scholarly journals Automatic Assesment of Pathological Disorder using Color Retinal Images

2019 ◽  
Vol 8 (4) ◽  
pp. 6610-6616
Keyword(s):  
Optic Disc ◽  
Retinal Images ◽  
Retinal Diseases ◽  
Body Structure ◽  
Color Intensity ◽  
Initial Stage ◽  
Yellow Color ◽  
Excretory Organ ◽  
Area Unit ◽  
Small Aneurysms

Our vision reduced in eye because of the presence of retinal diseases like Exudates(diabetic Retinopathy), small aneurysms and vessel harm. This project principally concentrates on the symptoms of heart, lung, liver and excretory organ issues identification mistreatment retina body structure pictures. Our planned work shows that however optic disc elimination and follower the symptom detection. Optic disc is one among the components that encompass intersection of blood vessels and it conjointly has same characteristics of exudates like yellow color, intensity and distinction. Distinguish the optic disc and exudates is crucial one. Thus solely initial eliminate the optic disc and follower that exudates detection. This detection methodology terribly favorably with existing and promise preparation of those systems small aneurysms area unit the initial stage of exudates.

scholarly journals Development of a Fundus Image-Based Deep Learning Diagnostic Tool for Various Retinal Diseases

2021 ◽  
Vol 11 (5) ◽  
pp. 321
Author(s):  
Kyoung Min Kim ◽  
Tae-Young Heo ◽  
Aesul Kim ◽  
Joohee Kim ◽  
Kyu Jin Han ◽  
...  
Keyword(s):  
Network Models ◽  
Retinal Disease ◽  
Age Related Macular Degeneration ◽  
Diagnostic Tools ◽  
Retinal Images ◽  
Dense Layer ◽  
Retinal Diseases ◽  
Fundus Image ◽  
Neural Network Models ◽  
Age Related

Artificial intelligence (AI)-based diagnostic tools have been accepted in ophthalmology. The use of retinal images, such as fundus photographs, is a promising approach for the development of AI-based diagnostic platforms. Retinal pathologies usually occur in a broad spectrum of eye diseases, including neovascular or dry age-related macular degeneration, epiretinal membrane, rhegmatogenous retinal detachment, retinitis pigmentosa, macular hole, retinal vein occlusions, and diabetic retinopathy. Here, we report a fundus image-based AI model for differential diagnosis of retinal diseases. We classified retinal images with three convolutional neural network models: ResNet50, VGG19, and Inception v3. Furthermore, the performance of several dense (fully connected) layers was compared. The prediction accuracy for diagnosis of nine classes of eight retinal diseases and normal control was 87.42% in the ResNet50 model, which added a dense layer with 128 nodes. Furthermore, our AI tool augments ophthalmologist’s performance in the diagnosis of retinal disease. These results suggested that the fundus image-based AI tool is applicable for the medical diagnosis process of retinal diseases.

Optic Disc Recognition Method for Retinal Images

2015 ◽  
pp. 875-889 ◽  
Author(s):  
Florin Rotaru ◽  
Silviu Ioan Bejinariu ◽  
Cristina Diana Niţă ◽  
Ramona Luca ◽  
Mihaela Luca ◽  
...  
Keyword(s):  
Optic Disc ◽  
Retinal Images ◽  
Recognition Method

scholarly journals The effect of grape ripening stage on red wine color

OENO One ◽  
2006 ◽  
Vol 40 (1) ◽  
pp. 15 ◽  
Author(s):  
Ana Belén Bautista-Ortín ◽  
José Ignacio Fernández-Fernández ◽  
José María López-Roca ◽  
Encarnación Gómez-Plaza
Keyword(s):  
Red Wine ◽  
Vitis Vinifera L ◽  
Cell Wall Degradation ◽  
Color Intensity ◽  
Fresh Weight ◽  
Physico Chemical ◽  
Yellow Color ◽  
Anthocyanin Concentration ◽  
Wine Color

<p style="text-align: justify;">The physico-chemical and chromatic characteristics of grapes (Vitis vinifera L. cv. Monastrell) harvested at six different degree of ripeness (from August 16 to October 24, 2002) and that of the wines obtained from these grapes have been studied. The grape anthocyanins content (mg/kg of berry fresh weight) was maximum in those grapes harvested on September 11 and 16 (804.1 and 822.6 mg/kg, respectively) and decreased for grapes harvested in October. However, the results showed that the grapes with the highest anthocyanin concentration did not lead to the highest colored wines. The wines elaborated from grapes harvested on October 16 (671.9 mg of anthocyanins per kg of berry fresh weight) had the best chromatic characteristics and better withstood aging in the bottle; the extent of cell wall degradation in overly matured grapes probably facilitated the extraction of phenolic compounds from skins. However, the chromatic quality of wines made from grapes harvested one week later (October 24, the most mature grapes) was lower than that from October 16, with lower color intensity (13%lower in the wine elaborated from grapes harvested in October 24) and a percentage of yellow color 6 % higher in this wine.</p>

scholarly journals Correlation Coefficient Based Automatic Optic Disc Detection from Retinal Images

2020 ◽  
Author(s):  
S. Anand ◽  
R. Prabhadevi ◽  
D. Rini
Keyword(s):  
Optic Disc ◽  
Correlation Coefficient ◽  
Retinal Image ◽  
Retinal Images ◽  
Detection Accuracy ◽  
Maximum Correlation ◽  
Exact Location ◽  
Peak Intensity ◽  
The Given

ABSTRACTIn this paper an algorithm to detect the optic disc (OD) automatically is described. The proposed method is based on the circular brightness of the OD and its correlation coefficient. At first the peak intensity points are taken, a mask is generated for the given image which gives the circular bright regions of the image. To locate the OD accurately, a pattern is generated which is similar to the OD. By correlating the retinal image with the pattern generated, the maximum correlation of the pattern with the OD is obtained. On locating the coordinates of maximum correlation, the exact location of the OD is detected. The proposed algorithm has been tested with DRIVE database images and an average OD detection accuracy of 95% was obtained for healthy and pathological retinas respectively.

Microperimetry in the diagnosis of early stages glaucoma

2021 ◽  
pp. 170-176
Author(s):  
I.A. Kazennova ◽  
◽  
A.D. Chuprov ◽  
A.E. Voronina ◽  
A.N. Kazennov ◽  
...  
Keyword(s):  
Optic Nerve ◽  
Optic Disc ◽  
Control Group ◽  
Ganglion Cell Complex ◽  
Macular Area ◽  
Healthy Individuals ◽  
Optic Nerve Atrophy ◽  
Early Stages ◽  
Initial Stage ◽  
Key Words Glaucoma

Purpose. To increase the efficiency of diagnostics of glaucomatous process in the early stages using microperimetry. Materials and methods. We examined 15 patients (30 eyes) aged 43-71 years (average age 62 years) with the initial stage of POAG, the duration of the disease was 8-36 months. The control group consisted of 10 patients (20 eyes), somatically healthy individuals without concomitant ophthalmopathology. In addition to standard research methods, the following were additionally carried out: optical coherence tomography (OCT) of the optic nerve disk, macular OCT for analyzing the thickness of the ganglion cell complex, angio-OCT of the optic disc and macula, and microperimetry. Results. When conducting microperimetric studies, a decrease in the average threshold photosensitivity AvThr (20 (4.8-23.3)) and the index of macular preservation MI (23 (2.8-26.8)) in patients with POAG was found in comparison with the control group. During OCT of the optic disc and macula, no changes were recorded in both groups, and there was no decrease in peripapillary perfusion during angio-OCT of the optic disc. However, in patients with POAG, during angio-OCT in the macular area, attention is drawn to some of its expansion and deformation, which confirms the fact that the macular area is involved in the glaucomatous process, which affects the photosensitivity of the cells of the central retinal area. Conclusion. Thus, the decrease in the average threshold of sensitivity in patients with POAG revealed by microperimetry makes it possible to detect glaucoma in the early stages, as well as to assess the dynamics of the glaucomatous process, which in its turn increases the effectiveness of treatment of patients. Key words: glaucoma, glaucomatous process progression, computer perimetry, microperimetry, optic nerve atrophy.

Examination of Optic Disc Sections of Fundus Retinal Images—A Study with Rim-One Database

2020 ◽  
pp. 711-719
Author(s):  
S. Fuzail Ahmed Razeen ◽  
Emmanuel ◽  
V. Rajinikanth ◽  
P. Tamizharasi ◽  
B. Parvatha Varthini
Keyword(s):  
Optic Disc ◽  
Retinal Images

Multicolor Retinal Imaging

2017 ◽  
pp. 12-16
Keyword(s):  
Optic Disc ◽  
New Technology ◽  
Retinal Imaging ◽  
Retinal Diseases ◽  
Screening Programs ◽  
Multicolor Imaging ◽  
Retinal Screening

Multicolor imaging is a new technology that provides retinal and optic disc imaging. Different layers of retina can be imaged by using three different wavelength lasers (blue, green, infrared). Retina can be seen in detail and clearly. As it aids in following up the retinal diseases by documenting the images, it has been started used in retinal screening programs.

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