International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 03|Mar -2017
www.irjet.net
e-ISSN: 2395 -0056 p-ISSN: 2395-0072
A Survey on Retinal Area Detector From Scanning Laser Ophthalmoscope (SLO) Images for Diagnosing Retinal Diseases Ms. SARIKA SAMBHAJIRAO KADAM1, Mr. SANTOSH D. KALE2 1PG
Scholar , Department of Electronics and Telecommunication, SVPM College of Engineering, Malegaon (BK), Maharashtra, India.
2Assistant
Professor , Department of Electronics and Telecommunication, SVPM College of Engineering, Malegaon (BK), Maharashtra, India.
-----------------------------------------------------------------****------------------------------------------------------------------------Abstract: Distinguishing the true retinal area from
correctly segment artifacts from the retinal eye
artefacts in SLO images is a challenging task and first
image. In the retinal area detection there are
important step towards computer-aided disease diagnosis.
extraneous objects involved like localization of
Retinal diseases are fatal and have to be detected and
eyelids, eyelashes and dust (EED) on optical
treated during the early stages itself otherwise it result in
surfaces. That may appear in focus. So, Automatic
the loss of eyesight. The purpose of the retina is to receive
segmentation of these artifacts from a retinal image
the light that is focused from lens, convert it into neural
is an important task. EED locating retina is a key
signals, and send these signals to the brain for visual recognition. The retina deal with a picture from the
task because the major part of the retina is almost
focused light, and the brain decide what the picture is.
partially occluded by artifacts, which will increase
Hence the retina plays important role in vision, damage to
the danger of faulty acceptance and faulty
it can also cause problems such as permanent blindness.
recognition if not excluded properly. Identification
So we find out whether a retina is true or not for the
of retinal diseases is based on manual observations
detection of retinal diseases. This paper focuses survey on
technique. Patients eye are captured using fundus
automatically extract out true retinal area from an SLO
camera
image based on image processing. And further the retinal
or
scanning
laser
ophthalmoscope.
Optometrists and ophthalmologists always depend
area is used to classify the retinal disorder based on
on image operations such as change of contrast and
machine learning approaches.
zooming to clarify these images and diagnose
Keywords: Feature selection, scanning laser
results based on their own experience and
ophthalmoscope (SLO), retinal artefacts extraction,
knowledge. Automated analysis of retinal images
retinal image analysis, retinal Disorders.
reduce the time that the clinicians need for looking at images which can expect more patients to be
1. INTRODUCTION
screened out and more consistent diagnoses can be
In the early treatments of retinal eye diseases
given in time efficient manner.
we avoid the vision loss. Hence focus is always on
The purpose of
performing this study is to develop a method that Š 2017, IRJET
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