Relevant bibliographies by topics / Fundus Image

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fundus Image'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Fundus Image"

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Starovoitov, V. V., Y. I. Golub, and M. M. Lukashevich. "Digital fundus image quality assessment." «System analysis and applied information science», no. 4 (January 5, 2022): 25–38. http://dx.doi.org/10.21122/2309-4923-2021-4-25-38.

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Diabetic retinopathy (DR) is a disease caused by complications of diabetes. It starts asymptomatically and can end in blindness. To detect it, doctors use special fundus cameras that allow them to register images of the retina in the visible range of the spectrum. On these images one can see features, which determine the presence of DR and its grade. Researchers around the world are developing systems for the automated analysis of fundus images. At present, the level of accuracy of classification of diseases caused by DR by systems based on machine learning is comparable to the level of qualif
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Wintergerst, Maximilian W. M., Linus G. Jansen, Frank G. Holz, and Robert P. Finger. "A Novel Device for Smartphone-Based Fundus Imaging and Documentation in Clinical Practice: Comparative Image Analysis Study." JMIR mHealth and uHealth 8, no. 7 (2020): e17480. http://dx.doi.org/10.2196/17480.

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Background Smartphone-based fundus imaging allows for mobile and inexpensive fundus examination with the potential to revolutionize eye care, particularly in lower-resource settings. However, most smartphone-based fundus imaging adapters convey image quality not comparable to conventional fundus imaging. Objective The purpose of this study was to evaluate a novel smartphone-based fundus imaging device for documentation of a variety of retinal/vitreous pathologies in a patient sample with wide refraction and age ranges. Methods Participants’ eyes were dilated and imaged with the iC2 funduscope
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Wang, Shuang. "Research on Fundus Image Mosaic Method Based on Genetic Algorithm." Advances in Multimedia 2021 (November 30, 2021): 1–7. http://dx.doi.org/10.1155/2021/6060691.

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Retinal image mosaic is the key to detect common diseases, and the existing image mosaic methods are difficult to solve the problems of low contrast of fundus images and geometric distortion between images in different fields of view. To solve the problem of noise in retinal fundus images, an image mosaic algorithm based on the genetic algorithm was proposed. Firstly, a series of morphological pretreatment was performed on the fundus images. Then, the vascular network is extracted by obtaining the maximum entropy of the image to determine the threshold value. The similarity of the image to be
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Chen, Shizhao, Qian Zhou, and Hua Zou. "A Novel Un-Supervised GAN for Fundus Image Enhancement with Classification Prior Loss." Electronics 11, no. 7 (2022): 1000. http://dx.doi.org/10.3390/electronics11071000.

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Fundus images captured for clinical diagnosis usually suffer from degradation factors due to variation in equipment, operators, or environment. These degraded fundus images need to be enhanced to achieve better diagnosis and improve the results of downstream tasks. As there is no paired low- and high-quality fundus image, existing methods mainly focus on supervised or semi-supervised learning methods for color fundus image enhancement (CFIE) tasks by utilizing synthetic image pairs. Consequently, domain gaps between real images and synthetic images arise. With respect to existing unsupervised
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Li, Zhenwei, Mengying Xu, Xiaoli Yang, and Yanqi Han. "Multi-Label Fundus Image Classification Using Attention Mechanisms and Feature Fusion." Micromachines 13, no. 6 (2022): 947. http://dx.doi.org/10.3390/mi13060947.

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Fundus diseases can cause irreversible vision loss in both eyes if not diagnosed and treated immediately. Due to the complexity of fundus diseases, the probability of fundus images containing two or more diseases is extremely high, while existing deep learning-based fundus image classification algorithms have low diagnostic accuracy in multi-labeled fundus images. In this paper, a multi-label classification of fundus disease with binocular fundus images is presented, using a neural network algorithm model based on attention mechanisms and feature fusion. The algorithm highlights detailed featu
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Dai, Peishan, Hanwei Sheng, Jianmei Zhang, Ling Li, Jing Wu, and Min Fan. "Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing." International Journal of Biomedical Imaging 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/5075612.

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Retinal fundus image plays an important role in the diagnosis of retinal related diseases. The detailed information of the retinal fundus image such as small vessels, microaneurysms, and exudates may be in low contrast, and retinal image enhancement usually gives help to analyze diseases related to retinal fundus image. Current image enhancement methods may lead to artificial boundaries, abrupt changes in color levels, and the loss of image detail. In order to avoid these side effects, a new retinal fundus image enhancement method is proposed. First, the original retinal fundus image was proce
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Gervelmeyer, Julius, Sarah Müller, Ziwei Huang, and Philipp Berens. "Fundus Image Toolbox: A Python package for fundus image processing." Journal of Open Source Software 10, no. 108 (2025): 7101. https://doi.org/10.21105/joss.07101.

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Zhao, Wen Dong, You Dong Zhang, and Chun Xia Jin. "A New Method of Fundus Image Enhancement Based on Rough Set and Wavelet Transform." Applied Mechanics and Materials 397-400 (September 2013): 2205–8. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2205.

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Fundus images are complex images with more details, and on the basis of the inadequate fuzzy enhancement algorithm proposed by Pal et al, this article propose an improved algorithm of rough set for fundus image enhancement. The fundus image will be multi-scale decomposed by wavelet transform firstly, and then the subgraphs are enhanced by using rough set to improve the visual effects; finally the processed sub-images will be reconstructed and generated a new-enhanced image. Compared with the Pal algorithm, the new algorithm not only overcomes its weaknesses that the threshold is set with a fix
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Kapoor, Preeti, and Shaveta Arora. "Fundus Image Generation using EyeGAN." Journal of Computers, Mechanical and Management 2, no. 6 (2023): 9–17. http://dx.doi.org/10.57159/gadl.jcmm.2.6.230106.

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Deep learning models are widely used in various computer vision fields ranging from classification, segmentation to identification, but these models suffer from the problem of overfitting. Diversifying and balancing the datasets is a solution to the primary problem. Generative Adversarial Networks (GANs) are unsupervised learning image generators which do not require any additional information. GANs generate realistic images and preserve the minute details from the original data. In this paper, a GAN model is proposed for fundus image generation to overcome the problem of labelled data insuffi
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Krzywicki, Tomasz, Piotr Brona, Agnieszka M. Zbrzezny, and Andrzej E. Grzybowski. "A Global Review of Publicly Available Datasets Containing Fundus Images: Characteristics, Barriers to Access, Usability, and Generalizability." Journal of Clinical Medicine 12, no. 10 (2023): 3587. http://dx.doi.org/10.3390/jcm12103587.

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This article provides a comprehensive and up-to-date overview of the repositories that contain color fundus images. We analyzed them regarding availability and legality, presented the datasets’ characteristics, and identified labeled and unlabeled image sets. This study aimed to complete all publicly available color fundus image datasets to create a central catalog of available color fundus image datasets.
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Dissertations / Theses on the topic "Fundus Image"

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Gonzalez, Ana Guadalupe Salazar. "Structure analysis and lesion detection from retinal fundus images." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6456.

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Ocular pathology is one of the main health problems worldwide. The number of people with retinopathy symptoms has increased considerably in recent years. Early adequate treatment has demonstrated to be effective to avoid the loss of the vision. The analysis of fundus images is a non intrusive option for periodical retinal screening. Different models designed for the analysis of retinal images are based on supervised methods, which require of hand labelled images and processing time as part of the training stage. On the other hand most of the methods have been designed under the basis of specif
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Colomer, Granero Adrián. "Fundus image analysis for automatic screening of ophthalmic pathologies." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/99745.

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En los ultimos años el número de casos de ceguera se ha reducido significativamente. A pesar de este hecho, la Organización Mundial de la Salud estima que un 80% de los casos de pérdida de visión (285 millones en 2010) pueden ser evitados si se diagnostican en sus estadios más tempranos y son tratados de forma efectiva. Para cumplir esta propuesta se pretende que los servicios de atención primaria incluyan un seguimiento oftalmológico de sus pacientes así como fomentar campañas de cribado en centros proclives a reunir personas de alto riesgo. Sin embargo, estas soluciones exigen una alta carga
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Běťák, Ondřej. "Multimodální registrace retinálních snímků z fundus kamery a OCT." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219716.

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V první části se práce se zabývá rešerší metod a principů potřebných při registraci obrazu. Dále pak popisuje zobrazovací systémy očního pozadí jako jsou OCT, fundus kamera a SLO. Druhá část práce je zaměřena na praktickou realizaci programů pro registraci snímků z OCT, SLO a fundus kamery v programovém prostředí Matlab.
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Morales, Martínez Sandra. "Fundus characterization for automatic disease screening through retinal image processing." Doctoral thesis, Editorial Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53933.

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[EN] The World Health Organization estimates that in 2010 there were 285 million people visually impaired in the world. It is calculated that the 80\% of these cases are preventable or treatable. In addition, aging population and chronic disease increase are two factors that predict a higher number of blindness cases in the future. Hypertension, diabetic retinopathy (DR), age-related macular degeneration (AMD) and glaucoma are the most common pathologies in the current society that provoke retinal damage and can be directly related to blindness and vision loss. The early diagnosis of these dis
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Svoboda, Ondřej. "Pokročilé metody segmentace cévního řečiště na fotografiích sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220290.

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Segmentation of vasculature tree is an important step of the process of image processing. There are many methods of automatic blood vessel segmentation. These methods are based on matched filters, pattern recognition or image classification. Use of automatic retinal image processing greatly simplifies and accelerates retinal images diagnosis. The aim of the automatic image segmentation algorithms is thresholding. This work primarily deals with retinal image thresholding. We discuss a few works using local and global image thresholding and supervised image classification to segmentation of bloo
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Xu, Xiayu. "Automated delineation and quantitative analysis of blood vessels in retinal fundus image." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3017.

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Automated fundus image analysis plays an important role in the computer aided diagnosis of ophthalmologic disorders. A lot of eye disorders, as well as cardiovascular disorders, are known to be related with retinal vasculature changes. Many studies has been done to explore these relationships. However, most of the studies are based on limited data obtained using manual or semi-automated methods due to the lack of automated techniques in the measurement and analysis of retinal vasculature. In this thesis, a fully automated retinal vessel width measurement technique is proposed. This novel metho
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Pinkava, Marek. "Extrakce krevního řečiště z Fundus snímku lidského oka." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220635.

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This thesis deals with processing of retinal fundus images. Vision is the most important human sense and its injury has very serious consequences for humans. Automatic processing of retinal images increases the efficiency of medical examination and accelerates diagnoses of deseases. Retina exhibits unique characteristics for each person and thus can also be used to identify people. In this task is briefly discussed the structure and properties of each parts of the eye, particularly the retina, and their possible diseases such as diabetic retinopathy, glaucoma and age related macular degenerati
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Díaz, Pinto Andrés Yesid. "Machine Learning for Glaucoma Assessment using Fundus Images." Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/124351.

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[ES] Las imágenes de fondo de ojo son muy utilizadas por los oftalmólogos para la evaluación de la retina y la detección de glaucoma. Esta patología es la segunda causa de ceguera en el mundo, según estudios de la Organización Mundial de la Salud (OMS). En esta tesis doctoral, se estudian algoritmos de aprendizaje automático (machine learning) para la evaluación automática del glaucoma usando imágenes de fondo de ojo. En primer lugar, se proponen dos métodos para la segmentación automática. El primer método utiliza la transformación Watershed Estocástica para segmentar la copa óptica y post
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Hu, Qiao. "Automatic construction of arterial and venous vascular trees in fundus images." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/3107.

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The retinal vasculature analysis plays an important role in the diagnosis of ophthalmological diseases, as well as general human disorders that manifest on the retina. The fundus photograph is a 2-D color image modality of the retina and is widely used in modern ophthalmology clinics due to its relatively low cost and its non-invasive access to the retina. However, due to the complexity of the retinal vasculature presented on the image and the large variation of the image quality, no automated method is able to re-construct the retinal vasculature (i.e. construct arteriovenous trees) satisfact
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Klimeš, Filip. "Zpracování obrazových sekvencí sítnice z fundus kamery." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220975.

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Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.
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Books on the topic "Fundus Image"

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Abdollahi, Mohsen. Computer aided processing and analysis of fundus images. University of Birmingham, 1988.

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Burton, Terry. Naming rights: Legacy gifts and corporate money. Wiley, 2008.

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Liyanage, Sidath E., Fred K. Chen, and James W. Bainbridge. Vitreoretinal surgery. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199672516.003.0005.

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This chapter explores vitreoretinal surgery. It starts off with a detailed examination of retinal anatomy, including a discussion of retinal embryology, and then discusses the physiology of the retina. Next, it outlines the clinical skills of posterior segment history taking and examination. It then discusses the use of diagnostic lenses, which enable visualization of the fundus by neutralizing the optical power of the eye (direct lenses) or increasing the refractive power of the eye to create an inverted real image of the fundus anterior to the eye (indirect lenses). It then continues with a
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Intelligent Analysis of Fundus Images: Methods and Applications. World Scientific Publishing Co Pte Ltd, 2023.

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Ash, Eric. Scanned Image Microscopy (Rank Prize Funds Opto-Electronics Biennial Symposia). Academic Press, 1997.

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Ash, Eric. Scanned Image Microscopy (Rank Prize Funds Opto-Electronics Biennial Symposia). Academic Press, 1997.

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Clift, Ben. The IMF, the UK Policy Debate, and Debt and Deficit Discourse. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198813088.003.0006.

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This chapter charts changing character of the economic ideas informing fiscal policymaking in Britain, and Fund responses to them. Drawing on interviews with the Fund’s UK Missions and UK authorities, it shows how, despite the IMF’s prizing of its non-political, scientific image, its differing views of UK policy space and prioritization became the stuff of a contested politics. The central assumption of the coalition government’s construction of fiscal rectitude was that Britain faced a ‘crisis of debt’, yet the IMF did not share this view. Fund work on fiscal multipliers being higher during r
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Braddick, O. J., and A. C. Sleigh. Physical and Biological Processing of Images: Proceedings of an International Symposium Organised by the Rank Prize Funds, London, England, 27–29 ... Series in Information Sciences ). Springer, 2011.

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Gross, Valerie J. Transforming Our Image, Building Our Brand. ABC-CLIO, LLC, 2012. http://dx.doi.org/10.5040/9798216027126.

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This book describes a groundbreaking concept that enables public libraries—and librarians—to become indispensable by following a "Three Pillars" educational approach, and by replacing traditional terms with powerful, intuitive, value-enhanced terminology that everyone understands. While there is no question that what librarians and library professionals do is critically important, the ways in which these roles and responsibilities are described can mean the difference between being valued as essential to the community or considered optional. Something as simple as a choice of words can determi
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Davies, H. P. R. Twiston. Transmission of the Book of the Dead in New Kingdom Tombs at Saqqara. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350350618.

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Texts and images from theBook of the Deadwere widely used to decorate the walls of tombs during Egypt’s New Kingdom (c. 1550-1077 BCE).Prior research has tended to focus on either individual tombs, or on the contents of papyrus copies of theBook of the Dead. This book focusses on the adaptation of parts of this funerary corpus in individual tombs from the New Kingdom necropolis at Saqqara, with the aim of showing how each tomb’s decoration was tailored to the ends of their builders. In doing so, it builds up a picture of the ways in which these developments changed over time, and captures the
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Book chapters on the topic "Fundus Image"

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Wang, Li, and Abhir Bhalerao. "Model Based Segmentation for Retinal Fundus Images." In Image Analysis. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_57.

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Li, Wanyue, Yi He, Wen Kong, et al. "SequenceGAN: Generating Fundus Fluorescence Angiography Sequences from Structure Fundus Image." In Simulation and Synthesis in Medical Imaging. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87592-3_11.

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Liu, Yufan. "Continual Learning for Fundus Image Segmentation." In Lecture Notes in Computer Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8496-7_22.

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Ray, Abheek, Ayantika Chakraborty, Dipankar Roy, Barun Sengupta, and Mainak Biswas. "Blood Vessel Extraction from Fundus Image." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1501-5_22.

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Adal, Kedir M., Ronald M. Ensing, Rosalie Couvert, et al. "A Hierarchical Coarse-to-Fine Approach for Fundus Image Registration." In Biomedical Image Registration. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08554-8_10.

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Kolar, Radim, Bernhard Hoeher, Jan Odstrcilik, Bernhard Schmauss, and Jiri Jan. "Registration of Image Sequences from Experimental Low-Cost Fundus Camera." In Biomedical Image Registration. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08554-8_18.

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Mueller, Simon, Snezhana Karpova, Maximilian W. M. Wintergerst, et al. "Automated Detection of Diabetic Retinopathy from Smartphone Fundus Videos." In Ophthalmic Medical Image Analysis. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63419-3_9.

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Ahn, Sangil, and Jitae Shin. "Self-supervised Learning for Anomaly Detection in Fundus Image." In Ophthalmic Medical Image Analysis. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16525-2_15.

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Rekha, R., V. P. Brintha, and P. Anushree. "Heart Disease Prediction Using Retinal Fundus Image." In Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24051-6_71.

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Raja Rajeswari Chandni, P., Judith Justin, and R. Vanithamani. "Fundus Image Enhancement Using EAL-CLAHE Technique." In Advances in Data and Information Sciences. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5689-7_54.

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Conference papers on the topic "Fundus Image"

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Shen, Ding, Yuhan Zhang, Shiping Zhang, and Menglin Wu. "Unsupervised Registration Network for Fundus Image Mosaicking." In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://dx.doi.org/10.1109/isbi56570.2024.10635356.

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Dutta, Monoronjon, Md Abbas Ali Khan, M. M. Fazle Rabbi, Md Atiqur Rahman, and Mohammad Monirul Islam. "Retinal Fundus Image Classification Using Generative Adversarial Networks." In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE). IEEE, 2025. https://doi.org/10.1109/ecce64574.2025.11013430.

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Correra, Simona, Giulia Varriano, Vittoria Nardone, and Antonella Santone. "Identifying Ocular Diseases through Image Processing: Pattern Matching on Single Fundus Images." In 2024 32nd International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). IEEE, 2024. https://doi.org/10.1109/wetice64632.2024.00031.

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A, Aruna K., Vrinda S. Anil, Anju Anand, et al. "Image Mosaicing for Neonatal Fundus Images." In 2021 8th International Conference on Smart Computing and Communications (ICSCC). IEEE, 2021. http://dx.doi.org/10.1109/icscc51209.2021.9528163.

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Xu, Mengdi, Jun Cheng, Damon Wing Kee Wong, Ching-Yu Cheng, Seang Mei Saw, and Tien Yin Wong. "Automated Tessellated Fundus Detection in Color Fundus Images." In Ophthalmic Medical Image Analysis Third International Workshop. University of Iowa, 2016. http://dx.doi.org/10.17077/omia.1043.

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Mitra, Sunanda, Vinod Chandran, Thomas F. Krile, and Dah-Jye Lee. "Fundus Image Registration Algorithms for a PC-Based Image Processing System." In Noninvasive Assessment of the Visual System. Optica Publishing Group, 1987. http://dx.doi.org/10.1364/navs.1987.md4.

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Fundus photographs are routinely taken in an ophthalmology clinic to monitor feature changes in the suspected regions of the retina. For quantitative evaluation of subtle changes in the fundus from the photographs taken over a period of time using digital image processing, the fundus images have to be registered to a reference image, usually, the image of the same fundus taken earlier. The problem of registering one digital image with another reduces to that of finding local similarity between two structural data sets.
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Shenkut, Dereje, and Vijayakumar Bhagavatula. "Fundus GAN - GAN-based Fundus Image Synthesis for Training Retinal Image Classifiers." In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2022. http://dx.doi.org/10.1109/embc48229.2022.9871771.

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Binti Sabri, Nur Rafidah, and Haniza Binti Yazid. "Image Enhancement Methods For Fundus Retina Images." In 2018 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2018. http://dx.doi.org/10.1109/scored.2018.8711106.

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Zheng, Jin, Liye Guo, Lihui Peng, Jianqiang Li, Jijiang Yang, and Qingfeng Liang. "Fundus image based cataract classification." In 2014 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2014. http://dx.doi.org/10.1109/ist.2014.6958452.

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Mitra, Sunanda, Steven Whiteside, Ravi Bagri, Thomas F. Krile, and Zuhair Shihab. "Image enhancement of fundus photographs." In OSA Annual Meeting. Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.thx4.

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A novel application of digital image enhancement and restoration techniques has allowed us to detect structural changes in fundus photographs (i.e., photographs of the retina as viewed through the pupil of the eye). The visualization of the structural changes in the nerve fiber layers in the retina has been obtained by a combination of edge detection and point-to-point mapping procedures. Such a combination of optimized edge detectors has significant application in quantitative evaluation of early textural changes in the retina caused by degeneration of nerve fibers. In ocular diseases such as
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Reports on the topic "Fundus Image"

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Ushizima, Daniela, and Jorge Cuadros. Image analysis of ocular fundus for retinopathy characterization. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1004692.

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Enscore, Susan, Dawn Morrison, Adam Smith, and Sunny Adams. Fort Huachuca ranges : a history and analysis. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42720.

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Fort Huachuca Environmental and Natural Resources Division (ENRD) sent funds to ERDC-CERL to develop a historic context that assists Fort Huachuca personnel in identifying the likely history and provenance of numerous historic range features located across Fort Huachuca's training lands. The historic context will be used by cultural resources personnel to evaluate and manage the resources appropriately. Various historic training range features (e.g., structures, fragments, and items left over from previous activities) are located across the ranges of Fort Huachuca, representing its long and st
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Peippo, Jaana, Mervi Honkatukia, Maria Kjetså, and Ellen-Louisa Fagerheim White. The NordFrost Project Report – Farm Animal Gene Banks in the Nordic Region: Added Value Through Nordic Cooperation. Nordic Genetic Resource Center (NordGen), 2024. http://dx.doi.org/10.53780/arpi5480.

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The network project titled “Nordic animal gene banks – added value through Nordic cooperation” (NordFrost), has aimed to strengthen the collaboration and competence for ex-situ conservation of animal genetic resources (AnGR) in the Nordic region. This project was launched as a case study following the Horizon2020 funded IMAGE project (2016-2020) where it was concluded that there is a broad variation in the current state of practices and the distribution of responsibilities related to cryoconservation activities between the Nordic countries. The national strategies on conserving AnGR emphasise
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Peippo, Jaana, Mervi Honkatukia, Maria Kjetså, and Ellen-Louisa Fagerheim White. The NordFrost Project Report – Farm Animal Gene Banks in the Nordic Region: Added Value Through Nordic Cooperation. Nordic Genetic Resource Center (NordGen), 2024. http://dx.doi.org/10.53780/rlyj6032.

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The network project titled “Nordic animal gene banks – added value through Nordic cooperation” (NordFrost), has aimed to strengthen the collaboration and competence for ex-situ conservation of animal genetic resources (AnGR) in the Nordic region. This project was launched as a case study following the Horizon2020 funded IMAGE project (2016-2020) where it was concluded that there is a broad variation in the current state of practices and the distribution of responsibilities related to cryoconservation activities between the Nordic countries. The national strategies on conserving AnGR emphasise
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Emma, Olsson. Kolinlagring med biokol : Att nyttja biokol och hydrokol som kolsänka i östra Mellansverige. Linköping University Electronic Press, 2025. https://doi.org/10.3384/9789180759496.

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Pest inventory of a field is a way of knowing when the thresholds for pest control is reached. It is of increasing interest to use machine learning to automate this process, however, many challenges arise with detection of small insects both in traps and on plants. This thesis investigates the prospects of developing an automatic warning system for notifying a user of when certain pests are detected in a trap. For this, sliding window with histogram of oriented gradients based support vector machine were implemented. Trap detection with neural network models and a check size function were test
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Limoges, A., A. Normandeau, J. B R Eamer, et al. 2022William-Kennedy expedition: Nunatsiavut Coastal Interaction Project (NCIP). Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/332085.

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The accelerating Arctic cryosphere decline severely impacts the land on which northern communities live through the presence of coastal and marine geohazards and coastal erosion, which further places the cultural heritage of coastal archaeological sites at risks. Sea ice decline also compromises the formation of polynyas, with unknown consequences for the regional ecosystems. From the 10th to the 18th of July 2022, a scientific cruise onboard the research vessel William-Kennedy allowed the collection of a suite of samples and data from the marine coastal environment of Nain, Nunatsiavut. In to
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Aleksandrov, Pavlo. NEWS GAMES IN THE UKRAINIAN MEDIA SPACE DURING THE FULL-SCALE RUSSIAN INVASION. Ivan Franko National University of Lviv, 2024. http://dx.doi.org/10.30970/vjo.2024.54-55.12140.

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The phenomenon of news games on the topic of the Russian-Ukrainian war of 2022-2023 has been explored in the article. During the research, a number of gaming projects from this period were analyzed, their genre and thematic specificity were determined, examples of gaming products were provided, and our own concept of a news game on the topical subject of wartime was presented. In 2022-2023, many game projects on the theme of the war in Ukraine appeared, which can be fully or partially classified as news games, conditionally dividing them into “civilian” ones, where the game character is a volu
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Kwon, Heeseo Rain, HeeAh Cho, Jongbok Kim, Sang Keon Lee, and Donju Lee. International Case Studies of Smart Cities: Namyangju, Republic of Korea. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0007014.

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This case study is one of ten international studies developed by the Korea Research Institute for Human Settlements (KRIHS), in association with the Inter-American Development Bank (IDB), for the cities of Anyang, Medellin, Namyangju, Orlando, Pangyo, Rio de Janeiro, Santander, Singapore, Songdo, and Tel Aviv. At the IDB, the Competitiveness and Innovation Division (CTI), the Fiscal and Municipal Management Division (FMM), and the Emerging and Sustainable Cities Initiative (ESCI) coordinated the study. This project was part of technical cooperation ME-T1254, financed by the Knowledge Partnersh
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Horwitz, Benjamin, and Barbara Gillian Turgeon. Secondary Metabolites, Stress, and Signaling: Roles and Regulation of Peptides Produced by Non-ribosomal Peptide Synthetases. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7696522.bard.

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Fungal pathogens of plants produce a diverse array of small molecules. Often referred to as secondary metabolites because they were thought to be dispensable for basic functions, they may indeed have central roles as signals for the fungal cell, and in interactions with the host. We have identified more than a dozen genes encoding nonribosomal peptide synthetases (NPS) in Cochliobolusheterostrophus, the agent of southern corn leaf blight. The aim of this project was to identify roles of these genes in stress responses and signaling. The first objective was to test a complete collection of C. h
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Ampatzidis, Yiannis, Mahendra Bhandari, Andres Ferreyra, et al. AI in Agriculture: Opportunities, Challenges, and Recommendations. Chair Alex Thomasson. Council for Agricultural Science and Technology, 2025. https://doi.org/10.62300/iaag042514.

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Artificial Intelligence (AI) is rapidly being integrated into people’s lives, reshaping industries, and enabling previously unimagined innovation, even in agriculture. Generative AI focuses on creating content like text and pictures based on vast quantities of data. ExtensionBot is a generative AI platform that supports agricultural extension by providing farmers with accurate scientific information and specific recommendations. It has been shown to deliver more accurate responses to agricultural questions than broader generative AI models. Other forms of AI have been used to analyze data to p
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