do crescimento do fungo (perfis de biomassa e comprimentos totais, por exemplo). Embora se observe que o uso de traçado de filamentos é promisor para obter mais dados do crescimento de fungos filamentosos, discutiu-se a necessidade de aprimorar as técnicas de preparo de amostra e das configurações na aquisição das imagens, de maneira a aumentar a qualidade final das imagens e fornecer resultados mais confiáveis e concretos após o traçado para então tirar conclusões dos dados. Palavras-chave: fungos filamentosos, filamentos biológicos, análise de imagem, traçado de filamentos, melhoramento de imagem.Abstract: Image analysis of biofilaments is becoming an important part of research on biology and biotechnology because it does not only elucidates the morphology of such structures but also gives insights into their development. Additionally, the morphology can be correlated with other variables. For example, image analysis of filamentous fungi allows the correlation of enzyme productivity with different morphologies. We are interested in understanding how the mycelium of a filamentous fungus develops during growth on solid substrates. In order to study that, time-lapsed 3D images of the fungus during growth were obtained, with the intention of computing growth dynamics and morphometric data: colony and tip extension rates, number and positions of branches and tips, segment lengths, among others. However, prior to computing this data, we analysed the literature of biofilament tracing methods. The analysis was done to facilitate the understanding of the vast number of methods available, from single components (e.g. filament enhancement techniques, and specialized model-based approaches) to complete biofilament tracing workflows. There were also many software implementations options. The analysis comprised 87 publications proposing complete biofilament tracing workflows or workflow components. For the analysis, we created a classification methodology (10 main classes, including user interaction, theoretical approach, imaging technique, among other classes and 120 sub-classes) and analysed the publications using graph theory concepts. The proposed methodology could be used in the future with semantic web tools and crowd-sourced web-based databases, allowing the analysis of greater number of data. Out of this analysis, we identified the most common image enhancement methods (Filament enhancement 44.9%, smoothing 16.3%, background subtraction 14.3%) and the theoretical approach trends for biofilament tracing (e.g. graph-based approaches coupled with machine learning algorithms, image enhancement such as gradient vector flows followed by model-based fast marching approach). Following the literature analysis, we selected the most common image enhancement methods to be used prior to biofilament tracing and evaluated their impact on image quality. The tests were done on two sample images (experiments of the growth of Aspergillus niger on two different carbon sources obtained by confocal laser scanning microscopy) through a full factorial design of experiments and analysis of the structural similarity index, SSIM and signal-to-noise ratio, SNR. Results show that background subtraction (Rolling-ball algorithm, 20 pixels radius) had the most positive effect on SSIM and SNR. Then, using the enhanced images as input, we tested 5 different biofilament tracing methods (APP1, APP2, NeuTube, NeuronStudio and NeuroGPS-Tree). We evaluated the tracing results visually and qualitatively: NeuTube was the method with the most visually accurate results. After choosing NeuTube as the best method, we applied it to our complete 3D time-lapsed images and computed some growth dynamics and morphmetric parameters (e.g. biomass profiles, segment and total lengths). Although we indicate that biofilament tracing methods are a promising approach to obtain more data on the growth of the filamentous fungi, we discuss the need to improve the sample preparation techniques and image acquisition set-up in order to increase the quality of the images so the tracing results provide more reliable and concrete results to draw conclusions. Keywords: filamentous fungi, biological filaments, image analysis, filament tracing, image enhancement

The multiscale bowler-hat transform for blood vessel enhancement in retinal images

Enhancement, followed by segmentation, quantification and modelling of blood vessels in retinal images plays an essential role in computer-aided retinopathy diagnosis. In this paper, we introduce the bowler-hat transform method a new approach based on mathematical morphology for vessel enhancement. The proposed method combines different structuring elements to detect innate features of vessel-like structures. We evaluate the proposed method qualitatively and quantitatively and compare it with the state-of-the-art methods using both synthetic and real datasets. Our results establish that the proposed method achieves high-quality vessel-like structure enhancement in both synthetic examples and clinically relevant retinal images. The bowler-hat transform is shown to be able to detect fine vessels while still remaining robust at junctions

Chapter 34 - Biocompatibility of nanocellulose: Emerging biomedical applications

Nanocellulose already proved to be a highly relevant material for biomedical applications, ensued by its outstanding mechanical properties and, more importantly, its biocompatibility. Nevertheless, despite their previous intensive research, a notable number of emerging applications are still being developed. Interestingly, this drive is not solely based on the nanocellulose features, but also heavily dependent on sustainability. The three core nanocelluloses encompass cellulose nanocrystals (CNCs), cellulose nanofibrils (CNFs), and bacterial nanocellulose (BNC). All these different types of nanocellulose display highly interesting biomedical properties per se, after modification and when used in composite formulations. Novel applications that use nanocellulose includewell-known areas, namely, wound dressings, implants, indwelling medical devices, scaffolds, and novel printed scaffolds. Their cytotoxicity and biocompatibility using recent methodologies are thoroughly analyzed to reinforce their near future applicability. By analyzing the pristine core nanocellulose, none display cytotoxicity. However, CNF has the highest potential to fail long-term biocompatibility since it tends to trigger inflammation. On the other hand, neverdried BNC displays a remarkable biocompatibility. Despite this, all nanocelluloses clearly represent a flag bearer of future superior biomaterials, being elite materials in the urgent replacement of our petrochemical dependence

Phytochemical Omics in Medicinal Plants

Medicinal plants are used to treat diseases and provide health benefits, and their applications are increasing around the world. A huge array of phytochemicals have been identified from medicinal plants, belonging to carotenoids, flavonoids, lignans, and phenolic acids, and so on, with a wide range of biological activities. In order to explore our knowledge of phytochemicals with the assistance of modern molecular tools and high-throughput technologies, this book collects recent innovative original research and review articles on subtopics of mechanistic insights into bioactivities, treatment of diseases, profiling, extraction and identification, and biotechnology

Handbook of Marine Model Organisms in Experimental Biology

"The importance of molecular approaches for comparative biology and the rapid development of new molecular tools is unprecedented. The extraordinary molecular progress belies the need for understanding the development and basic biology of whole organisms. Vigorous international efforts to train the next-generation of experimental biologists must combine both levels – next generation molecular approaches and traditional organismal biology. This book provides cutting-edge chapters regarding the growing list of marine model organisms. Access to and practical advice on these model organisms have become aconditio sine qua non for a modern education of advanced undergraduate students, graduate students and postdocs working on marine model systems. Model organisms are not only tools they are also bridges between fields – from behavior, development and physiology to functional genomics. Key Features Offers deep insights into cutting-edge model system science Provides in-depth overviews of all prominent marine model organisms Illustrates challenging experimental approaches to model system research Serves as a reference book also for next-generation functional genomics applications Fills an urgent need for students Related Titles Jarret, R. L. & K. McCluskey, eds. The Biological Resources of Model Organisms (ISBN 978-1-1382-9461-5) Kim, S.-K. Healthcare Using Marine Organisms (ISBN 978-1-1382-9538-4) Mudher, A. & T. Newman, eds. Drosophila: A Toolbox for the Study of Neurodegenerative Disease (ISBN 978-0-4154-1185-1) Green, S. L. The Laboratory Xenopus sp. (ISBN 978-1-4200-9109-0)