Zobrazeno 1 - 10
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pro vyhledávání: '"Rétinal"'
Retinal Detachment: Principles and Practice provides a historical review of current information on the diagnosis and treatment of retinal detachment. It is intended as both an introduction for graduate students in ophthalmology and a concise review o
This advanced text, first published in 2006, takes a developmental approach to the presentation of our understanding of how vertebrates construct a retina. Written by experts in the field, each of the seventeen chapters covers a specific step in the
Autor:
Konno, Tsubasa, Ninomiya, Takahiro, Miura, Kanta, Ito, Koichi, Himori, Noriko, Sharma, Parmanand, Nakazawa, Toru, Aoki, Takafumi
Major retinal layer segmentation methods from OCT images assume that the retina is flattened in advance, and thus cannot always deal with retinas that have changes in retinal structure due to ophthalmopathy and/or curvature due to myopia. To eliminat
Externí odkaz:
http://arxiv.org/abs/2410.01185
Autor:
Dong, Yiwang, Deng, Xiangyu
The accurate segmentation of retinal vessels in fundus images is a great challenge in medical image segmentation tasks due to their highly complex structure from other organs.Currently, deep-learning based methods for retinal cessel segmentation achi
Externí odkaz:
http://arxiv.org/abs/2410.15444
Autor:
Zhang, Weiyi, Yang, Jiancheng, Chen, Ruoyu, Huang, Siyu, Xu, Pusheng, Chen, Xiaolan, Lu, Shanfu, Cao, Hongyu, He, Mingguang, Shi, Danli
Fundus fluorescein angiography (FFA) is crucial for diagnosing and monitoring retinal vascular issues but is limited by its invasive nature and restricted accessibility compared to color fundus (CF) imaging. Existing methods that convert CF images to
Externí odkaz:
http://arxiv.org/abs/2410.13242
Autor:
Wu, Yuli, Nguyen, Do Dinh Tan, Konermann, Henning, Yilmaz, Rüveyda, Walter, Peter, Stegmaier, Johannes
This study proposes a retinal prosthetic simulation framework driven by visual fixations, inspired by the saccade mechanism, and assesses performance improvements through end-to-end optimization in a classification task. Salient patches are predicted
Externí odkaz:
http://arxiv.org/abs/2410.11688
Autor:
Prenner, Andrea
Early detection of cardiovascular disease risk factors is essential to alter the course of the disease. Previous studies showed that deep learning can successfully be used to detect such risk factors from retinal images. This study uses convolutional
Externí odkaz:
http://arxiv.org/abs/2410.11535
Purpose: To investigate the changes in retinal vascular structures associated various stages of myopia by designing automated software based on an artif intelligencemodel. Methods: The study involved 1324 pediatric participants from the National Chil
Externí odkaz:
http://arxiv.org/abs/2409.20419
Autor:
Zoellin, Jay, Merk, Colin, Buob, Mischa, Saad, Amr, Giesser, Samuel, Spitznagel, Tahm, Turgut, Ferhat, Santos, Rui, Zhou, Yukun, Wagner, Sigfried, Keane, Pearse A., Tham, Yih Chung, DeBuc, Delia Cabrera, Becker, Matthias D., Somfai, Gabor M.
Integrating deep learning into medical imaging is poised to greatly advance diagnostic methods but it faces challenges with generalizability. Foundation models, based on self-supervised learning, address these issues and improve data efficiency. Natu
Externí odkaz:
http://arxiv.org/abs/2409.17332
Autor:
Quiros, Jose Vargas, Liefers, Bart, van Garderen, Karin, Vermeulen, Jeroen, Center, Eyened Reading, Consortium, Sinergia, Klaver, Caroline
We introduce VascX models, a comprehensive set of model ensembles for analyzing retinal vasculature from color fundus images (CFIs). Annotated CFIs were aggregated from public datasets for vessel, artery-vein, and disc segmentation; and fovea localiz
Externí odkaz:
http://arxiv.org/abs/2409.16016