matlab coding for cup to disc ratio detection in glaucoma
#1
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cup to disc ratio matlab coding njeed after disc detection through bnactive contour model
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#2
Glaucoma is defined as „multi factorial optic
neuropathy. Which is a potentially blinding disease
which affects 66.8 million people worldwide. Risk
assessment of the disease goes a long way in diagnosis
and management of the disease. The blood pressure of
eye is known as intra ocular pressure (IOP) and if it
increases to dangerous level, then affects the optic nerve
axon. Thus, increase in IOP has a significant risk factor
for developing glaucoma. This can result in decrease in
vision and leads to blindness. Glaucoma is similar to
intra ocular hypertension, but glaucoma results into
optic nerve damage. Vision loss is caused by damage to
the optic nerve, which carries image information from
the light receptors to the brain. The glaucoma leads to
permanent damage to the optic nerve and result in vision
loss [1].
The ailment is physiologically described as the
degeneration of optic nerve cells, and is characterized by
changes in the optic nerve head and visual field.
Although Glaucomatous damage is irreversible, early
detection and subsequent medical intervention by
ophthalmologists is effective in slowing the progression
of the disease. Fig. 1 shows the glaucoma image with
nomenclature representation [2].
The detection of Optic cup and disc position is a prerequisite
for the computation of some important
diagnostic indexes like glaucoma. The optic disc is the
region on the retina at which optic nerve axon enters and
leaves the eye. The optic disc was located by identifying
the area with the highest variation in intensity of
adjacent pixels [1].
Fig 1: Glaucoma image.
The optic cup to disc image is used to examine of some
diseases such as glaucoma. Changes in the optic disc can
indicate the current position and progression of a certain
disease. The optic cup and disc location is an important
issue in fundus image analysis
The preprocessing step is introduced to reduce bright
spots that are likely to introduce errors in the ROI
localization. Next, the entire image is processed to
locate the most likely location of the ROI. The ROI
localization method is a key component of ARGALI,
which we developed for glaucoma risk diagnosis
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#3
Thank you very much! In fact, my teacher let me search some code for measuring the cup-to-disk ratio.
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