Results 21 to 30 of about 2,892,707 (247)

Fractal dimension of retinal vasculature as an image quality metric for automated fundus image analysis systems

Scientific Reports, 2022
Automated fundus screening is becoming a significant programme of telemedicine in ophthalmology. Instant quality evaluation of uploaded retinal images could decrease unreliable diagnosis.
Xingzheng Lyu, Purvish Jajal, Muhammad Zeeshan Tahir, Sanyuan Zhang   +3 more
doaj   +1 more source

Accuracy and Utility of Internet Image Search as a Learning Tool for Retinal Pathology

Journal of Academic Ophthalmology, 2023
Purpose Ophthalmology residency training heavily relies on visual and pattern recognition-based learning. In parallel with traditional reference texts, online internet search via Google Image Search (GIS) is commonly used and offers an accessible fund of
Lucy V. Cobbs, Hytham Al-Hindi, Cherie Fathy, Raziyeh Mahmoudzadeh, Tara Uhler, David Xu   +5 more
doaj   +1 more source

Accurate and reliable segmentation of the optic disc in digital fundus images [PDF]

, 2014
We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based ...
Giachetti, Andrea, Emanuele Trucco, Trucco, Emanuele; id_orcid, Lucia Ballerini, Ballerini, Lucia   +4 more
core   +1 more source

Intelligent Diagnosis of Multiple Peripheral Retinal Lesions in Ultra-widefield Fundus Images Based on Deep Learning

Ophthalmology and Therapy, 2023
Introduction Compared with traditional fundus examination techniques, ultra-widefield fundus (UWF) images provide 200° panoramic images of the retina, which allows better detection of peripheral retinal lesions.
Tong Wang, Guoliang Liao, Lin Chen, Yan Zhuang, Sibo Zhou, Qiongzhen Yuan, Lin Han, Shanshan Wu, Ke Chen, Binjian Wang, Junyu Mi, Yunxia Gao, Jiangli Lin, Ming Zhang   +13 more
doaj   +1 more source

Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification [PDF]

, 2006
—We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel’s feature vector. Feature vectors are composed of the pixel’
Michael J. Cree, João V. B. Soares, Herbert F. Jelinek, Cesar, R.M., Jr., Jorge J. G. Le, Senior Member, Roberto M. Cesar, Jelinek, H.F., Soares, J.V.B., Leandro, J.J.G., Cree, Michael J.   +10 more
core   +1 more source

Evaluation of Retinal Optic Disc Segmentation in Patients with Glaucoma and Comparison with Other Methods of Medical Image Processing

مجله انفورماتیک سلامت و زیست پزشکی, 2021
Introduction: Glaucoma is the most common cause of blindness in some countries. In the meantime, the field of retinal image processing has been proposed in order to provide automatic systems for disease diagnosis.
Sahand Shahalinejad, Mehdi Nooshyar
doaj  

Presumed Bietti crystalline dystrophy with optic nerve head drusen: a case report

Journal of Medical Case Reports, 2022
Background Bietti crystalline dystrophy is primarily a retinal dystrophy caused by a CYP4V2 mutation and typically presents with crystalline retinal deposits in the posterior fundus.
Fatemeh Bazvand, Esmaeil Asadi Khameneh
doaj   +1 more source

Ensemble Learning Approach to Retinal Thickness Assessment in Optical Coherence Tomography

IEEE Access, 2021
Manual assessment of the retinal thickness in optical coherence tomography images is a time-consuming task, prone to error and inter-observer variability.
Alex Cazanas-Gordon, Esther Parra-Mora, Luis A. Da Silva Cruz   +2 more
doaj   +1 more source

Water flow based vessel detection in retinal images

, 2006
Previous vessel segmentation methods mainly concentrate on the general structure, and often ignore the accuracy, smoothness and continuity of vessel boundaries. A water flow based method is proposed to solve the problem. It embodies the fluidity of water
M.S. Nixon, Nixon, Mark S, Liu, Xin U, X.U. Liu   +3 more
core   +2 more sources

Spatial and spatio-temporal statistical analyses of retinal images: a review of methods and applications

BMJ Open Ophthalmology, 2020
Background Clinical research and management of retinal diseases greatly depend on the interpretation of retinal images and often longitudinally collected images. Retinal images provide context for spatial data, namely the location of specific pathologies
Simon Harding, Yalin Zheng, Gabriela Czanner, Ruwanthi Kolamunnage-Dona, Wenyue Zhu   +4 more
doaj   +1 more source