Similar articles for PMID: 30444873

Year	Number of Results
1987	1
1995	1
1997	1
1998	1
2004	2
2006	1
2007	4
2008	3
2009	2
2010	3
2011	4
2012	6
2013	3
2014	5
2015	9
2016	8
2017	16
2018	10
2019	3
2020	1
2024	0

1

Scan, dwell, decide: Strategies for detecting abnormalities in diabetic retinopathy.

Rangrej SB, Sivaswamy J, Srivastava P. Rangrej SB, et al. PLoS One. 2018 Nov 16;13(11):e0207086. doi: 10.1371/journal.pone.0207086. eCollection 2018. PLoS One. 2018. PMID: 30444873 Free PMC article.

2

An Eye Tracking Analysis on Diagnostic Performance of Digital Fundus Photography Images between Ophthalmologists and Optometrists.

Mohamad Shahimin M, Razali A. Mohamad Shahimin M, et al. Int J Environ Res Public Health. 2019 Dec 18;17(1):30. doi: 10.3390/ijerph17010030. Int J Environ Res Public Health. 2019. PMID: 31861457 Free PMC article.

3

Automatic detection of microaneurysms in retinal fundus images.

Wu B, Zhu W, Shi F, Zhu S, Chen X. Wu B, et al. Comput Med Imaging Graph. 2017 Jan;55:106-112. doi: 10.1016/j.compmedimag.2016.08.001. Epub 2016 Aug 4. Comput Med Imaging Graph. 2017. PMID: 27595214

4

Accuracy assessment of intra- and intervisit fundus image registration for diabetic retinopathy screening.

Adal KM, van Etten PG, Martinez JP, van Vliet LJ, Vermeer KA. Adal KM, et al. Invest Ophthalmol Vis Sci. 2015 Feb 3;56(3):1805-12. doi: 10.1167/iovs.14-15949. Invest Ophthalmol Vis Sci. 2015. PMID: 25650416

5

Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines.

Nazir T, Irtaza A, Shabbir Z, Javed A, Akram U, Mahmood MT. Nazir T, et al. Artif Intell Med. 2019 Aug;99:101695. doi: 10.1016/j.artmed.2019.07.003. Epub 2019 Jul 26. Artif Intell Med. 2019. PMID: 31606114

6

Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy.

Bawankar P, Shanbhag N, K SS, Dhawan B, Palsule A, Kumar D, Chandel S, Sood S. Bawankar P, et al. PLoS One. 2017 Dec 27;12(12):e0189854. doi: 10.1371/journal.pone.0189854. eCollection 2017. PLoS One. 2017. PMID: 29281690 Free PMC article.

7

Automatic recognition of severity level for diagnosis of diabetic retinopathy using deep visual features.

Abbas Q, Fondon I, Sarmiento A, Jiménez S, Alemany P. Abbas Q, et al. Med Biol Eng Comput. 2017 Nov;55(11):1959-1974. doi: 10.1007/s11517-017-1638-6. Epub 2017 Mar 28. Med Biol Eng Comput. 2017. PMID: 28353133

8

Detection of Hard Exudates in Colour Fundus Images Using Fuzzy Support Vector Machine-Based Expert System.

Jaya T, Dheeba J, Singh NA. Jaya T, et al. J Digit Imaging. 2015 Dec;28(6):761-8. doi: 10.1007/s10278-015-9793-5. J Digit Imaging. 2015. PMID: 25822397 Free PMC article.

9

Evaluation of automated fundus photograph analysis algorithms for detecting microaneurysms, haemorrhages and exudates, and of a computer-assisted diagnostic system for grading diabetic retinopathy.

Dupas B, Walter T, Erginay A, Ordonez R, Deb-Joardar N, Gain P, Klein JC, Massin P. Dupas B, et al. Diabetes Metab. 2010 Jun;36(3):213-20. doi: 10.1016/j.diabet.2010.01.002. Epub 2010 Mar 10. Diabetes Metab. 2010. PMID: 20219404

10

Determination of foveal avascular zone in diabetic retinopathy digital fundus images.

Ahmad Fadzil MH, Izhar LI, Nugroho HA. Ahmad Fadzil MH, et al. Comput Biol Med. 2010 Jul;40(7):657-64. doi: 10.1016/j.compbiomed.2010.05.004. Epub 2010 Jun 22. Comput Biol Med. 2010. PMID: 20573343

Save citations to file

Email citations

Send citations to clipboard

Add to Collections

Add to My Bibliography

Create a file for external citation management software

Your saved search

Your RSS Feed

My NCBI Filters

Results by year

Text availability

Article attribute

Article type

Publication date

70 results

Results by year