Literature DB >> 21271293

Analysis of retinal fundus images for grading of diabetic retinopathy severity.

M H Ahmad Fadzil1, Lila Iznita Izhar, Hermawan Nugroho, Hanung Adi Nugroho.   

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.

Entities:  

Mesh:

Year:  2011        PMID: 21271293     DOI: 10.1007/s11517-011-0734-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  19 in total

1.  A contribution of image processing to the diagnosis of diabetic retinopathy--detection of exudates in color fundus images of the human retina.

Authors:  Thomas Walter; Jean-Claude Klein; Pascale Massin; Ali Erginay
Journal:  IEEE Trans Med Imaging       Date:  2002-10       Impact factor: 10.048

Review 2.  ROC analysis in medical imaging: a tutorial review of the literature.

Authors:  Charles E Metz
Journal:  Radiol Phys Technol       Date:  2007-10-27

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

Authors:  M H Ahmad Fadzil; Lila Iznita Izhar; Hanung Adi Nugroho
Journal:  Comput Biol Med       Date:  2010-06-22       Impact factor: 4.589

4.  Psychophysical measurement of the size and shape of the human foveal avascular zone.

Authors:  A Bradley; R A Applegate; B S Zeffren; W A van Heuven
Journal:  Ophthalmic Physiol Opt       Date:  1992-01       Impact factor: 3.117

5.  Extraction and reconstruction of retinal vasculature.

Authors:  M H Ahmad Fadzil; Lila Iznita Izhar; P A Venkatachalam; T V N Karunakar
Journal:  J Med Eng Technol       Date:  2007 Nov-Dec

6.  Measuring fundus landmarks.

Authors:  A M Mansour
Journal:  Invest Ophthalmol Vis Sci       Date:  1990-01       Impact factor: 4.799

Review 7.  Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.

Authors:  M H Zweig; G Campbell
Journal:  Clin Chem       Date:  1993-04       Impact factor: 8.327

8.  Foveal avascular zone in diabetic retinopathy: quantitative vs qualitative assessment.

Authors:  J Conrath; R Giorgi; D Raccah; B Ridings
Journal:  Eye (Lond)       Date:  2005-03       Impact factor: 3.775

9.  Automated identification of diabetic retinopathy stages using digital fundus images.

Authors:  Jagadish Nayak; P Subbanna Bhat; Rajendra Acharya; C M Lim; Manjunath Kagathi
Journal:  J Med Syst       Date:  2008-04       Impact factor: 4.460

10.  A decision support framework for automated screening of diabetic retinopathy.

Authors:  P Kahai; K R Namuduri; H Thompson
Journal:  Int J Biomed Imaging       Date:  2006-02-02
View more
  8 in total

1.  An exudate detection method for diagnosis risk of diabetic macular edema in retinal images using feature-based and supervised classification.

Authors:  D Marin; M E Gegundez-Arias; B Ponte; F Alvarez; J Garrido; C Ortega; M J Vasallo; J M Bravo
Journal:  Med Biol Eng Comput       Date:  2018-01-10       Impact factor: 2.602

2.  Classification of diabetes maculopathy images using data-adaptive neuro-fuzzy inference classifier.

Authors:  Sulaimon Ibrahim; Pradeep Chowriappa; Sumeet Dua; U Rajendra Acharya; Kevin Noronha; Sulatha Bhandary; Hatwib Mugasa
Journal:  Med Biol Eng Comput       Date:  2015-06-25       Impact factor: 2.602

3.  Application of higher-order spectra for automated grading of diabetic maculopathy.

Authors:  Muthu Rama Krishnan Mookiah; U Rajendra Acharya; Vinod Chandran; Roshan Joy Martis; Jen Hong Tan; Joel E W Koh; Chua Kuang Chua; Louis Tong; Augustinus Laude
Journal:  Med Biol Eng Comput       Date:  2015-04-18       Impact factor: 2.602

4.  An Intelligent Segmentation and Diagnosis Method for Diabetic Retinopathy Based on Improved U-NET Network.

Authors:  Qianjin Li; Shanshan Fan; Changsheng Chen
Journal:  J Med Syst       Date:  2019-08-12       Impact factor: 4.460

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

Authors:  Qaisar Abbas; Irene Fondon; Auxiliadora Sarmiento; Soledad Jiménez; Pedro Alemany
Journal:  Med Biol Eng Comput       Date:  2017-03-28       Impact factor: 2.602

6.  Automatic Detection of Diabetic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm.

Authors:  Feng Li; Zheng Liu; Hua Chen; Minshan Jiang; Xuedian Zhang; Zhizheng Wu
Journal:  Transl Vis Sci Technol       Date:  2019-11-12       Impact factor: 3.283

7.  Diabetic retinopathy grading by digital curvelet transform.

Authors:  Shirin Hajeb Mohammad Alipour; Hossein Rabbani; Mohammad Reza Akhlaghi
Journal:  Comput Math Methods Med       Date:  2012-09-12       Impact factor: 2.238

8.  Which Color Channel Is Better for Diagnosing Retinal Diseases Automatically in Color Fundus Photographs?

Authors:  Sangeeta Biswas; Md Iqbal Aziz Khan; Md Tanvir Hossain; Angkan Biswas; Takayoshi Nakai; Johan Rohdin
Journal:  Life (Basel)       Date:  2022-06-28
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.