nach oben

Medical & Biological Engineering & Computing

Erschienen in:

01.06.2011 | Original Article

Analysis of retinal fundus images for grading of diabetic retinopathy severity

verfasst von: M. H. Ahmad Fadzil, Lila Iznita Izhar, Hermawan Nugroho, Hanung Adi Nugroho

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 6/2011

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Diabetic retinopathy (DR) is a sight threatening complication due to diabetes mellitus that affects the retina. In this article, a computerised DR grading system, which digitally analyses retinal fundus image, is used to measure foveal avascular zone. A v-fold cross-validation method is applied to the FINDeRS database to evaluate the performance of the DR system. It is shown that the system achieved sensitivity of >84%, specificity of >97% and accuracy of >95% for all DR stages. At high values of sensitivity (>95%), specificity (>97%) and accuracy (>98%) obtained for No DR and severe NPDR/PDR stages, the computerised DR grading system is suitable for early detection of DR and for effective treatment of severe cases.

Vorheriger Artikel BMP7 induces the differentiation of bone marrow-derived mesenchymal cells into chondrocytes

Nächster Artikel Biological surface modification of titanium surfaces using glow discharge plasma

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Ahmad Fadzil MH, Izhar LI (2008) A non-Invasive method for analysing the retina for ocular manifested diseases. Patent filing no. PI20083503 September, 2008 ed. Malaysia, v. patent filing no. PI20083503 September, 2008

Ahmad Fadzil MH, Lila Iznita I (2009) A non-Invasive method for analysing the retina for ocular manifested diseases. Patent filing no. PCT/MY2009/000025 2009 ed. Malaysia, v. patent filing no. PCT/MY2009/000025 2009

Ahmad Fadzil MH, Lila Iznita I (2009) An apparatus for monitoring and grading diabetic retinopathy. Patent filing no. PI20091936 May, 2009 ed. Malaysia, v. patent filing no. PI20091936 May, 2009

Ahmad Fadzil MH, Nugroho HA, Venkatachalam PA, et al (2008) Determination of retinal pigments from fundus images using independent component analysis. In: Proceeding of biomed 2008 4th Kuala Lumpur international conference on biomedical engineering vol 21. Springer, Berlin Heidelberg, 2008

Ahmad Fadzil MH, Nugroho HA (2009) Retinal vasculature enhancement using independent component analysis. J Biomed Sci Eng 2:543–549CrossRef

Ahmad Fadzil MH, Izhar LI, Venkatachalam PA, Karunakar TVN (2007) Extraction and reconstruction of retinal vasculature. J Med Eng Tech 31:435–442CrossRef

Ahmad Fadzil MH, Lila Iznita I, Nugroho HA (2009) Analysis of foveal avascular zone in color fundus image for grading of diabetic retinopathy. Int J Recent Trends Eng 2:101–104

American academy of ophthalmology retina panel. Preferred practice pattern guidelines. Diabetic retinopathy. American Academy of Ophthalmology San Francisco, CA. http://www.aao.org/ppp

Bradley A, Applegate RA, Zeffren BS, Heuven WAJ (1992) Psychophysical measurement of the size and shape of the human foveal avascular zone. Ophthal Physiol Opt 12:18–23CrossRef

10.

Bresnick GH, Condit R, Syrjala S et al (1984) Abnormalities of the foveal avascular zone in diabetic retinopathy. Arch Ophthalmol 102:1286–1293PubMed

11.

Comon P (1994) Independent component analysis, a new concept? Signal Process 36:287CrossRef

12.

Conrath J, Giorgi R, Raccah D, Ridings B (2004) Foveal avascular zone in diabetic retinopathy: quantitative vs qualitative assessment. Eye 19:322–326CrossRef

13.

Conrath J, Valat O, Giorgi R et al (2006) Semi-automated detection of the foveal avascular zone in fluorescein angiograms in diabetes mellitus. Clin Exp Ophthalmol 34:119–123CrossRef

14.

Duda RO, Hart PE, Stork DG (2001) Pattern classification. Wiley, New York

15.

Fadzil MHA, Lila Iznita I, Hanung Adi N (2010) Determination of foveal avascular zone in diabetic retinopathy digital fundus images. Comput Biol Med 40:657–664CrossRef

16.

Goh PP (2008) Status of diabetic retinopathy among diabetics registered to the diabetic eye registry, National eye database, 2007. Med J Malaysia 63:24–28PubMed

17.

Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29–36PubMed

18.

Hyvarinen A, Oja E (2000) Independent component analysis: algorithms and applications. Neural Networks 13:411PubMedCrossRef

19.

Izenman AJ (2008) Modern multivariate statistical techniques: regression, classification, and manifold learning. Springer New York, Berlin

20.

Iznita L (2006) Analysis of retinal vasculature and foveal avascular zone for grading of diabetic retinopathy. M.Sc. Thesis, Universiti Teknologi PETRONAS, Electrical and electronics engineering programme. Bandar Seri Iskandar, Malaysia

21.

Jelinek HF, Cree MJ, Leandro JJG et al (2007) Automated segmentation of retinal blood vessels and identification of proliferative diabetic retinopathy. J Opt Soc Am A 24:1448–1456CrossRef

22.

John D, Braganza A, Kuriakose T (2006) A study of the foveal avascular zone using the Heidelberg retina angiogram-2 in normal eyes. In: Proceedings 34th all India optometry conference (AIOC 2008) Amritsar, India

23.

Kahai P, Namuduri KR, Thompson H (2004) Decision support for automated screening of diabetic retinopathy. Conference on signals, systems and computers, vol 2. Conference record of the thirty-eighth asilomar

24.

Kahai P, Namuduri KR, Thompson H (2006) A decision support framework for automated screening of diabetic retinopathy. Int J Biomed Imaging 2006:1–7CrossRef

25.

Khurana AK (2003) Ophthalmology. New Age International Publishers, New Delhi

26.

Mansour AM (1990) Measuring fundus landmark. Invest Ophthalmol Vis Sci 31:41–42PubMed

27.

Metz C (2008) ROC analysis in medical imaging: a tutorial review of the literature. Radiol Phys Technol 1:2–12PubMedCrossRef

28.

Micheli-Tzanakou E (2000) Supervised and unsupervised pattern recognition: feature extraction and computational intelligence. CRC Press, Boca Raton

29.

Mitchell TM (1997) Machine Learning. McGraw-Hill, New York

30.

Nayak J, Bhat P, Acharya UR et al (2008) Automated identification of diabetic retinopathy stages using digital fundus images. J Med Syst 32:107–115PubMedCrossRef

31.

Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9:62–66CrossRef

32.

Parodi MB, Visintin F, Rupe PD, Ravalico G (1995) Foveal avascular zone in macular branch retinal vein occlusion. Int Ophthalmol 19:25–28PubMedCrossRef

33.

Pratt WK (1978) Digital image processing. Wiley, New York

34.

Rasmussen CE, Williams CKI (2006) Gaussian processes for machine learning. MIT, Cambridge, Mass

35.

Richard G, Soubrane Gl, Yannuzzi LA, Courland S (1998) Fluorescein and ICG angiography. Thieme Medical, New York

36.

Saini VK, Varma P, Bhaisare V, et al. Foveal Avascular Zone Calculation and its Variation with Different Posterior Segment Diseases and Analysis of its Impact on Best Corrected Visual Acuity. In: Bhattacharyya DD, AIOC 2006. Bhopal, India, 2006; v. 4

37.

Sopharak A, Uyyanonvara B, Barman S, Williamson TH (2008) Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods. Comput Med Imaging Graph 32:720–727PubMedCrossRef

38.

Stone M (1974) Cross-validatory choice and assessment of statistical predictions. J Royal Stat Soc B 36:111–147

39.

Walter T, Klein J-C, Massin P, Erginay A (2002) A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina. IEEE Trans Med Imaging 21:1236–1243PubMedCrossRef

40.

Yun WL, Rajendra Acharya U, Venkatesh YV et al (2008) Identification of different stages of diabetic retinopathy using retinal optical images. Inf Sci 178:106–121CrossRef

41.

Zeffren B, Applegate R, Bradley A, van Heuven W (1990) Retinal fixation point location in the foveal avascular zone. Invest Ophthalmol Vis Sci 31:2099–2105PubMed

42.

Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577PubMed

Titel: Analysis of retinal fundus images for grading of diabetic retinopathy severity
verfasst von: M. H. Ahmad Fadzil
Lila Iznita Izhar
Hermawan Nugroho
Hanung Adi Nugroho
Publikationsdatum: 01.06.2011
Verlag: Springer-Verlag
Erschienen in: Medical & Biological Engineering & Computing / Ausgabe 6/2011
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-011-0734-2

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 6/2011

Differences in citation frequency of clinical and basic science papers in cardiovascular research

A hybrid strategy to integrate surface-based and mutual-information-based methods for co-registering brain SPECT and MR images

3D network model of NO transport in tissue

Biological surface modification of titanium surfaces using glow discharge plasma

Response to Dr. Annemiek J.M. Cornelissen editorial

Another role for nitric oxide in blood flow control?