real-time automatic segmentation of optical coherence

Segmentation

2020-06-03 Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning Yukun Guo Tristan T Hormel Honglian Xiong Jie Wang Thomas S Hwang Yali Jia arXiv_CV arXiv_CV Segmentation Face CNN Deep_Learning PDF

Automated detection of choroid boundary and vessels in

Consequently ophthalmologists inspect optical coherence tomography (OCT) scans of the posterior section of the eye towards making diagnosis With a view to assist diagnosis we propose an automated technique for segmentation of the choroid layer Specifically we detect the upper and lower boundaries of the choroid using structural similarity and adaptive Hessian analysis Subsequently we

Universiti Teknologi Malaysia Institutional Repository: No

A research on polymer based optical waveguides and devices have been a topic of great interest in optical communications due to its pertinent advantages which include versatility and reduction in fabrication cost This thesis is significantly devoted towards the first ever development of single mode optical waveguides and multimode interference (MMI) interconnecting devices based on

Automated Intraretinal Layer Segmentation of Optical

Automated Intraretinal Layer Segmentation of Optical Coherence Tomography Images using Graph-theoretical Methods: Publication Type: Journal Article: Year of Publication: 2018: Authors : Roy P P Gholami M Parthasarathy J Zelek and V Lakshminarayanan: Journal: Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine Xxii: Volume: 10483:

OSA

To investigate the potential of optical coherence tomography (OCT) to distinguish between normal and pathologic thyroid tissue 3D OCT images were acquired on ex vivo thyroid samples from adult subjects (n=22) diagnosed with a variety of pathologies The follicular structure was analyzed in terms of count size density and sphericity Results showed that OCT images highly agreed with the

Accurate and automated image segmentation of 3D optical

Accurate and automated image segmentation of 3D optical coherence tomography data suffering from low signal-to-noise levels Rong Su 1 * Peter Ekberg 1 Michael Leitner 2 and Lars Mattsson1 1Department of Production Engineering KTH Royal Institute of Technology 68 Brinellvgen Stockholm 10044 Sweden 2Thorlabs Maria-Goeppert-Str 5 23562 Lbeck Germany

A Review of Adaptive Optics Optical Coherence

Purpose: Optical coherence tomography (OCT) has enabled "virtual biopsy" of the living human retina revolutionizing both basic retina research and clinical practice over the past 25 years For most of those years in parallel adaptive optics (AO) has been used to improve the transverse resolution of ophthalmoscopes to foster in vivo study of the retina at the microscopic level

We also simulated the optical system and did some off-line and online measurement experiments The results show the spectrometer has satisfactory reliability large luminous flux and online measurement capability It can be real-time online monitoring the biological process through measuring the concentration of the related bioreactor reactant

Tool/Resource Listing

The framework comprises two innovative parts: a longitudinal segmentation and a longitudinal classification step We introduce a novel approach to the joint segmentation of the hippocampus across multiple time points this approach is based on graph cuts of longitudinal MRI scans with constraints on hippocampal atrophy and supported by atlases

Clinical validation of an algorithm for rapid and accurate

The analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures However manual image segmentation is a cumbersome and time-consuming process subject to significant intra- and inter-observer variability This study aims to present and validate a fully-automated method for segmentation of intracoronary OCT

Automated segmentation of pathological cavities in optical

Automated segmentation of pathological cavities in optical coherence tomography scans Invest Ophthalmol Vis Sci 2013 Jun 27 54(6):4385-93 PMID:23737469 Pilch M Stieger K Wenner Y Preising MN Friedburg C Meyer zu Bexten E Lorenz B

JCM

13 This study aimed to develop and validate a deep learning system for diagnosing glaucoma using optical coherence tomography (OCT) A training set of 1822 eyes (332 control 1490 glaucoma) with 7288 OCT images an internal validation set of 425 eyes (104 control 321 glaucoma) with 1700 images and an external validation set of 355 eyes (108 control 247 glaucoma) with 1420 images

Real

Real-time automatic segmentation of optical coherence tomography volume data of the macular region Jing Tian Boglrka Varga Gbor Mrk Somfai Wen-Hsiang Lee William E Smiddy Delia Cabrera DeBuc Ophthalmology Research output: Contribution to journal › Article 47 Scopus citations Abstract Optical coherence tomography (OCT) is a high speed high resolution and non-invasive imaging

Real

Real-Time Automatic Segmentation of Optical Coherence Tomography Volume Data of the Macular Region (PMID:26258430 PMCID:PMC4530974) Full Text Citations Related Articles Data BioEntities External Links PLoS One 2015 10(8): e0133908 Published online 2015 Aug 10 doi: 10 1371/journal pone 0133908 PMCID: PMC4530974 PMID: 26258430 Real-Time Automatic

Feasibility evaluation of micro

The acquired optical coherence tomography (OCT) images were pathologically evaluated and compared to their corresponding histology for both tumor type and tumor grade discriminations in different cases By using the lab-built μOCT both the cross-sectional and en face images of glioma and meningioma were acquired ex vivo Based upon the morphology results both the glioma and

LIST website

pin International Conference on Ad-Hoc Networks and Wireless (ADHOC-NOW 2019): Ad-Hoc Mobile and Wireless Networks Luxembourg 1-3 October Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) vol 11803 LNCS p 566-574 ISBN: 978-303031830-7 2019/p https

Segmentation

2020-06-03 Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning Yukun Guo Tristan T Hormel Honglian Xiong Jie Wang Thomas S Hwang Yali Jia arXiv_CV arXiv_CV Segmentation Face CNN Deep_Learning PDF

Automatic Segmentation of Corneal Microlayers on Optical

11 06 2019Automatic Segmentation of Corneal Microlayers on Optical Coherence Tomography Images Elsawy A(1)(2) Abdel-Mottaleb M(2) Sayed IO(1) Wen D(1) Roongpoovapatr V(1) Eleiwa T(1)(3) Sayed AM(1)(4) Raheem M(1) Gameiro G(1) Shousha MA(1)(2)(5) Author information: (1)Bascom Palmer Eye Institute Miller School of Medicine University of Miami Miami FL USA

Evaluation of segmentation algorithms for optical

Optical coherence tomography (OCT) is an emerging technique that provides depthresolved high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging however due to small organ size the ovaries must rst be separated from the

Fully automatic three

Intravascular optical coherence tomography (IV-OCT) is an imaging modality that can be used for the assessment of intracoronary stents Recent publications pointed to the fact that 3D visualizations have potential advantages compared to conventional 2D representations However 3D imaging still requires a time consuming manual procedure not suitable for on-line application during coronary

OSA

To investigate the potential of optical coherence tomography (OCT) to distinguish between normal and pathologic thyroid tissue 3D OCT images were acquired on ex vivo thyroid samples from adult subjects (n=22) diagnosed with a variety of pathologies The follicular structure was analyzed in terms of count size density and sphericity Results showed that OCT images highly agreed with the

Segmentation

2020-06-03 Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning Yukun Guo Tristan T Hormel Honglian Xiong Jie Wang Thomas S Hwang Yali Jia arXiv_CV arXiv_CV Segmentation Face CNN Deep_Learning PDF

SYSTEM AND METHOD FOR THE SEGMENTATION OF

The present disclosure describes a system and method to segment optical coherence tomography (OCT) images The present system uses a hybrid method that employs both Bayesian level sets (BLS) and graph-based segmentation algorithms The system first identifies retinal tissue within an OCT image using the BLS algorithms The identified retinal tissue is then further segmented using the graph

Tomography optical coherence Medical search

26 he planned it to save his download spectral domain optical coherence at the theological Xbox not Just to be not and the one who says those who are today in Jesus 24 but back for our download spectral domain optical coherence tomography in to whom it will be created those who uphold in the one who were Jesus our Lord from the interest 25 He taught helped over because of our industries

english

Yankui Sun Tian Zhang Yue Zhao Yufan He 3D Automatic Segmentation Method for Retinal Optical Coherence Tomography Volume Data Using Boundary Surface Enhancement Journal of Innovative Optical Health Sciences 2016 9(2): 1650008-1~1650008-18 DOI: 10 1142/S1793545816500085

Real

Real-time automatic segmentation of optical coherence tomography volume data of the macular region Jing Tian Boglrka Varga Gbor Mrk Somfai Wen Hsiang Lee William E Smiddy Delia Cabrera DeBuc Semmelweis University Research output: Contribution to journal › Article 48 Citations (Scopus) Abstract Optical coherence tomography (OCT) is a high speed high resolution and non

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