Ekstraksi secara morphology pada pembuluh darah retina dari gambar fundus retina

Ekstraksi pembuluh darah retina dari gambar fundus retina merupakan langkah kunci dalam proses mengenal bentuk pola penyakit di retina. Metode-metode sebelumnya pada Ektraksi Pembuluh Darah Retina mempunyai ciri khas tersendiri terutama pada langkah pra-proses, ektraksi, dan post-proses pembuluh darah. Akan tetapi masih banyak ciri khas tersebut yang menjadikannya tidak cukup untuk memuaskan akan kebutuhan. Oleh karena itu penelitian selalu melakukan pengembangan untuk mencapai kebutuhan yang memuaskan bagi bidang medis. Maka dari pada itu kami melakukan percobaan dalam rangka pengembangan. Pada paper ini kami menggunakan metode Ekstraksi secara Morphology pada Pembuluh Darah Retina. Alhasil dengan menggunakan data STARE dan DRIVE didapatkan akurasi 90% dan 80%

Microscopy and Analysis

Microscopes represent tools of the utmost importance for a wide range of disciplines. Without them, it would have been impossible to stand where we stand today in terms of understanding the structure and functions of organelles and cells, tissue composition and metabolism, or the causes behind various pathologies and their progression. Our knowledge on basic and advanced materials is also intimately intertwined to the realm of microscopy, and progress in key fields of micro- and nanotechnologies critically depends on high-resolution imaging systems. This volume includes a series of chapters that address highly significant scientific subjects from diverse areas of microscopy and analysis. Authoritative voices in their fields present in this volume their work or review recent trends, concepts, and applications, in a manner that is accessible to a broad readership audience from both within and outside their specialist area

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Redes neurais convolucionais para segmentação de unidades de tecidos funcionais do rim

TCC (graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Elétrica.Redes Neurais Convolucionais pautadas na inteligência artificial e no deep learning são agentes facilitadores para resolução de problemas. O objetivo geral deste estudo é treinar um modelo de segmentação semântica de imagens médicas, em várias etapas estruturadas, testando diversos otimizadores, tamanhos de imagem, técnicas de transformação de dados e arquiteturas de redes neurais, buscando a melhor performance e a capacidade de segmentação de imagens médicas. Neste sentido apresenta-se a construção de um modelo de inteligência artificial, totalmente convolucional, capaz de segmentar tecidos funcionais do rim, gerando a base tecnológica necessária para auxiliar trabalhos futuros de análise em larga escala dos glomérulos presentes no rim. A relevância se apresenta na contribuição científica em estudos de automatização de exames de diagnósticos para doenças renais e possíveis aplicações para outros ramos. Além disso, ajuda o entendimento de como as interações intercelulares afetam a saúde humana, em específico, na segmentação do glomérulo, um tecido funcional do rim. O modelo final consiste em uma variação da arquitetura U-Net que obteve uma performace na métrica DICE de 92,33% na competição HuBMAP – Hacking the Kidney, superando 74% dos modelos submetidos à competição

What makes a landmark a landmark? How active vision strategies help honeybees to process salient visual features for spatial learning

Mertes M. Primary sensory processing of visual and olfactory signals in the bumblebee brain. Bielefeld: Bielefeld University; 2013.Since decades honeybees are being used as an insect model system for answering scientific questions in a variety of areas. This is due to their enormous behavioural repertoire paired with their learning capabilities. Similar learning capabilities are also evident in bumblebees that are closely related to honeybees. As honeybees, they are central place foragers that commute between a reliable food source and their nest and, therefore, need to remember particular facets of their environment to reliably find back to these places. Via their flight style that consists of fast head and body rotations (saccades)interspersed with flight segments of almost no rotational movements of the head (intersaccades) it is possible to acquire distance information about objects in the environment. Depending on the structure of the environment bumblebees as well as honeybees can use these objects as landmarks to guide their way between the nest and a particular food source. Landmark learning as a visual task depends of course on the visual input perceived by the animal’s eyes. As this visual input rapidly changes during head saccades, we recorded in my first project bumblebees with high-speed cameras in an indoor flight arena, while they were solving a navigation task that required them to orient according to landmarks. First of all we tracked head orientation during whole flight periods that served to learn the spatial arrangement of the landmarks. Like this we acquired detailed data on the fine structure of their head saccades that shape the visual input they perceive. Head-saccades of bumblebees exhibit a consistent relationship between their duration, peak velocity and amplitude resembling the human so-called "saccadic main sequence" in its main characteristics. We also found the bumblebees’saccadic sequence to be highly stereotyped, similar to many other animals. This hints at a common principle of reliably reducing the time during which the eye is moved by fast and precise motor control. In my first project I tested bumblebees with salient landmarks in front of a background covered with a random-dot pattern. In a previous study, honeybees were trained with the same landmark arrangement and were additionally tested using landmarks that were camouflaged against the background. As the pattern of the landmark textures did not seem to affect their performance in finding the goal location, it had been assumed that the way they acquire information about the spatial relationship between objects is independent of the objects texture. Our aim for the second project of my dissertation was therefore to record the activity of motion sensitive neurons in the bumblebee to analyse in how far object information is contained in a navigation-related visual stimulus movie. Also we wanted to clarify, if object texture is represented by the neural responses. As recording from neurons in free-flying bumblebees is not possible, we used one of the recorded bumblebee trajectories to reconstruct a three-dimensional flight path including data on the head orientation. We therefore could reconstruct ego-perspective movies of a bumblebee 10 while solving a navigational task. These movies were presented to motion-sensitive neurons in the bumblebee lobula. We found for two different classes of neurons that object information was contained in the neuronal response traces. Furthermore, during the intersaccadic parts of flight the object’s texture did not change the general response profile of these neurons, which nicely matches the behavioural findings. However, slight changes in the response profiles acquired for the saccadic parts of flight might allow to extract texture information from these neurons at later processing stages. In the final project of my dissertation I switched from exploring coding of visual information to the coding of olfactory signals. For honeybees and bumblebees olfaction is approximately equally important for their behaviour as their vision sense. But whereas there is a solid knowledge base on honeybee olfaction with detailed studies on the single stages of olfactory information processing this knowledge was missing for the bumblebee. In the first step we conducted staining experiments and confocal microscopy to identify input tracts conveying information from the antennae to the first processing stage of olfactory information – the antennal lobe (AL ). Using three-dimensional reconstruction of the AL we could further elucidate typical numbers of single spheroidal shaped subunits of the AL , which are called glomeruli. Odour molecules that the bumblebee perceives induce typical activation patterns characteristic of particular odours. By retrogradely staining the output tracts that connect the AL to higher order processing stages with a calcium indicator, we were capable of recording the odourdependent activation patterns of the AL glomeruli and to describe their basic coding principles. Similarly as in honeybees, we could show that the odours’ carbon chain length as well as their functional groups are dimensions that the antennal lobe glomeruli are coding in their spatial response pattern. Applying correlation methods underlined the strong similarity of the glomerular activity pattern between honeybees and bumblebees

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

Microscopy Conference 2017 (MC 2017) - Proceedings

Das Dokument enthält die Kurzfassungen der Beiträge aller Teilnehmer an der Mikroskopiekonferenz "MC 2017", die vom 21. bis 25.08.2017, in Lausanne stattfand

29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202