Computer-aided diagnosis of plus disease via measurement of vessel thickness in retinal fundus images of preterm infants

Computers in Biology and Medicine

Volumn 66, Issue , 2015, Pages 316-329

  Oloumi, Faraz ^a   Rangayyan, Rangaraj M ^a   Casti, Paola ^b   Ells, Anna L ^a,c  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY OF ROME TOR VERGATA   (Italy)

^c ALBERTA CHILDREN'S HOSPITAL   (Canada)

Author keywords

Computer aided diagnosis; Gabor filters; Plus disease; Retinal blood vessels; Retinal fundus images; Retinopathy of prematurity; Temporal arcade; Vessel width

Indexed keywords

ARCHES; BLOOD VESSELS; DIAGNOSIS; DISEASES; EYE PROTECTION; GABOR FILTERS; IMAGE PROCESSING; IMAGE SEGMENTATION; LEAST SQUARES APPROXIMATIONS; OPHTHALMOLOGY;

RETINAL BLOOD VESSELS; RETINAL FUNDUS IMAGES; RETINOPATHY OF PREMATURITY; TEMPORAL ARCADE; VESSEL WIDTH;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE SEVERITY; EYE FUNDUS; HUMAN; IMAGE PROCESSING; INFANT; PLUS DISEASE; PREMATURITY; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RETINA BLOOD VESSEL; RETROLENTAL FIBROPLASIA; AREA UNDER THE CURVE; FACTUAL DATABASE; FEMALE; MALE; NEWBORN; PATHOLOGY; PROCEDURES; RETINOPATHY OF PREMATURITY;

AREA UNDER CURVE; DATABASES, FACTUAL; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; FUNDUS OCULI; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; INFANT, NEWBORN; INFANT, PREMATURE; MALE; RETINAL VESSELS; RETINOPATHY OF PREMATURITY; ROC CURVE;

EID: 84943628767     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2015.09.009     Document Type: Article

References (58)

1. Narasimha-Iyer H., Can A., Roysam B., Stewart C.V., Tanenbaum H.L., Majerovics A., Singh H. Robust detection and classification of longitudinal changes in color retinal fundus images for monitoring diabetic retinopathy. IEEE Trans. Biomed. Eng. 2006, 53(6):1084-1098.
2. Fleming A.D., Goatman K.A., Philip S., Olson J.A., Sharp P.F. Automatic detection of retinal anatomy to assist diabetic retinopathy screening. Phys. Med. Biol. 2007, 52:331-345.
3. M.D. Abràmoff, M. Niemeijer, Detecting retinal pathology automatically with special emphasis on diabetic retinopathy, in: H.F. Jelinek, M.J. Cree (Eds.), Automated Image Detection of Retinal Pathology, CRC Press, Boca Raton, FL, 2010, pp. 67-78.
4. Oloumi F., Rangayyan R.M., Ells A.L. Computer-aided diagnosis of proliferative diabetic retinopathy via modeling of the major temporal arcade in retinal fundus images. J. Digit. Imaging 2013, 26(6):1124-1130.
5. Jaafar H.F., Nandi A.K., Al-Nuaimy W. Decision support system for the detection and grading of hard exudates from color fundus photographs. J. Biomed. Opt. 2011, 16(11):116001.
6. Wallace D.K., Jomier J., Aylward S.R., Landers M.B. Computer-automated quantification of plus disease in retinopathy of prematurity. J. Am. Assoc. Pediatr. Ophthalmol. Strabismus 2003, 7:126-130.
7. Heneghan C., Flynn J.T., O'Keefe M., Cahill M. Characterization of changes in blood vessels width and tortuosity in retinopathy of prematurity using image analysis. Med. Image Anal. 2002, 6(1):407-429.
8. Grisan E., Foracchia M., Ruggeri A. A novel method for the automatic grading of retinal vessel tortuosity. IEEE Trans. Med. Imaging 2008, 27(3):310-319.
9. Muramatsu C., Hayashi Y., Sawada A., Hatanaka Y., Hara T., Yamamoto T., Fujita H. Detection of retinal nerve fiber layer defects on retinal fundus images for early diagnosis of glaucoma. J. Biomed. Opt. 2010, 15:016021.
10. Muramatsu C., Nakagawa T., Sawada A., Hatanaka Y., Yamamoto T., Fujita H. Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images. J. Biomed. Opt. 2011, 16(9):096009.
11. Niemeijer M., Xu X., Dumitrescu A.V., Gupta P., van Ginneken B., Folk J.C., Abràmoff M.D. Automated measurement of the arteriolar-to-venular width ratio in digital color fundus photographs. IEEE Trans. Med. Imaging 2011, 30(11):1941-1950.
12. Bhuiyan A., Karmakar C., Kawasaki R., Lamoureux E., Ramamohanarao K., Kanagasingam Y., Wong T.Y. Retinal artery and venular caliber grading. a semi-automated evaluation tool. Comput. Biol. Med. 2014, 44:1-9.
13. Kristinsson J.K., Gottfredsdóttir M.S., Stefánsson E. Retinal vessel dilatation and elongation precedes diabetic macular oedema. Br. J. Ophthalmol. 1997, 81(4):274-278.
14. Early Treatment Diabetic Retinopathy Study Research Group, Fundus photographic risk factors for progression of diabetic retinopathy, Ophthalmology 98 (5) (1991) 823-833.
15. Pedersen L., Grunkin M., Ersbøll B., Madsen K., Larsen M., Christoffersen N., Skands U. Quantitative measurement of changes in retinal vessel diameter in ocular fundus images. Pattern Recognit. Lett. 2000, 21:1215-1223.
16. Swanson C., Cocker K.D., Parker K.H., Moseley M.J., Fielder A.R. Semiautomated computer analysis of vessel growth in preterm infants without and with ROP. Br. J. Ophthalmol. 2003, 87(12):1474-1477.
17. Wilson C.M., Cocker K.D., Moseley M.J., Paterson C., Clay S.T., Schulenburg W.E., Mills M.D., Ells A.L., Parker K.H., Quinn G.E., Fielder A.R., Ng J. Computerized analysis of retinal vessel width and tortuosity in premature infants. Investig. Ophthalmol. Vis. Sci. 2008, 49(1):3577-3585.
18. Koreen S., Gelman R., Martínez-Pérez M.E., Jiang L., Berrocal A.M., Hess D.J., Flynn J.T., Chiang M.F. Evaluation of a computer-based system for plus disease diagnosis in retinopathy of prematurity. Ophthalmology 2007, 114(12):59-67.
19. Wong T.Y., Klein R., Klein B.E.K., Tielsch J.M., Hubbard L., Nieto F.J. Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease, and mortality. Surv. Ophthalmol. 2001, 46(1):59-80.
20. Early Treatment for Retinopathy of Prematurity Cooperative Group, Revised indications for the treatment of retinopathy of prematurity: results of the early treatment for retinopathy of prematurity randomized trial, Arch. Ophthalmol. 121 (2003) 1684-1696.
21. Davitt B.V., Wallace D.K. Plus disease. Surv. Ophthalmol. 2009, 54(6):663-670.
22. Chiang M.F., Jiang L., Gelman R., Du Y.E., Flynn J.T. Interexpert agreement of plus disease diagnosis in retinopathy of prematurity. Arch. Ophthalmol. 2007, 125(7):875-880.
23. Gelman R., Jiang L., Du Y.E., Martínez-Pérez M.E., Flynn J.T., Chiang M.F. Plus disease in retinopathy of prematurity. pilot study of computer-based and expert diagnosis. J. Am. Assoc. Pediatr. Ophthalmol. Strabismus 2007, 11(6):532-540.
24. Ells A.L., Holmes J.M., Astle W.F., Williams G., Leske D.A., Fielden M., Uphill B., Jennett P., Hebert M. Telemedicine approach to screening for severe retinopathy of prematurity. a pilot study. Am. Acad. Ophthalmol. 2003, 110(11):2113-2117.
25. International Committee for the Classification of Retinopathy of Prematurity, The international classification of retinopathy of prematurity revisited, Arch. Ophthalmol. 123 (2005) 991-999.
26. Oloumi F., Rangayyan R.M., Ells A.L. Quantification of the changes in the openness of the major temporal arcade in retinal fundus images of preterm infants with plus disease. Investig. Ophthalmol. Vis. Sci. 2014, 55(10):6728-6735.
27. Hartnett M.E., Martiniuk D., Byfield G., Geisen P., Zeng G., Bautch V.L. Neutralizing VEGF decreases tortuosity and alters endothelial cell division orientation in arterioles and veins in a rat model of ROP. relevance to plus disease. Investig. Ophthalmol. Vis. Sci. 2008, 49(7):3107-3114.
28. Erb M.H., Sioulis C.E., Kuppermann B.D., Osann K., Wong C.G. Differential retinal angiogenic response to sustained intravitreal release of VEGF and bFGF in different pigmented rabbit breeds. Current Eye Res. 2002, 24(4):245-252.
29. Schaffer D.B., Palmer E.A., Plotsky D.F., Metz H.F., Flynn J.T., Tung B., Hardy R.J. Prognostic factors in the natural course of retinopathy of prematurity. Cryotherapy for retinopathy of prematurity cooperative group. Ophthalmology 1993, 100:230-237.
30. Johnston S.C., Wallace D.K., Freedman S.F., Yanovitch T.L., Zhao Z. Tortuosity of arterioles and venules in quantifying plus disease. J. Am. Assoc. Pediatr. Ophthalmol. Strabismus 2009, 13(2):181-185.
31. Gelman R., Martínez-Pérez M.E., Vanderveen D.K., Moskowitz A., Fulton A.B. Diagnosis of plus disease in retinopathy of prematurity using retinal image multiscale analysis. Investig. Ophthalmol. Vis. Sci. 2005, 46(12):4734-4738.
32. Thyparampil J.P., Park Y., Martínez-Pérez M.E., Lee T.C., Weissgold D.J., Berrocal A.M., Chan R.V.P., Flynn J.T., Chiang M.F. Plus disease in retinopathy of prematurity. quantitative analysis of vascular change. Am. J. Ophthalmol. 2010, 150(4):468-475.
33. D. Fiorin, A. Ruggeri, Computerized analysis of narrow-field ROP images for the assessment of vessel caliber and tortuosity, in: 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, 2011, pp. 2622-2625.
34. Lowell J., Hunter A., Steel D., Basu A., Ryder R., Kennedy R.L. Measurement of retinal vessel widths from fundus images based on 2-D modeling. IEEE Trans. Med. Imaging 2004, 23(10):1196-1204.
35. M.E. Martínez-Pérez, A.D. Hughes, A.V. Stanton, S.A. Thom, A.A. Bharath, K.H. Parker, Retinal blood vessel segmentation by means of scale-space analysis and region growing, in: Medical Image Computing and Computer-Assisted Intervention-MICCAI99, 1999, pp. 90-97.
36. Martínez-Pérez M.E., Hughes A.D., Stanton A.V., Thom S.A., Chapman N., Bharath A.A., Parker K.H. Retinal vascular tree morphology. a semi-automatic quantification. IEEE Trans. Biomed. Eng. 2002, 49(8):912-917.
37. Gang L., Chutatape O., Krishnan S.M. Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter. IEEE Trans. Biomed. Eng. 2002, 49(2):168-172.
38. Ayres F.J., Rangayyan R.M. Characterization of architectural distortion in mammograms. IEEE Eng. Med. Biol. Mag. 2005, 24(1):59-67.
39. Han W.-Y., Lee J.-C. Palm vein recognition using adaptive Gabor filter. Expert Syst. Appl. 2012, 39(18):13225-13234.
40. Dantas R.G., Costa E.T. Ultrasound speckle reduction using modified Gabor filters. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 2007, 54(3):530-538.
41. Banik S., Rangayyan R.M., Desautels J.E.L. Detection of architectural distortion in prior mammograms. IEEE Trans. Med. Imaging 2011, 30(2):279-294.
42. Soares J.V.B., Leandro J.J.G., Cesar R.M., Jelinek H.F., Cree M.J. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Trans. Med. Imaging 2006, 25(9):1214-1222.
43. R.M. Rangayyan, F.J. Ayres, F. Oloumi, F. Oloumi, P. Eshghzadeh-Zanjani, Detection of blood vessels in the retina with multiscale Gabor filters, J. Electron.Imaging 17 (April-June) (2008) 023018:1-7.
44. F. Oloumi, R.M. Rangayyan, A.L. Ells, Measurement of vessel width in retinal fundus images of preterm infants with plus disease, in: Proceedings of 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Lisbon, Portugal, 2014, pp. 1-5.
45. P.L. Hildebrand, A.L. Ells, A.D. Ingram, The impact of telemedicine integration on resource use in the evaluation ROP-analysis of the telemedicine for ROP in Calgary (TROPIC) database, Investig. Ophthalmol. Vis. Sci. 50 (2009) E-Abstract 3151.
46. Silva D.J.D., Cocker K.D., Lau G., Clay S.T., Fielder A.R., Moseley M.J. Optic disk size and optic disk-to-fovea distance in preterm and full-term infants. Investig. Ophthalmol. Vis. Sci. 2006, 47(11):4683-4686.
47. Şevik U., Köse C., Berber T., Erdöl H. Identification of suitable fundus images using automated quality assessment methods. J. Biomed. Opt. 2014, 19(4):046006.
48. F. Oloumi, R.M. Rangayyan, A.L. Ells, A graphical user interface for measurement of temporal arcade angles in fundus images of the retina, in: Proceedings of IEEE 25th Annual Canadian Conference on Electrical and Computer Engineering (CCECE), Montreal, QC, Canada, 2012, pp. 4 on CD-ROM.
49. Rangayyan R.M., Zhu X., Ayres F.J., Ells A.L. Detection of the optic nerve head in fundus images of the retina with Gabor filters and phase portrait analysis. J. Digit. Imaging 2010, 23(4):438-453.
50. R.M. Rangayyan, Biomedical Image Analysis, CRC, Boca Raton, FL, 2005.
51. Tsai W.-H. Moment-preserving thresolding. a new approach. Comput. Vis. Graph. Image Process. 1985, 29(3):377-393.
52. C. Arcelli, G.S. di Baja, Skeletons of planar patterns, in: T. Kong, A. Rosenfeld (Eds.), Topological Algorithms for Digital Image Processing, Machine Intelligence and Pattern Recognition, vol. 19, North-Holland, Amsterdam, The Netherlands, 1996, pp. 99-143.
53. Oloumi F., Dhara A.K., Rangayyan R.M., Mukhopadhyay S. Detection of blood vessels in retinal fundus images (invited paper). Comput. Sci. J. Mold. 2014, 22(2):155-185.
54. Pham-Gia T., Hung T. The mean and median absolute deviations. Math. Comput. Model. 2001, 34(7-8):921-936.
55. Delori F.C., Fitch K.A., Feke G.T., Deupree D.M., Weiter J.J. Evaluation of micrometric and microdensitometric methods for measuring the width of retinal vessel images on fundus photographs. Graefe's Arch. Clin. Exp. Ophthalmol. 1988, 226(4):293-299.
56. Euvrard G., Genevois O., Rivals I., Massin P., Collet A., Sahel J.-A., Paques M. A semi-automated computer tool for the analysis of retinal vessel diameter dynamics. Comput. Biol. Med. 2013, 43(5):512-523.
57. Fathi A., Naghsh-Nilchi A.R., Mohammadi F.A. Automatic vessel network features quantification using local vessel pattern operator. Comput. Biol. Med. 2013, 43(5):587-593.
58. F. Oloumi, R.M. Rangayyan, A.L. Ells, Computer-aided diagnosis of plus disease in retinal fundus images of preterm infants via measurement of vessel tortuosity, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Milan, Italy, 2015.