Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Hajar, Danesh"'
Publikováno v:
IET Image Processing, Vol 14, Iss 15, Pp 3812-3818 (2020)
Limited labelled data is a challenge in the field of medical imaging and the need for a large number of them is paramount for the training of machine learning algorithms, as well as measuring the performance of image processing algorithms. The purpos
Externí odkaz:
https://doaj.org/article/8afc5dabb6fd4f76a406fb8ae4ba3689
Publikováno v:
IET Image Processing. 14:3812-3818
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92b5bc3c623af596fb69fc94d459c22f
https://doi.org/10.1049/iet-ipr.2020.0075
https://doi.org/10.1049/iet-ipr.2020.0075
Publikováno v:
مجله دانشکده پزشکی اصفهان, Vol 31, Iss 230, Pp 343-350 (2013)
Background: Enhanced depth imaging optical coherence tomography images (EDI-OCT) is used for detailed imaging of the choroid layer that contains the highest amount of blood flow in the eye and is affected in several diseases such as choroidal polyps,
Externí odkaz:
https://doaj.org/article/90497929a397493a9198ffe7202f72ed
Autor:
Hajar, Danesh, David H, Steel, Jeffry, Hogg, Fereshteh, Ashtari, Will, Innes, Jaume, Bacardit, Anya, Hurlbert, Jenny C A, Read, Rahele, Kafieh
Publikováno v:
Translational Vision Science & Technology, 2022, Vol.11(10), pp.10 [Peer Reviewed Journal]
Purpose: Optical coherence tomography (OCT) has recently emerged as a source for powerful biomarkers in neurodegenerative diseases such as multiple sclerosis (MS) and neuromyelitis optica (NMO). The application of machine learning techniques to the a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eddec77be689dda11c822b3bd5d54004
https://doi.org/10.1167/tvst.11.10.10
https://doi.org/10.1167/tvst.11.10.10
Publikováno v:
Medical & Biological Engineering & Computing
Nowadays, retinal optical coherence tomography (OCT) plays an important role in ophthalmology and automatic analysis of the OCT is of real importance: image denoising facilitates a better diagnosis and image segmentation and classification are undeni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a45bf5f8a1a66d64961df28edd524bb8
https://pubmed.ncbi.nlm.nih.gov/34792759
https://pubmed.ncbi.nlm.nih.gov/34792759
The challenge of limited labeled data in the field of medical imaging and the need for large number of labeled data for training machine learning algorithms, and to measure the performance of image processing algorithms increases the demand to use sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66912006df08de3ee4bcbf1a9beb3467
https://doi.org/10.1101/2020.09.05.20181917
https://doi.org/10.1101/2020.09.05.20181917
Publikováno v:
Computational and Mathematical Methods in Medicine
Computational and Mathematical Methods in Medicine, Vol 2014 (2014)
Computational and Mathematical Methods in Medicine, Vol 2014 (2014)
The introduction of enhanced depth imaging optical coherence tomography (EDI-OCT) has provided the advantage of in vivo cross-sectional imaging of the choroid, similar to the retina, with standard commercially available spectral domain (SD) OCT machi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::017d64f1155e2dd0f0e03772cbb2cd52
Publikováno v:
ICASSP
The correct segmentation of blood vessels in optical coherence tomography (OCT) images is an important requirement for better diagnosis of many retinal diseases. Although OCT blood vessel segmentation is often performed by applying vessel detection m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a291a338c7a1568dcfbef935440e32aa
https://doi.org/10.1109/icassp.2013.6637815
https://doi.org/10.1109/icassp.2013.6637815