An Automated Approach for Localizing Retinal Blood Vessels in Confocal Scanning Laser Ophthalmoscopy Fundus Images.
In this work, we present a rules-based method for localizing retinal blood vessels in confocal scanning laser ophthalmoscopy (cSLO) images and evaluate its feasibility. A total of 31 healthy participants (17 female; mean age: 64.0 ± 8.2 years) were studied using manual and automatic segmentation. High-resolution peripapillary scan acquisition cSLO images were acquired. The automated segmentation method consisted of image pre-processing for gray-level homogenization and blood vessel enhancement (morphological opening operation, Gaussian filter, morphological Top-Hat transformation), binary thresholding (entropy-based thresholding operation), and removal of falsely detected isolated vessel pixels. The proposed algorithm was first tested on the publically available dataset DRIVE, which contains color fundus photographs, and compared to performance results from the literature. Good results were obtained. Monochromatic cSLO images segmented using the proposed method were compared to those manually segmented by two independent observers. For the algorithm, a sensitivity of 0.7542, specificity of 0.8607, and accuracy of 0.8508 were obtained. For the two independent observers, a sensitivity of 0.6579, specificity of 0.9699, and accuracy of 0.9401 were obtained. The results demonstrate that it is possible to localize vessels in monochromatic cSLO images of the retina using a rules-based approach. The performance results are inferior to those obtained using fundus photography, which could be due to the nature of the technology.
Department of Ophthalmology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany.
Robert
R
Kromer
Department of Computer Science, University of Manitoba, Winnipeg, Canada.
Rahman
R
Shafin
Department of Ophthalmology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany.
Sebastian
S
Boelefahr
Department of Ophthalmology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246 Hamburg, Germany.
Maren
M
Klemm
Blood vessel; Confocal scanning laser ophthalmoscopy (cSLO); Image processing; Retinal imaging; Retinal nerve fiber layer
Appl Opt. 1987 Apr 15;26(8):1492-9
20454349
Med Biol Eng Comput. 2002 Jan;40(1):2-13
11954703
Comput Methods Programs Biomed. 2009 Nov;96(2):85-95
19419790
IEEE Trans Med Imaging. 2006 Sep;25(9):1214-22
16967806
IEEE Trans Med Imaging. 2000 Mar;19(3):203-10
10875704
IEEE Trans Med Imaging. 2011 Jan;30(1):146-58
20699207
Med Image Anal. 2007 Dec;11(6):555-66
17950655
IEEE Trans Med Imaging. 1998 Apr;17(2):263-73
9688158
Invest Ophthalmol Vis Sci. 2003 Jul;44(7):2900-4
12824229
IEEE Trans Med Imaging. 2004 Apr;23(4):501-9
15084075
IEEE Trans Med Imaging. 1994;13(4):619-26
18218540
J Med Syst. 2010 Oct;34(5):849-58
20703624
IEEE Trans Med Imaging. 2007 Oct;26(10):1357-65
17948726
IEEE Trans Biomed Eng. 2002 Feb;49(2):168-72
12066884
IEEE Trans Med Imaging. 2004 Oct;23(10):1196-204
15493688
Br J Ophthalmol. 1999 Aug;83(8):902-10
10413690
IEEE Trans Med Imaging. 1989;8(3):263-9
18230524
IEEE Trans Inf Technol Biomed. 1999 Jun;3(2):125-38
10719494
JAMA. 2002 Mar 6;287(9):1153-9
11879113
PLoS One. 2014 Sep 09;9(9):e102034
25203135
Comput Methods Programs Biomed. 2012 Oct;108(1):407-33
22525589
Comput Methods Programs Biomed. 2012 Nov;108(2):600-16
21963241
IEEE Trans Image Process. 2001;10(7):1010-9
18249674
Br J Ophthalmol. 1992 Aug;76(8):470-4
1390528
Med Image Anal. 2002 Dec;6(4):407-29
12426111
IEEE Trans Biomed Eng. 2004 Feb;51(2):246-54
14765697
Br J Ophthalmol. 1996 Nov;80(11):940-4
8976718
IEEE Trans Med Imaging. 2006 Sep;25(9):1200-13
16967805
IEEE Trans Med Imaging. 1993;12(2):334-41
18218423
Comput Methods Programs Biomed. 2007 Sep;87(3):248-53
17610985
IEEE Trans Med Imaging. 1999 May;18(5):419-28
10416803
Comput Biol Med. 2007 Feb;37(2):262-7
16697363
Appl Opt. 1980 Sep 1;19(17):2991-7
20234539
Med Image Anal. 2000 Jun;4(2):73-91
10972323