Journal of Diagnostic Techniques and Biomedical AnalysisISSN: 2469-5653

All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.

Research Article, J Diagn Tech Biomed Anal Vol: 6 Issue: 1

Computer Aided Diagnostic of Dry Eye: Toward an Automatic Diagnosis from Noisy Tear Ferning Images

Ali S Saad*

College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia

*Corresponding Author : Ali S Saad
College of Applied Medical Sciences, Riyadh, Saudi Arabia
Tel: +966508975969

Received: October 17, 2016 Accepted: November 11, 2016 Published: January 02, 2017

Citation: Saad AS (2017) Computer Aided Diagnostic of Dry Eye: Toward an Automatic Diagnosis from Noisy Tear Ferning Images. J Diagn Tech Biomed Anal 6:1. doi: 10.4172/2469-5653.1000116


This work focuses on the use of digital image analysis for automatic diagnose of Dry Eye. Recently, scaling of tear ferning images been used to diagnose dry eye. A classification approach in wavelet space is proposed as an initial step toward an automatic diagnose of dry eye. Correlation coefficient, in wavelet space, between a reference image and unclassified noisy tear ferning image, at different level of wavelet decomposition is used as classifier. The noise in the images has a great impact on the value of the correlation coefficient (CF). The noise reduction using wavelet technics at different level of wavelet decomposition (WD) provides a strong improvement for the classification (diagnose) of tear ferning noisy images. A set of reference image representing the scaling of the tear ferning images is used. The CFs between the reference images against each other was used in order to estimate the value of the background noise. The CF was first performed between the reference images and the noisy ones without wavelet decomposition. Then, CFs was obtained for five levels of WD. A comparison of the CFs at different wavelet levels is performed. It shows that CF values highly increase upon increasing the level of WD. This result provides strong evidence that the proposed new approach for automatic dry eye diagnosis is highly promising with the advantage of great accuracy and time processing reduction. Cloud computing is an emerging hypothesis of computing that replaces computing as a personal commodity by computing as a public utility. As such, it offers many advantages in terms of public utility system, in terms of economy of scale, flexibility and convenience. Here many issues rises like not least of which are: loss of control and security. The aim of this study, to understand the different approaches of virtualization and appropriate approach of virtualization in cloud computing.

Keywords: Wavelet decomposition, Correlation coefficient, Filtering, Dry eye, Tear ferning, Classification

international publisher, scitechnol, subscription journals, subscription, international, publisher, science

Track Your Manuscript

Awards Nomination

open access