Skip to main content
main-content
Top

Hint

Swipe to navigate through the articles of this issue

01-07-2019 | APPLIED PROBLEMS | Issue 3/2019

Pattern Recognition and Image Analysis 3/2019

Predictive Diagnosis of Glaucoma Based on Analysis of Focal Notching along the Neuro-Retinal Rim Using Machine Learning

Journal:
Pattern Recognition and Image Analysis > Issue 3/2019
Authors:
Rishav Mukherjee, Shamik Kundu, Kaushik Dutta, Anindya Sen, Somnath Majumdar
Important notes
An erratum to this article is available online at https://​doi.​org/​10.​1134/​S105466181904023​0.
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030155/MediaObjects/11493_2019_6019_Fig11_HTML.gif
Rishav Mukherjee received the B.Tech degree from Heritage Institute of Technology affiliated to Maulana Abul Kalam Azad University of Technology in 2018 in Electronics and Communication Engineering. He has successfully qualified GATE, examination held by IIT. He has been the joint first author to a previous research paper on Glaucoma detection from CFIs. His research interests include image processing, biomedical image analysis, networking and cognitive radio networks (CRN).
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030155/MediaObjects/11493_2019_6019_Fig12_HTML.gif
Shamik Kundu received his B.Tech degree in Electronics and Communications Engineering from Heritage Institute of Technology affiliated to Maulana Abul Kalam Azad University of Technology in 2018. He has been the joint first author to a previous research paper on Glaucoma detection from CFIs. His research interests include signal and image processing, communications, and networks.
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030155/MediaObjects/11493_2019_6019_Fig13_HTML.gif
Kaushik Dutta received his B.Tech degree in Electronics and Communications Engineering from Heritage Institute of Technology affiliated to Maulana Abul Kalam Azad University of Technology in 2018. He has been the joint first author to a previous research paper on Glaucoma detection from CFIs. His research interests include biomedical image processing, computer vision, and cognitive radio networks.
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030155/MediaObjects/11493_2019_6019_Fig14_HTML.gif
Anindya Sen is a Professor at the department of Electronics and Communication Engineering, Heritage Institute of Technology, a private autonomous engineering college in Anandapur, Kolkata, India. He received his B.E. from Jadavpur University, India in the year 1980, PhD from University of Minnesota, Twin Cities in 1996, and got his Post-Doctoral training from University of Chicago from 1996 to 2000. He currently holds one US patent and thirty research paper publications. His research interests include, medical image processing, internet of things, artificial intelligence and VLSI design.
https://static-content.springer.com/image/art%3A10.1134%2FS1054661819030155/MediaObjects/11493_2019_6019_Fig15_HTML.gif
Somnath Majumdar is a senior consultant ophthalmologist in Kolkata, India for last 20 years. He is currently a consultant ophthalmologist for Apollo Hospitals, Kolkata and Fortis Hospitals. He had done post graduation from Dr. R.P. Centre for Ophthalmic Sciences, AIIMS, New Delhi and completed his FRCS (Edin. and Glasgow) in 2000. He is an expert in fields of Glaucoma, Cataract, and Retinal surgery.

Abstract

Automatic evaluation of the retinal fundus image is regarded as one of the most important future tools for early detection and treatment of progressive eye diseases like glaucoma. Glaucoma leads to progressive degeneration of vision which is characterized by shape deformation of the optic cup associated with focal notching, wherein the degeneration of the blood vessels results in the formation of a notch along the neuroretinal rim. In this study, we have developed a methodology for automated prediction of glaucoma based on feature analysis of the focal notching along the neuroretinal rim and cup to disc ratio values. This procedure has three phases: the first phase segments the optic disc and cup by suppressing the blood vessels with dynamic thresholding; the second phase computes the neuroretinal rim width to detect the presence and direction of notching by the conventional ISNT rule apart from calculating the cup-to-disc ratio from the color fundus image (CFI); the third phase uses linear support vector based machine learning algorithm by integrating extracted parameters as features for classification of CFIs into glaucomatous or normal. The algorithm outputs have been evaluated on a freely available database of 101 images, each marked with decision of five glaucoma expert ophthalmologists, thereby returning an accuracy rate of 87.128%.

Please log in to get access to this content

To get access to this content you need the following product:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

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

  • über 69.000 Bücher
  • über 500 Zeitschriften

aus folgenden Fachgebieten:

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

Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 58.000 Bücher
  • über 300 Zeitschriften

aus folgenden Fachgebieten:

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




Testen Sie jetzt 30 Tage kostenlos.

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 50.000 Bücher
  • über 380 Zeitschriften

aus folgenden Fachgebieten:

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




Testen Sie jetzt 30 Tage kostenlos.

Literature
About this article

Other articles of this Issue 3/2019

Pattern Recognition and Image Analysis 3/2019 Go to the issue

REPRESENTATION, PROCESSING, ANALYSIS, AND UNDERSTANDING OF IMAGES

Image Classification Model Using Visual Bag of Semantic Words

MATHEMATICAL METHOD IN PATTERN RECOGNITION

Lightweight Nearest Convex Hull Classifier

REPRESENTATION, PROCESSING, ANALYSIS, AND UNDERSTANDING OF IMAGES

Robust Visual Tracking Based on Relaxed Target Representation

Premium Partner

    Image Credits