Chandhakanond P, Aimmanee P
Sci Rep. 2025; 15(1):5541.
PMID: 39953248
PMC: 11829032.
DOI: 10.1038/s41598-025-90048-6.
Kaur J, Mittal D, Malebary S, Nayak S, Kumar D, Kumar M
J Healthc Eng. 2023; 2023:4537253.
PMID: 37483301
PMC: 10361834.
DOI: 10.1155/2023/4537253.
Wei Q, Qiu W, Liu Q, Jiang Y
Int J Gen Med. 2022; 15:6021-6029.
PMID: 35818578
PMC: 9270927.
DOI: 10.2147/IJGM.S366348.
Erciyas A, Barisci N
Comput Math Methods Med. 2021; 2021:9928899.
PMID: 34194538
PMC: 8184323.
DOI: 10.1155/2021/9928899.
Alharithi F, Almulihi A, Bourouis S, Alroobaea R, Bouguila N
Sensors (Basel). 2021; 21(7).
PMID: 33918120
PMC: 8036303.
DOI: 10.3390/s21072450.
The SUSTech-SYSU dataset for automated exudate detection and diabetic retinopathy grading.
Lin L, Li M, Huang Y, Cheng P, Xia H, Wang K
Sci Data. 2020; 7(1):409.
PMID: 33219237
PMC: 7679367.
DOI: 10.1038/s41597-020-00755-0.
Detection of Early Signs of Diabetic Retinopathy Based on Textural and Morphological Information in Fundus Images.
Colomer A, Igual J, Naranjo V
Sensors (Basel). 2020; 20(4).
PMID: 32069912
PMC: 7071097.
DOI: 10.3390/s20041005.
A region growing and local adaptive thresholding-based optic disc detection.
Khan T, Mehmood M, Naqvi S, Butt M
PLoS One. 2020; 15(1):e0227566.
PMID: 31999720
PMC: 6991997.
DOI: 10.1371/journal.pone.0227566.
Network-based features for retinal fundus vessel structure analysis.
Amil P, Reyes-Manzano C, Guzman-Vargas L, Sendina-Nadal I, Masoller C
PLoS One. 2019; 14(7):e0220132.
PMID: 31344132
PMC: 6658152.
DOI: 10.1371/journal.pone.0220132.
Sensitivity and specificity of computer vision classification of eyelid photographs for programmatic trachoma assessment.
Kim M, Okada K, Ryner A, Amza A, Tadesse Z, Cotter S
PLoS One. 2019; 14(2):e0210463.
PMID: 30742639
PMC: 6370195.
DOI: 10.1371/journal.pone.0210463.
Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms.
Khojasteh P, Aliahmad B, Kumar D
BMC Ophthalmol. 2018; 18(1):288.
PMID: 30400869
PMC: 6219077.
DOI: 10.1186/s12886-018-0954-4.
Detection of exudates in fundus photographs with imbalanced learning using conditional generative adversarial network.
Zheng R, Liu L, Zhang S, Zheng C, Bunyak F, Xu R
Biomed Opt Express. 2018; 9(10):4863-4878.
PMID: 30319908
PMC: 6179403.
DOI: 10.1364/BOE.9.004863.
Retinal Vascular Imaging in Vascular Cognitive Impairment: Current and Future Perspectives.
Dumitrascu O, Qureshi T
J Exp Neurosci. 2018; 12:1179069518801291.
PMID: 30262988
PMC: 6149015.
DOI: 10.1177/1179069518801291.
Remote examination of exudates-impact of macular oedema.
Punniyamoorthy U, Pushpam I
Healthc Technol Lett. 2018; 5(4):118-123.
PMID: 30155263
PMC: 6103783.
DOI: 10.1049/htl.2017.0026.
A Random Forest classifier-based approach in the detection of abnormalities in the retina.
Chowdhury A, Chatterjee T, Banerjee S
Med Biol Eng Comput. 2018; 57(1):193-203.
PMID: 30076537
DOI: 10.1007/s11517-018-1878-0.
Automated Diagnosis and Grading of Diabetic Retinopathy Using Optical Coherence Tomography.
Sandhu H, Eltanboly A, Shalaby A, Keynton R, Schaal S, El-Baz A
Invest Ophthalmol Vis Sci. 2018; 59(7):3155-3160.
PMID: 30029278
PMC: 6018370.
DOI: 10.1167/iovs.17-23677.
Automated segmentation of hyperreflective foci in spectral domain optical coherence tomography with diabetic retinopathy.
Okuwobi I, Fan W, Yu C, Yuan S, Liu Q, Zhang Y
J Med Imaging (Bellingham). 2018; 5(1):014002.
PMID: 29430477
PMC: 5800482.
DOI: 10.1117/1.JMI.5.1.014002.
Semi-automated quantification of hard exudates in colour fundus photographs diagnosed with diabetic retinopathy.
Marupally A, Vupparaboina K, Peguda H, Richhariya A, Jana S, Chhablani J
BMC Ophthalmol. 2017; 17(1):172.
PMID: 28931389
PMC: 5607622.
DOI: 10.1186/s12886-017-0563-7.
Retina Image Vessel Segmentation Using a Hybrid CGLI Level Set Method.
Chen G, Chen M, Li J, Zhang E
Biomed Res Int. 2017; 2017:1263056.
PMID: 28840122
PMC: 5559923.
DOI: 10.1155/2017/1263056.
Automatic optic disk detection in retinal images using hybrid vessel phase portrait analysis.
Muangnak N, Aimmanee P, Makhanov S
Med Biol Eng Comput. 2017; 56(4):583-598.
PMID: 28836125
DOI: 10.1007/s11517-017-1705-z.