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GPU-Based Image Geodesics for Optical Coherence Tomography
[chapter]
2017
Informatik aktuell
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First results for time series of optical coherence tomography images of a macular degeneration demonstrate the applicability of this geometric concept. ...
Based on a variational time discretization, discrete geodesic paths in this space of images are computed. ...
In this paper, we demonstrate the applicability of this approach to optical coherence tomography (OCT) images in age-related macular degeneration, the most common cause of irreversible visual loss in industrial ...
doi:10.1007/978-3-662-54345-0_21
dblp:conf/bildmed/BerkelsBERS17
fatcat:nsjx6c3awzcbbmxt2djxickr44
A New Idea of Fast Three-Dimensional Median Filtering for Despeckling of Optical Coherence Tomography Images
2015
Image Processing & Communications
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The authors encountered the problem when applying median filter to speckle noise reduction in optical coherence tomography images acquired by the Spark OCT systems. ...
In the paper a new approach to the GPU (Graphics Processing Unit) based median smoothing has been proposed, which uses two-step evaluation of local intensity histograms stored in the shared memory of a ...
Speckle noise influences the visual assessment of optical coherence tomography (OCT) images, affects detected boundaries of internal layers and therefore reduces diagnostic importance of acquired image ...
doi:10.1515/ipc-2015-0037
fatcat:cgyefwtpifhjpbcfhnyjlh3ori
Detection of Diabetic Macular Edema in Optical Coherence Tomography Image Using an Improved Level Set Algorithm
2020
BioMed Research International
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DME detection in Optical Coherence Tomography (OCT) image contributes to the early diagnosis of diabetic retinopathy and blindness prevention. ...
In this study, we proposed a novel algorithm for the detection and segmentation of DME region in OCT image based on the K-means clustering algorithm and improved Selective Binary and Gaussian Filtering ...
Optical coherence tomography (OCT) has gained increasing attention as a diagnosis tool for DME detection [29] . ...
doi:10.1155/2020/6974215
pmid:32420362
pmcid:PMC7210525
fatcat:prxf6m7sijhn3m7qep4a3nx6za
Estimating postprandial glucose fluxes using hierarchical Bayes modelling
2012
Computer Methods and Programs in Biomedicine
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Lamouche, "Real-time control of angioplasty balloon inflation based on feedback from intravascular optical coherence tomography: experimental validation on an excised heart and a beating heart model" IEEE ...
Lamouche, "Real-time Control of Angioplasty Balloon Inflation Based on Feedback from Intravascular Optical Coherence Tomography: Preliminary Study on an Artery Phantom," IEEE Transactions on Ng and P.E.Caines ...
doi:10.1016/j.cmpb.2012.01.010
pmid:22364961
fatcat:op6ujxzgwfbdbf5abvwcp5ysx4
Transmission–reflection optoacoustic ultrasound (TROPUS) computed tomography of small animals
2019
Light: Science & Applications
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Graphics-processing unit (GPU)-based algorithms employing spatial compounding and bent-ray-tracing iterative reconstruction were further developed to attain real-time rendering of ultrasound tomography ...
The system features full-view cross-sectional tomographic imaging geometry for concomitant noninvasive mapping of the absorbed optical energy, acoustic reflectivity, speed of sound, and acoustic attenuation ...
Reflection ultrasound-computed tomography (RUCT) In the RUCT mode, a high-resolution image was created by coherent summation of the low-resolution images from 128 individual transmission events corresponding ...
doi:10.1038/s41377-019-0130-5
pmid:30728957
pmcid:PMC6351605
fatcat:e77ykq7kqja67j2bycj274frwe
Integrating Handcrafted and Deep Features for Optical Coherence Tomography Based Retinal Disease Classification
2019
IEEE Access
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tomography image-based eye disease classification. ...
INDEX TERMS Artificial intelligence, deep learning, optical coherence tomography, feature integration. ...
Optical coherence tomography (OCT) has become a powerful imaging modality for non-invasive diagnosis of various retinal abnormalities, such as choroidal neovascularization (CNV) [1] - [3] , diabetic ...
doi:10.1109/access.2019.2891975
fatcat:54pbkn2zuzcupc3a6s4y2repiy
Faster Segmentation Algorithm for Optical Coherence Tomography Images with Guaranteed Smoothness
[chapter]
2011
Lecture Notes in Computer Science
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In this paper we present a highly efficient graph-theoretical approach for segmenting a surface from 3D OCT images. ...
Based on a volumetric graph representation of the 3D images that incorporates curvature information, our approach first generates a set of 2D local optimal segmentations, and then iteratively improves ...
The problem arises not only in the segmentation problem of biomedical images (e.g., CT, MRI, Ultrasound, Microscopy, Optical Coherence Tomography (OCT)) [4, 5] , but also in many other fundamental optimization ...
doi:10.1007/978-3-642-24319-6_38
fatcat:5tlipemlwna4fjwwjmmaedf6ei
Interactive processing and visualization of image data for biomedical and life science applications
2007
BMC Cell Biology
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We present an adaptive high-resolution display system suitable for biomedical image data, algorithms for analyzing and visualization protein surfaces and retinal optical coherence tomography data, and ...
visualization tools for 3D gene expression data. ...
Werner, Robert Zawadzki, Joe Izaatt, Stacey Choi, and Alfred Fuller for their contributions to the retinal imaging project. ...
doi:10.1186/1471-2121-8-s1-s10
pmid:17634091
pmcid:PMC1924506
fatcat:pqu2xstzunhtrbyvsnqy52fgei
Blood vessel segmentation algorithms — Review of methods, datasets and evaluation metrics
2018
Computer Methods and Programs in Biomedicine
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For each analyzed approach, summary tables are presented reporting imaging technique used, anatomical region and performance measures employed. ...
Blood vessel segmentation is a topic of high interest in medical image analysis since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and evaluation of clinical outcomes ...
OCT: Optical Coherence Tomography. ...
doi:10.1016/j.cmpb.2018.02.001
pmid:29544791
fatcat:cchvmvuy5zgzzetv5hwc67nnbe
Automated Deep Learning-based Multi-class Fluid Segmentation in Swept-Source Optical Coherence Tomography Images
[article]
2020
bioRxiv
pre-print
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Methods: Twenty-two swept-source optical coherence tomography (SS-OCT) volumes of the macula from 22 from different individuals with wAMD were manually annotated by two expert graders. ...
The correlation of fluid volume between the expert graders and the algorithm were 0.99 for IRF, 0.99 for SRF and 0.82 for PED. ...
Optical coherence tomography (OCT) revolutionized the management of AMD and has been used in investigative trials to link anatomical structure to function in the form of visual acuity (VA). 6 This ability ...
doi:10.1101/2020.09.01.278259
fatcat:6avafd3kqbhbxh3qr64s4ilb2u
Brain-inspired algorithms for retinal image analysis
2016
Machine Vision and Applications
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This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the B Bart M. ter Haar Romeny B.M.terHaarRomeny@tue.nl . ...
The methods are currently validated in collaborating hospitals, with a rich accompanying base of metadata, to phenotype and validate the quantitative algorithms for optimal classification power. ...
Several other early DR signs can be measured, such as nerve damage in the cornea with confocal laser microscopy, or changes in retina neural tissue layer thickness with optical coherence tomography (OCT ...
doi:10.1007/s00138-016-0771-9
fatcat:uzkykflk7zcodjdxadakqekn2u
Advanced Algorithms in Medical Computer Graphics
[article]
2008
Eurographics State of the Art Reports
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Advanced algorithms and efficient visualization techniques are of major importance in intra-operative imaging and image-guided surgery. ...
This paper summarizes advanced algorithms for medical visualization with special focus on risk structures such as tumors, vascular systems and white matter fiber tracts. ...
However, recent advances in GPU-based ray-casting easily allow for perspective projection, which is especially important in virtual endoscopy [SHNB06] . ...
doi:10.2312/egst.20081043
fatcat:7pk4swpmmvb4vl576xjm3leuue
From survey to representation. Operation guidelines
[chapter]
2012
Computational Modelling of Objects Represented in Images III
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An automatic unsupervised fuzzy method for image segmentation ...
Methods of graph searching for border detection in image sequences with applications to cardiac magnetic resonance imaging. IEEE Transaction On Medical Imaging 14 (1), 42-55. ...
Realtime pickup method for a three-dimensional image based
on integral photography. Applied Optics. Vol.36, NO.7. ...
doi:10.1201/b12753-91
fatcat:nh3phzgj2rcr3hwvqajsligzoq
2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57
2019
IEEE Transactions on Geoscience and Remote Sensing
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., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary ...
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang, ...
., +, TGRS Aug. 2019 6003-6017 An Object-Based Hierarchical Compound Classification Method for Change Detection in Heterogeneous Optical and SAR Images. ...
doi:10.1109/tgrs.2020.2967201
fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
Learning Capacity in Simulated Virtual Neurological Procedures
2020
Journal of WSCG
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ACKNOWLEDGEMENTS The authors would like to thank Oana Rotaru-Orhei for her comments and the three anonymous reviewers for their insightful suggestions. ...
ACKNOWLEDGMENTS The authors acknowledge the support of the NSERC/Creaform Industrial Research Chair on 3-D Scanning for conducting the work presented in this paper. ...
[22] developed a fully automated algorithm to segment fluid-filled and cyst regions in optical coherence tomography (OCT) retina images, segmented by combining a neutrosophic transformation and a graph-based ...
doi:10.24132/csrn.2020.3001.13
fatcat:uytlm7nytrhmnk553ellfhl54a
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